Formant tracking using segmental phonemic information

analog 模拟digital 数字的binary-coded number 二进制编码数electromagnetic induction 电磁感应telegraph 电报triode vacuum tube 三级真空管broadcasting 广播amplitude modulation (AM)幅度调制frequency modulation (FM)频率调制phase modulation (PM) 相位调制transistor 晶体管linear integrated circuit 线性集成电路microwave 微波satellite 卫星optical fiber 光纤shortwave 短波negative-feedback amplifier 负反馈放大器PCM（Pulse-Code Modulation）脉冲编码调制time-division multiplexing (TDM)时分多路stereo FM 立体声调频error-correction code 纠错编码adaptive equalization 自适应均衡random access memory (RAM)随机存取存储器VLSI(very large scale integration)超大规模集成FAX (facsimile) 传真cellular telephone 蜂窝电话移动电话oscilloscope 示波器spread spectrum system 扩频系统ISDN(integrated services digital network)综合业务数字网HDTV(high definition television)高清晰度电视transmitter 发射机channel 信道频道通道receiver 接收机baseband 基带bandwidth (BW)频带宽度带宽ADC(analog-digital converter)模数变换器carrier 载波载流子bandpass signal 带通信号signal sideband (SSB)单边带phase-shift keying(PSK)相移键控ITU(international telecommunications union)国际电信联盟PTN(public telecommunications network)公用电信网络LOS propagation 视线传播ionospheric reflection 电离层反射high fidelity (Hi-Fi)高保真度signal-to-noise 信噪比interference 干扰mapping 映射dimension 维数量纲frequency selectivity 频率选择性photocathode 光电阴极raster scanning 光栅扫描blanking pulse 消隐脉冲multiplexer 多路转换器encoder 编码器decoder 译码器pixel 像素vocal tract filter 声道滤波器melodic structure 韵律结构harmonic structure 谐波结构interlaced fields 交替的场horizontal retrace 水平行回程primary colors 基色interactive video 交互式视频ASCII 美国标准信息交换码DCT (discrete cosine transform)离散余弦变换JPEG (joint photographic experts group)联合图像专家组MPEG(motion photographic experts group)) 活动图像专家组synchronous transmission 同步传输asynchronous transmission 异步传输frame 帧frame-packing 成帧modeling 建模Fourier series(FS) 傅里叶级数transmission medium 传输介质coaxial cable 同轴电缆instantaneous power 瞬时功率decibel 分贝dBRF(radio frequency)射频commutator 换向器转接器ripple 波纹起伏ionosphere 电离层potential difference 电位差shot noise 散弹噪声flicker noise 闪变噪声noise figure 噪声系数mathematic model 数学模型rms value 均方根值orthogonal series 正交系数power density spectrum 功率谱密度common logarithm 以10为底的对数DC power supply 直流电源AC ripple 交流波纹AM receiver 调幅接收机thermal noise 热噪声root-mean-square(rms)alternating current (AC) 交流direct current (DC) 直流cable television (CATV)有线电视field-effect transistor (FET)场效应晶体管bipolar junction transistor(BJT)晶体三极管inductor coil 电感线圈inductor 电感器rating power 额定功率capacitor 电容器quality factor 品质因数piezoelectric crystal 压电晶体inductive reactance 感抗capacitive reactance容抗susceptance 电纳mounting capacitance 安装电容impedance 阻抗notch filter 陷波式滤波器oscillator 振荡器flywheel effect 飞轮效应feedback 反馈loop gain 环路增益voltage gain 电压增益amplifier 放大器扩音器emitter 发射机base 基极collector 集电极inductive coupling 电感耦合radio-frequency choke (RFC)射频扼流圈junction capacitance 结电容integrated-circuit (IC)集成电路buffer amplifier 缓冲放大器chip 芯片frequency synthesizer 频率合成器energy dissipation 能耗tank circuit 槽路sinusoidal signal 正弦信号crystal oscillator 晶体振荡器monolithic chip 单片VHF(very high frequency) 甚高频UHF（ultra high frequency）超高频uncertainty 不确定性误差probability 概率几率autocorrelation 自相关函数covariance 协方差strict-sense stationary process 狭义平稳过程严平稳过程wide- sense stationary process 广义平稳过程宽平稳过程second-order process 二阶平稳过程infinity 无穷大ergodic process 各态遍历过程Gaussian process 高斯过程stochastic process 随机过程random signal 随机信号deterministic signal 确定信号argument function 被积函数joint probability distribution 联合概率分布statistical parameter 统计参数mathematical expectation 数学期望Gaussian white noise 高斯白噪声ensemble average 总体平均time average 时间平均correlation function 相关函数auto covariance 自协方差the first-order moment 一阶矩sample space 样本空间random variable 随机变量unbiased estimation 无偏估计normalized 归一化linear functional 线性泛函antenna 天线nonlinear 非线性的envelope 包络AM DSBFC 全载波的双边带调幅modulator 调制器class A amplifier (A)甲类放大器transformer 变压器double sideband (DSB)双边带AM envelope调幅包络carrier signal 载波信号voice-grade 话音级modulation coefficient 调制系数lower side band (LSB)下边带lower side frequency (LSF)上边频upper side band (USB)上边带upper side frequency (USF)上边频phasor 相量vector 矢量nonlinear mixing非线性混频frequency domain 频域coupling capacitor 耦合电容final stage 末级（电路）modulating signal 调制信号modulated wave 已调波emitter modulator 发射机调制器DSB AM 双边带幅度调制transistorized transmission 晶体管化发射机unitless 无量纲的lo-level modulator 低电平调制器modulation 调制过程modulator 实现调制的电路modulating signal 调制信号demodulation 在接收端从已调波中恢复调制信号的过程demodulator 解调器duplicate 复制品，副本inversion 倒置elimination 消除canonical 规范的quadrature 正交discrimination 辨别，区别，识别力nonoverlapping 不相重叠的resonator 谐振器，振荡器simultaneous 同时的，同时发生的subsequent 后来的，并发的reinforcement 增援，加强，加固junction 连接，交叉点prescribe 指示，规定cutoff 截止，切掉coherent 相干的，一致的locally 在本地undergo 经历，遭受，忍受difference 差分，差别angle modulation 角度调制complex envelop 复包络proportional 比例量，成比例的intergral 积分，综合deviation constant 偏移常数subscript 下标的integrator 积分器，综合者cascade 串联，级联instantaneous 瞬间的，即刻的frequency deviation 频率偏移nonnegative 非负的正的peak-to-peak deviation 峰峰偏移phase modulation index 调相指数frequency modulation index 调频指数sinusoida 正弦的superposition 重叠，叠加原理approximation 接近，近似值sideband 边带multiplier 乘数，乘法器narrowband frequency modulation(NBFM)窄带频率调制wideband frequency modulation(WBFM)宽带频率调制frequency multiplication 倍频limiter 限幅器voltage-controlled-oscillator( V OC)压控振荡器incorporate合并混合PLL(phase locked loop) 锁相环frequency divider 分频器tolerance 耐性容限power spectral density（PSD）功率谱密度probability density function(PDF)概率密度函数intuitive直觉的viewpoint 观点emphasis加重preemphasis 预加重deemphasis去加重boost升压，attenuate 减弱信号，衰减longitudinalpotential位差，势差balun 巴伦，平衡—不平衡变压器electrostatic shield 静电屏蔽ribbon cable 带状传输线coaxial cable 同轴电缆open-wire 明线insulated 绝缘的，隔热的sheath 阳极，屏极stray capacitance 寄生电容杂散电容spacer 逆电流器dielectric 电介质绝缘体susceptible 易受影响的pick-up 获得polyethylene聚乙烯permittivity 介电常数reflectometry反射计impairment 损害，损伤echo 回声，回波prependicular 垂直的transponder 微型转发器vacuum 真空encounter 遭遇遇到infrared 红外线ultraviolet 紫外线refraction 折射diffract 衍射interference 干涉collide 碰撞penetrate 穿透渗透curve 曲线弯曲diffuse 漫射散开redistribution 重新分配opaque 不透明物phenomenon 现象wavelet小波finite 有限的simultaneously同时的polarization偏振极化negligible可以忽略的conductivity 传导性传导率induce感应navigation导航curvature曲率troposphere对流层ionize电离molecule 分子exert 施加vibrate 震动equivalent相当的ionization离子化nonuniform不均匀的stratified分层的parabolic抛物线的focal焦点resonance谐振共振dipole双极子偶极子mast天线竿triode 三极真空管klystron调速管magnetron磁控管radiotelephone 无线电话elliptically椭圆形的feedpoint馈点isotropic等方性的reciproal互易的beamwidth波束宽度omnidirectional全方向的parasitic寄生的concave凹的inphase同相的reradiated在辐射convergent汇聚性的convex凸的broadside侧面的crisscross十字形交叉power splitter 功率分配器dielectric电介质绝缘体boundary边界photophone光电话impurity杂质混杂物megabit百万兆位dispersion色散pulsing脉冲调制repester转发器regenerator再生器photodetector光电探测器threshold阀值，门限timing时序thermoelectric电热的splic接合cooler冷却器packaging封装adapter适配器jumper跳线overload超过负荷multiplexer多路复用器demultiplexer多路信号分离器doped 掺杂质的very large integration(VLSI)超大规模集成电路digital signal processing(DSP)数字信号处理noise immunity抗干扰度encryption加密programmable可编程的multipath and fading多径衰减power efficiency功率效率bandwidth efficiency带宽效率fidelity保真度pulse-width 脉冲宽度throughput吞吐量non-fading channel无衰落信道multimum-shift-keyed(MSK)最小位移键控on-off keying(OOK)开关键控unipolar 单极性的binary phase-shift keying(BPSK)二进制相移键控mark frequency传号频率space frequency空号频率premodulation预调制cosine-rolloff filter余弦滚降滤波器pilot carrier导频载波digital modulation index数字调制指数null-to-null bandwidth零点-零点带宽coherent相干检波ambiguity含糊differential差分编码integrate-and-dump matched filter积分清楚匹配滤波器digital-to-analog converter(DAC) 数模转换器offset 偏移量wavelength-division multiplexing(WDM)波分复用dense-WDM密集波分复用end-fire-array 端射阵phased array 相控阵inpedence matcher 阻抗匹配器erbium-doped fiber amplifiers 掺铒光纤放大器binary-coded 二进制编码的mainframe 主机，大型机interconnect 使互相连接information highway 信息高速公路indefinitely 不确定的facility 容易，便利，设备，工具secondary 次要的，二级的，第二的peripheral 外围的，外围设备data terminal equipment(DTE) 数据终端设备data conmunications equipment(DCE)数据通信设备vice versa 反之亦然serial 串行的parallel 并行的host主机topology 拓扑，布局，mesh 网孔，网套，陷阱citizens band 居民频带syntax 语法，句子结构interrogation 审问，问号American Standard Code for Information Interchange (ASCII) 美国信息交换标准码Extended Binary-Code Decimal Interchange Code (EBCDIC) 扩充的二-十进制交换码teletype code 电传打字机电码least significant bit(LSB) 最低有效位most significant bit(MSB) 最高有效位partity 同等，平等，奇偶校验error control 差错控制error detection 检错error correction 纠错echoplex 回送checksum 校验和cyclic redundancy checking(CRC) 循环冗余检查backspace 退后一格，退格erroneous 错误的，不正确的circuitry 电线，线路hex 十六进制polynomial 多项式的symbol substitution 符号替换selective retransmission 选择性重传forward error correction 前向纠错ingtegrity 正直，诚实，完整性turnaround 回车场，转变，转向prior 在先，居先Hamming code 汉明码electronic mail 电子邮件handset 电话听筒，手机，手持机cellular phone 便携式电话，移动电话set-top TV box 电视机顶盒telephony 电话学，电话技术conversation 会话，交谈circuit switching 电路交换mechanical 机械的，呆板的bit stream 位流，比特流interface 分界面，界面，接口instruction 指令common channel signaling 公共信道信令trunk 干线中继线路subscriber telephone 电话用户digital carrier system 数字载波系统accommodate 供应，调节，调和deviate 异化，越轨，偏离nominal 名义上得Integrated Services Digital Network(ISDN)综合业务数字网bidirectional 双向的full-duplex 全双工的facsimile 摹写，传真remote monitoring 远程监控videotext 可视图文videophone 可视电话attenuation 变薄，变细，衰减Asymmetric Digital Subscriber Line(ADSL)非对称用户数字线protocol 草案，协议character at a time 每次传送一个字符cross-talk 他处传来的干扰，串话severe 严厉的，剧烈的，严重的modem 调制解调器synchronous transmission 同步传输SDLC(Synchronous Data Link Control)同步数据链路控制HDLC(High-Level Data Link Control)高级数据链路控制LAPB 平衡型链路访问规程packet 包装，信息包preamble 前言，序，前导信号self-synchronizing code 自同步码store-and-forward packet-switching存储转发分组交换point-to-point 点对点intermittent 间歇的，断断续续的statistical multiplexing 统计复用Ethernet 以太网Chip 碎片，芯片，筹码LAN(Local Area Network) 局域网，本地网WAN(Wide Area Network) 广域网Asynchronous Transfer Mode(ATM)异步传输模式cell 蜂窝，信源VCI 虚通路标识optical fiber 光纤cable television 有线电视，电缆电视Community Antenna Television(CATV)有线电视，公用天线电视obstruction 阻塞，妨碍，障碍物feeder 馈电线，电源线，连接线unidirectional 单向的，单向性的hybrid fiber/coaxial(HFC) 光缆与同轴电缆混合网fiber-to-the-curb(FTTC) 光纤到路边cable modem 电缆调制解调器nonadjacent 不临近的，不毗连的turn over 翻身，折腾，反复考虑Peer-to-Peer 对等网络wireline 有线线路toehold 排除障碍的方法notebook 笔记薄，笔记本palm-sized computer 掌上电脑backbone 脊椎，中枢，支柱，勇气terabit兆兆位Web 环球网bandwidth 带宽channel 信道，频道delay 延迟，时延hierarchy 层次结构pitch 音调substantially 充分的voiced 有声的，浊音的quasi-stationary 拟稳态的formant 共振峰，构形成分resonance 共鸣，回声，反响，谐振vocal track 声带vocoder 声码器VF(V oice Frequency) 话音频率adaptive subband coding 自适应自带编码vector quantization 矢量量化code excited linear prediction 码激励线性预测vector-sum excited linear prediction矢量和激励线性预测analysis-by-synthesis technique 分析合成技术codebook 码本best match 最佳匹配codec 多媒体数字信号编解码器probability distribution 概率分布autocorrelation 自相关successive 继承的，连续的unvoiced清音的quasiperiodicity 准周期性bandlimited 带限的time-discietized 时间离散化reconstruct 重建，改造，推想monotonically decreasing function 单调递减函数exponential 指数的，幂数的Gaussian distribution 高斯分布，正态分布variance 方差manifestation 显示，表现，示威运动coding gain 编码增益spectral flatness measure(SFM)谱平坦性测度geometric mean 几何平均redundancy冗余cordless 不用电线的，无绳preferentially 优待的perception 理解，感知，感觉harmonic 谐和的，和声的，谐波，谐函数sub-band coding(SBC) 子带编码block transform coding 块变换编码bandpass 带通band-splitting 子带分解articulation index 传声准率portion 一部分，一分in tune 和调子convolution 卷积，卷积积分multiplex 多路传输，多路复用alias 混淆，折叠quadrature mirror filters(QMF) 正交镜像滤波器latecy 等待时间，延迟cellular telephone system 蜂窝(移动)电话系统performance 性能，能力signal-to-noise radio 信噪比mean square error(MSE) 均方误差weighted 加权的diagnostic rhyme test(DRT) 押韵诊断测试diagnostic acceptability measure(DAM)接受能力诊断测试mean opinion score(MOS)平均主观评分inherently 天地性，固有性spectrum 频谱utilization 利用intrastate 周内的haul 托运距离noncoherent 非相干的simultaneously 同时的deviator 偏差器，致偏器scheme 安排，配置，计划，方案uniform 统一的，相同的，一致的，均衡的eventually 最后，终于mixer 混频器heterodyning 外差法，外差作用demodulator 解调器convey 搬运传达destination 目的地phenomenal 显著的telemetry 遥感勘测，自动测量记录传导diminishing 逐渐缩小的accommodate 供给，容纳investigate 调查，研究avenue 方法途径prohibitive 禁止的，抑制的adequate 适当的，足够的quantize 使量子化，量化discrete 不连续的，离散的aptly 适当的，适宜的lean 倾向，偏向designator 指示者，指定者so-called 所谓的，号称的astronomical 天文学的，天文celestial body 天体payload 有效载荷military 军事的，军用的subscriber 订户，签署者geostationary 与地球的相对位置之不变的aeronautical 航空学的roughly 概略的obstacle 障碍，障碍物govern 统治，支配constituent 要素hub 网络集线器，网络中心margin 极限，富余architecture 体系结构platform 平台cruise 巡航gateway 网关altenatively 作为选择，二者选一overlap 与..交叠implement 实现，执行hybrid 混合的latitude 纬度，地区guarantee 保证，担保nowadays 现今，现在sophisticated 高度发展的，精密复杂的coordinate 协调，调整，整理equatorial 近赤道的，赤道的distributed 分布式的stationary 固定的deploy 配置isotropic各向同性的specialise 专门研究，深入miche 放在适当的位置marketability 可销售性crosspolarization 交叉极化furthermore 此外，而且critical 紧要的，关键性的，临界的majority 多数，大半degrading 丧失体面的，可耻的，不名誉的coding 编码intermediate 中间的alongside 并排地regulate 管制，控制budget 预算degrade 降低，降级，退化compensate 补偿，付报酬subdivide 再分，细分feasible 切实可行的burst 突发，脉冲periodic 周期的，定期的synchronize 同步recovery 恢复expansion 扩充，扩展vital 至关重要的，必须得preassign 预先指定，预先分配reservation 预定，预约dynamic 动态的eliminate 消除，去除uncoordinated 不协调的collision 碰撞，冲突implementation 执行，实现retransmission 重发，转播optimal 最佳的，最理想的corresponding 相应的yielding 出产，生长，生产incremental 增加的magnitude 大小，数量，模algorithm 算法encoding 编码concatenation 串联，连锁node 节点tolerant 容许的literally 逐字的antijam 抗干扰contiguous 临近的，邻接的authentication 证明，鉴定adequately 充分的eavesdropper 偷听者pseudorandom 伪随机的simultaneously 同时的excel优秀penalty 损失unpredictable 不可预知的correlation 相互关系，相关性clutter混乱mobile telephone service 移动电话业务monster 怪物，妖怪，巨人methodology 一套方法provoke 激怒，挑拨，煽动，驱使regardless 不管，不顾terminology 术语学transceiver 无线电收发机，收发器pedestrian 步行者，徒步的，通俗的base station 基站scramble 扰频municipal 市政的，地方自治的trunking 中继census 人口普查hexagonal 六角形，六边形的honeycomb 蜂巢，蜂窝in accordance with 与..一致，依照macrocell 宏单元，宏小区radius 半径，范围，界限microcell 微小区virtue 德行，美德，贞操，优点，功效，效力mild 温和的，温柔的，适度的overlay 覆盖，microcellular 微小区intriguing 迷人的，有迷惑力的infrastructure 下部结构，基础组织splitting 分裂，裂解sector 使分成部分，扇形扫描overhead 在头上的，高架的handoff 手递手传递，移交metropolitan 首都的，大城市United States Digital Cellular(USDC)美国数字蜂窝系统compatible 谐调的，一致的，兼容的reuse 再使用time-division multiple accessing(TDMA)时分多址time slot 时间空档，时隙geographical 地理学得，地理的interleaving 交叉，交错threeflod 三倍encrypt 加密decrypt 解释明白，解密safeguard 维护，捍卫，eavesdropping 偷听channelization通信波道的选择coed-division multiple accession(CDMA) 码分多址Pilot 飞行员differentiate 区分，区别，微分spread-spectrum 扩频coherent 黏在一起的，相干的graceful 优美的，雅致的，适度的real time 实时asynchronous 不同时的，异步的重点词汇。

LOW-FREQUENCY ACTIVE TOWED SONAR (LFATS)LFATS is a full-feature, long-range,low-frequency variable depth sonarDeveloped for active sonar operation against modern dieselelectric submarines, LFATS has demonstrated consistent detection performance in shallow and deep water. LFATS also provides a passive mode and includes a full set of passive tools and features.COMPACT SIZELFATS is a small, lightweight, air-transportable, ruggedized system designed specifically for easy installation on small vessels. CONFIGURABLELFATS can operate in a stand-alone configuration or be easily integrated into the ship’s combat system.TACTICAL BISTATIC AND MULTISTATIC CAPABILITYA robust infrastructure permits interoperability with the HELRAS helicopter dipping sonar and all key sonobuoys.HIGHLY MANEUVERABLEOwn-ship noise reduction processing algorithms, coupled with compact twin line receivers, enable short-scope towing for efficient maneuvering, fast deployment and unencumbered operation in shallow water.COMPACT WINCH AND HANDLING SYSTEMAn ultrastable structure assures safe, reliable operation in heavy seas and permits manual or console-controlled deployment, retrieval and depth-keeping. FULL 360° COVERAGEA dual parallel array configuration and advanced signal processing achieve instantaneous, unambiguous left/right target discrimination.SPACE-SAVING TRANSMITTERTOW-BODY CONFIGURATIONInnovative technology achievesomnidirectional, large aperture acousticperformance in a compact, sleek tow-body assembly.REVERBERATION SUPRESSIONThe unique transmitter design enablesforward, aft, port and starboarddirectional transmission. This capabilitydiverts energy concentration away fromshorelines and landmasses, minimizingreverb and optimizing target detection.SONAR PERFORMANCE PREDICTIONA key ingredient to mission planning,LFATS computes and displays systemdetection capability based on modeled ormeasured environmental data.Key Features>Wide-area search>Target detection, localization andclassification>T racking and attack>Embedded trainingSonar Processing>Active processing: State-of-the-art signal processing offers acomprehensive range of single- andmulti-pulse, FM and CW processingfor detection and tracking. Targetdetection, localization andclassification>P assive processing: LFATS featuresfull 100-to-2,000 Hz continuouswideband coverage. Broadband,DEMON and narrowband analyzers,torpedo alert and extendedtracking functions constitute asuite of passive tools to track andanalyze targets.>Playback mode: Playback isseamlessly integrated intopassive and active operation,enabling postanalysis of pre-recorded mission data and is a keycomponent to operator training.>Built-in test: Power-up, continuousbackground and operator-initiatedtest modes combine to boostsystem availability and accelerateoperational readiness.UNIQUE EXTENSION/RETRACTIONMECHANISM TRANSFORMS COMPACTTOW-BODY CONFIGURATION TO ALARGE-APERTURE MULTIDIRECTIONALTRANSMITTERDISPLAYS AND OPERATOR INTERFACES>State-of-the-art workstation-based operator machineinterface: Trackball, point-and-click control, pull-down menu function and parameter selection allows easy access to key information. >Displays: A strategic balance of multifunction displays,built on a modern OpenGL framework, offer flexible search, classification and geographic formats. Ground-stabilized, high-resolution color monitors capture details in the real-time processed sonar data. > B uilt-in operator aids: To simplify operation, LFATS provides recommended mode/parameter settings, automated range-of-day estimation and data history recall. >COTS hardware: LFATS incorporates a modular, expandable open architecture to accommodate future technology.L3Harrissellsht_LFATS© 2022 L3Harris Technologies, Inc. | 09/2022NON-EXPORT CONTROLLED - These item(s)/data have been reviewed in accordance with the InternationalTraffic in Arms Regulations (ITAR), 22 CFR part 120.33, and the Export Administration Regulations (EAR), 15 CFR 734(3)(b)(3), and may be released without export restrictions.L3Harris Technologies is an agile global aerospace and defense technology innovator, delivering end-to-endsolutions that meet customers’ mission-critical needs. The company provides advanced defense and commercial technologies across air, land, sea, space and cyber domains.t 818 367 0111 | f 818 364 2491 *******************WINCH AND HANDLINGSYSTEMSHIP ELECTRONICSTOWED SUBSYSTEMSONAR OPERATORCONSOLETRANSMIT POWERAMPLIFIER 1025 W. NASA Boulevard Melbourne, FL 32919SPECIFICATIONSOperating Modes Active, passive, test, playback, multi-staticSource Level 219 dB Omnidirectional, 222 dB Sector Steered Projector Elements 16 in 4 stavesTransmission Omnidirectional or by sector Operating Depth 15-to-300 m Survival Speed 30 knotsSize Winch & Handling Subsystem:180 in. x 138 in. x 84 in.(4.5 m x 3.5 m x 2.2 m)Sonar Operator Console:60 in. x 26 in. x 68 in.(1.52 m x 0.66 m x 1.73 m)Transmit Power Amplifier:42 in. x 28 in. x 68 in.(1.07 m x 0.71 m x 1.73 m)Weight Winch & Handling: 3,954 kg (8,717 lb.)Towed Subsystem: 678 kg (1,495 lb.)Ship Electronics: 928 kg (2,045 lb.)Platforms Frigates, corvettes, small patrol boats Receive ArrayConfiguration: Twin-lineNumber of channels: 48 per lineLength: 26.5 m (86.9 ft.)Array directivity: >18 dB @ 1,380 HzLFATS PROCESSINGActiveActive Band 1,200-to-1,00 HzProcessing CW, FM, wavetrain, multi-pulse matched filtering Pulse Lengths Range-dependent, .039 to 10 sec. max.FM Bandwidth 50, 100 and 300 HzTracking 20 auto and operator-initiated Displays PPI, bearing range, Doppler range, FM A-scan, geographic overlayRange Scale5, 10, 20, 40, and 80 kyd PassivePassive Band Continuous 100-to-2,000 HzProcessing Broadband, narrowband, ALI, DEMON and tracking Displays BTR, BFI, NALI, DEMON and LOFAR Tracking 20 auto and operator-initiatedCommonOwn-ship noise reduction, doppler nullification, directional audio。

Articulatory Tradeoffs Reduce Acoustic Variability DuringAmerican English /r/ ProductionFrank H. Guenther1,2, Carol Y. Espy-Wilson3,2, Suzanne E. Boyce4,2,Melanie L. Matthies5,2, Majid Zandipour2,1, and Joseph S. Perkell2,6 Journal of the Acoustical Society of America (1999), vol. 105, pp. 2854-2865.Address correspondence to:Prof. Frank H. GuentherBoston UniversityCenter for Adaptive Systems andDepartment of Cognitive and Neural Systems677 Beacon StreetBoston, MA, 02215Fax Number: (617) 353-7755Email: guenther@ABSTRACTThe American English phoneme/r/has long been associated with large amounts of articulatory variability during production.This paper investigates the hypothesis that the articulatory variations used by a speaker to produce/r/in different contexts exhibit systematic tradeoffs,or articulatory trading relations,that act to maintain a relatively stable acoustic signal despite the large variations in vocal tract shape.Acoustic and articulatory recordings were collected from seven speakers producing/r/infive phonetic contexts.For every speaker,the different articulator configurations used to produce/r/in the different phonetic contexts showed systematic tradeoffs,as evidenced by significant correlations between the positions of transducers mounted on the tongue.Analysis of acoustic and articulatory variabilities revealed that these tradeoffs act to reduce acoustic variability,thus allowing relatively large contextual variations in vocal tract shape for/r/ without seriously degrading the primary acoustic cue.Furthermore,some subjects appeared to use completely different articulatory gestures to produce/r/in different phonetic contexts.When viewed in light of current models of speech movement control,these results appear to favor models that utilize an acoustic or auditory target for each phoneme over models that utilize a vocal tract shape target for each 1Department of Cognitive and Neural Systems, Boston University2Research Laboratory of Electronics, Massachusetts Institute of Technology3Department of Electrical and Computer Engineering, Boston University4Department of Communication Sciences and Disorders, University of Cincinnati5Department of Communication Disorders, Boston University6Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology1. IntroductionThe American English phoneme/r/has long been associated with relatively large amounts of articulatory variability(Alwan,Narayanan,and Haker,1997;Delattre and Freeman,1968;Espy-Wilson and Boyce,1994;Hagiwara,1994,1995;Ong and Stone,1998;Westbury,Hashi,and Lindstrom,1995, 1998).In fact,the endpoints of the articulatory continuum for/r/can be analyzed as functionally different articulator configurations that use different primary articulators(tongue tip vs.tongue dorsum).These endpoints have been characterized in the literature as“bunched”(using the tongue dorsum)and “retroflexed”(using the tongue blade/tip).Often,the same speaker will use different types of/r/in different productions,e.g.,in different phonetic contexts.At the same time,the primary acoustic cue for/r/is relatively simple and stable:a deep dip in the trajectory of the third spectral energy peak of the acoustic waveform,or third formant frequency(F3)(Boyce and Espy-Wilson,1997;Delattre and Freeman,1968; Westbury et al.,1995,1998).Furthermore,no consistent acoustic difference between bunched and retroflexed /r/’s has been discovered.How is it that a speaker can produce perceptually acceptable/r/’s despite using such variable vocal tract shapes?One possible answer to this question is that the variations in vocal tract shape for/r/are not haphazard,but are instead systematically related in a way that maintains a relatively stable acoustic signal across productions despite large variations in vocal tract shape across productions.In other words,the different vocal tract shapes used to produce/r/by a particular subject might involve articulatory tradeoffs, or trading relations.The concept of articulatory trading relations is illustrated by the following example. Assume that narrowing either of two constrictions at different locations along the vocal tract(call them location1and location2)has the same effect on an important acoustic cue for a phoneme.Assume further that narrowing either constriction causes a reduction in F3.In such a case,one could use different combinations of the two constrictions to achieve the same acoustic effect.For example,to achieve a particular value of F3,one might form a very narrow constriction at location1and a less narrow constriction at location2,or one might alternatively form a very narrow constriction at location2and a less narrow constriction at location1.If a speaker used one of these options in one phonetic context and the other option in a second phonetic context,a negative covariance between the sizes of these two constrictions would be seen across phonetic contexts.The primary purpose of the current study is to investigate the issue of whether the various vocal tract shapes used by an individual to produce/r/in different phonetic contexts exhibit articulatory trading relations that act to maintain a relatively stable acoustic signal.As discussed at the end of this article,this issue has important implications for theories of speech motor control and speech rgely for this reason,several recent experiments have investigated the trading relations issue for phonemes other than/r/(e.g.,de Jong,1997;Perkell et al.,1993;Perkell,Matthies,and Svirsky,1994;Savariaux et al. 1995a),but the results have not been uniform across subjects:although most subjects exhibit expected articulatory trading relations,some others do not.A possible reason for this ambiguity is that these studies have primarily concentrated on one hypothesized trading relationship,and subjects who do not exhibit this trading relation may be exhibit other,unanalyzed trading relations that act to reduce acoustic variability. For example,Perkell et al.(1993)investigated an hypothesized trading relation between lip rounding and tongue body raising for the vowel/u/.Three of four subjects showed weak trading relations,but the fourth subject showed the opposite pattern.This fourth subject may have been using other trading relations that overrode the effect of the lip rounding/tongue body raising relationship.In the current study,we employ analysis procedures that allow us to assess the combined effects of multiple articulatory covariances on the variability of the acoustic signal.Furthermore,American English/r/was chosen1because the large amount of articulatory variability associated with/r/productions should make it easier to detect trading relations if they are present.2. Methods2.1. Data collectionAn electromagnetic midsagittal articulometer(EMMA)system(Perkell et al.,1992)was used to track the movements of six small(5mm long x2.5mm diameter)transducer coils.The coils were attached in the midsagittal plane to the tongue(3coils),lips(2coils),and lower incisor(1coil)with bio-compatible adhesive.Transducers were also placed on the upper incisor and the bridge of the nose,for defining a coordinate system with a maxillary frame of reference.A directional microphone was suspended14inches from the subject's mouth and the acoustic signal was recorded simulatenously with the EMMA signals. Standard EMMA calibration protocols were completed prior to each experiment(c.f.Perkell et al.,1992 for details).The current study focused on the positions of the three tongue transducers,which were located approximately 1, 2.5, and 5 cm back from the tongue tip (with the tongue in a neutral configuration).The seven subjects were young adults,two females(Subjects2and3)andfive males.They had no history of speech,language,or hearing deficits or pronounced regional dialects.Each of the seven subjects produced4-6repetitions of the carrier phrase"Say____for me"for each of thefive test utterances; /warav/,/wabrav/,/wadrav/,/wagrav/,and/wavrav/.The articulatory and acoustic data from these utterances were time-aligned to allow direct comparison between the two data types.2.2. F3 extraction and alignmentThe minimum measured F3value during/r/production,which can be thought of as the acoustic “center”of/r/,served as a landmark for time-alignment of the data across utterances for each speaker. Formant tracks were computed for all utterances using the ESPS/W A VES formant tracker and a51.2ms window and3.2ms frame rate.The F3minimum was detected using an automatic procedure thatfirst identified all sonorant regions,then located the point of minimal F3from the relevant sonorant regions.F3 values and transducer positions within a140ms time window centered at the F3minimum were extracted. Extracted F3traces for some utterances were corrupted due to technical difficulties in automatically tracking low amplitude and low frequency values of F3after stop consonants.Therefore,utterances whose F3tracks changed by more than200Hz in a3.2ms time step were eliminated from the study,leaving12to 27analyzed utterances per subject.After this elimination process,the tongue shapes at the F3minimum of the remaining utterances were visually inspected,and two additional utterances(one each for Subjects1 and4)were identified as having articulations that were incorrectly labeled as/r/by the automatic extraction process. These two utterances were also eliminated from the study.2.3. Effects of vocal tract shape parameters on F3The vocal tract shape for/r/involves a palatal constriction formed by the tongue in the anterior third of the tract.Roughly speaking,the third formant frequency(F3)of/r/is the resonance resulting from the cavities anterior to the palatal constriction(e.g.,Alwan et al.,1997;Espy-Wilson,Narayanan,Boyce,and Alwan,1997;Stevens,1998).This part of the vocal tract consists of an acoustic compliance due to a large front cavity volume and two parallel acoustic masses due to natural tapering by the teeth/lips and the palatal constriction behind the front cavity.The resulting resonance is inversely proportional to the product of the total acoustic mass and the acoustic compliance.Because it is difficult to accurately infer lip aperture from EMMA data,we focus on the effects of the acoustic mass due to the size and location of the palatal constriction.From these considerations,we conclude that the frequency of F3can be decreased by tongue movements that lengthen the front cavity(thereby increasing the acoustic compliance of the front cavity),lengthen the constriction(thereby increasing the acoustic mass of the constriction behind the front cavity),or decrease the area of the constriction(thereby increasing the acoustic mass of the constriction)2.The predicted effects of these movements on F3were confirmed using vocal tract area functions derived from structural MRI scans of a speaker producing/r/3.Two area functions were derived:one representing a“bunched”/r/configuration,and one representing a“retroflexed”/r/configuration.Three manipulations were carried out on each area function to test the effects on F3predicted from acoustic theory:(i)the palatal constriction was extended backward by narrowing the vocal tract area immediately behind the constriction,(ii)the front cavity was lengthened by displacing the palatal constriction backward,and(iii)the vocal tract area at the palatal constriction was decreased.For all three manipulations,an acoustic signal was synthesized(using S.Maeda’s VTCALCS program;Maeda,1990) and compared to the signal synthesized from the original area function.Each manipulation resulted in a lower F3 in both the bunched and retroflexed /r/ cases, as expected from the acoustic theory analysis.Because all three manipulations act to lower F3,subjects could maintain a relatively stable F3despite vocal tract shape variations across contexts if these variations involved tradeoffs between the different manipulations.When looking at the different vocal tract shapes for/r/across contexts,these tradeoffs would be manifested by correlations between constriction length,front cavity length,and constriction area. Specifically,the following three correlations would be expected to aid in maintaining a relatively stable F3 across utterances while allowing variations in vocal tract shape:(1)a negative correlation between constriction length and front cavity length,since increases inconstriction length and front cavity length both act to reduce F3,(2)a positive correlation between constriction length and constriction area,since increases inconstriction length reduce F3 and decreases in constriction area reduce F3, and(3)a positive correlation between front cavity length and constriction area,since increases in frontcavity length reduce F3 and decreases in constriction area reduce F3.2.4. Predicted articulatory covariancesTo determine whether a subject uses any of the three trading relations hypothesized above,we must first describe the trading relations in terms of the x and y coordinates of the tongue transducers.For tongue configurations during/r/production,a forward movement of the tongue front transducer generally corresponds to a shortening of the front cavity,an upward movement of the tongue front transducer generally corresponds to a decrease in the area of the palatal constriction for/r/,and,since the point of maximal constriction for/r/is typically anterior to the tongue back transducer,an upward movement of the tongue back transducer generally corresponds to a lengthening of the palatal constriction and possibly a decrease in the area of the constriction.When determining the signs of the transducer coordinate correlations corresponding to the trading relations delineated above,we must take into account that increasing values of the tongue front horizontal position correspond to decreases in front cavity length,and increasing values of the tongue front vertical position correspond to decreases in constriction area.From these considerations,we can surmise that the three trading relation strategies described above should be evidenced by the following articulatory correlations:(1) a positive correlation between tongue back height and tongue front horizontal position,(2) a negative correlation between tongue back height and tongue front height, and(3) a positive correlation between tongue front horizontal position and tongue front height.Note that the use of all three trading relations by a single subject is unlikely given that they impose competing constraints;i.e.,if tongue back height and tongue front horizontal position are positively correlated as in relation(1),and tongue front horizontal position and tongue front height are positively correlated as in relation(3),it is very likely that tongue back height and tongue front height will also be positively correlated, thus violating relation (2).2.5. Analysis of articulatory and acoustic variancesTo quantify the combined effects of articulatory covariances on F3variability,an analysis was performed using both acoustic and articulatory data to estimate F3variance as a function of articulatory variances.The relationship between transducer coordinates and F3during /r/can be written for each speaker as follows:(1)where the are constants,the are the transducer coordinates,is the number of transducer coordinates considered in the analysis,and is a residual term that accounts for the effects on F3due to all other sources,including articulators not included in the analysis,measurement errors,and nonlinearities in the relationship between F3and the transducer coordinates.The equation relating F3variance to articulatory variances at each point in time is then:.(2)To determine the effects of articulatory covariances on F3variability,we can compare the variance estimate of Equation 2to the following variance estimate that excludes the covariances between the analyzed transducer coordinates:.(3)If the F3variance estimate in the absence of articulatory covariances (Equation 3)is significantly larger than the variance estimate including the articulatory covariances (Equation 2),we conclude that the primary effect of the articulatory covariances is a reduction in the variance of F3.Strictly speaking,a comparison of the F3variance estimates in Equations 2and 3tells us only about the effects of the covariances of the linear component of each transducer’s relation to F3.However,the relationship between F3and transducer coordinates should be linear near a particular configuration of the vocal tract,since F3is presumably a continuous nonlinear function of the vocal tract area function,and such functions are locally linear.One would further expect that the relationship is still approximately linear for the relatively limited range of vocal tract configurations utilized by a particular subject for /r/.The linear approximations reported below captured approximately 80%of the variance when using only three pellet coordinates,providing support for the assertion that the primary effect of articulatory covariances on F3variance can be captured by considering only the linear component of each transducer’s relationship to F3.Furthermore,the sign (positive or negative)of an articulatory covariance’s contribution to F3variance depends only on the sign of the corresponding terms,and we are primarily interested in the sign of the combined effects of articulatory covariances on F3variance.The expected signs of the for tongue back height,tongue front horizontal position,and tongue front height can be deduced from acoustic theory considerations (Sections 2.3and 2.4).values were estimated for each subject using muliple linear regression on the acoustic and articulatory data.As discussed in Section 3.4,all 21estimated values (3values for each of 7 subjects) were of the sign expected from these acoustic theory considerations.F 3A 0A i c i i 1=N∑+=E +A i c i N E Var F 3()A i 2Var c i ()i ∑Var E ()2A i A j Cov c i c j ,()∑i j <∑2A i Cov c i E ,()i ∑+++=Var F 3()A i 2Var c i ()i ∑Var E ()2A i Cov c i E ,()i ∑++=A i A i A i A i3. Results3.1. Temporal progression of tongue shapesFigures1through7show sample lingual articulations used to produce/r/in thefive contexts by the seven subjects.For each context,two schematized tongue shapes and a palatal trace4are shown.The tongue shape schematics were formed by connecting the three tongue transducers with straight lines.The solid tongue shape corresponds to the point in time at which F3reached its minimum value.The tongue shape70ms prior to the F3minimum is indicated by dashed lines.The movement of the tongue can thus be roughly characterized as a transition from the dashed tongue shape to the solid tongue shape.This movement corresponds to the articulation toward the“acoustic center”of/r/;i.e.,the portion of the movement up to the point in time of the F3 minimum.Inspection of the lingual articulations for some subjects suggests that these subjects utilize different articulatory gestures,aimed at different vocal tract shapes,to produce/r/in different phonetic contexts.For example,the backward movement of the tongue,with a slight downward movement of the tongue blade, used by Subject1to produce the/r/in/wadrav/does not appear to be aimed at the same vocal tract shape for/r/as the upward movements of the tongue blade used by the same subject to produce/r/in the/warav/, /wabrav/,and/wavrav/contexts(Figure1).Similarly,the downward movement of the tongue blade used by Subject2to produce the/r/in/wadrav/does not appear to be aimed at the same vocal tract shape as the upward movements of the tongue blade used by the same subject to produce/r/in/warav/,/wabrav/,or /wavrav/(see Figure2).Additional examples of this phenomenon can be seen in Figures1-7.The possible relevance of these observations to theories of speech motor control will be addressed in the Discussion section.3.2. Tongue shapes at acoustic center of /r/Figure8shows tongue configurations at the F3minimum of/r/for each of the seven speakers.For each utterance,the three tongue transducer positions are connected by a straight line.The tongue configurations for all repetitions in all phonetic contexts are superimposed for each speaker.Thus,the fact that different numbers of utterances were analyzed for different subjects and contexts is reflected in this figure.As previously reported elsewhere(e.g.,Delattre and Freeman,1968;Hagiwara,1994,1995;Ong and Stone,1998;Westbury,Hashi,and Lindstrom,1995),a wide range of tongue shapes is seen both within and across subjects.Also of note is the fact that,although most subjects seem to use an approximate continuum of tongue shapes(e.g.,S2,S3,S6,and S7),others show a more bimodal distribution of tongue shapes(e.g.,S4,S5).Finally,the tongue shapes across subjects appear to form an approximate continuum between a bunched configuration(e.g.,S6)and a retroflexed configuration(e.g.,S4).A more detailed indication of the effects of the different phonetic contexts on the tongue shapes for/r/can be gained from Figure9,which shows the average tongue shapes used by each subject in each phonetic context,coded by phonetic context.Figures10through16show the corresponding average F3traces,starting from the point of the F3minimum for/r/and continuing for70ms,for each speaker coded by phonetic context.With the exception of the/wadrav/productions of Subject2,which had considerably higher values of F3than the other utterances for that subject,the subjects showed minimum F3values well below2000Hz in all contexts, as expected from earlier studies of /r/ production.Figure17shows the midsagittal palatal outline(thick solid line)and mean tongue shapes at the time of the F3minimum for/r/for each of the seven subjects.For each subject,mean configurations from two phonetic contexts(solid and dashed lines)are shown to illustrate the range of tongue shapes used by that subject.Tongue outlines were created by connecting the average positions of the three tongue transducers for a given utterance with a smooth curve to roughly approximate tongue shape5.A line was then extendeddownward from the tongue front transducer position,then forward to the lower incisor transducer position,to provide a rough estimate of the relative size of the front cavity across contexts 6.Also shown in the upper left corner of this figure are two superimposed,highly schematic vocal tract outlines that illustrate trading relations for maintaining a relatively stable F3.The effect on F3of the longer front cavity of the dashed outline,which can be roughly characterized as a retroflexed /r/,is counteracted by the effects of the longer and slightly narrower constriction of the solid outline,which can be roughly characterized as a bunched /r/.Similarly,the vocal tract outlines for all subjects indicate that shorter front cavity lengths are accompanied by a compensating increase in constriction length and/or decrease in the constriction area.Furthermore,the tongue shapes during /wagrav/(solid lines)are generally much closer in shape to tongue shapes for /g/than are the /r/shapes for /wabrav/or /warav/(dashed lines),suggesting that subjects utilize /r/configurations that are reached relatively easily in the current phonetic context.3.3. Articulatory trading relationsFor each subject,Pearson correlation coefficients corresponding to the predicted covariances described in Section 2.4were estimated across utterances at the point of F3minimum and are listed in Table 1.All subjects showed a significant positive correlation between tongue back height (TBY inTableFigures 1-3.Sample lingual articulations used by Subjects 1-3to produce /r/in the five phonetic contexts.For each context,two schematized tongues shapes and a palatal trace are shown.Each tongue shape schematic was formed by connecting the three tongue transducers with straight lines.The tongue shape at the F3minimum for /r/is drawn with solid lines.The tongue shape 70ms prior to the F3minimum is drawn with dashed lines.1)and tongue front horizontal position (TFX),indicative of a trading relation between constriction length and front cavity length.Six of seven subjects also showed a second strong trading relation:five subjects showed a trading relation between constriction length and constriction area as evidenced by a negative correlation between TBY and tongue front height (TFY),and one subject showed a trading relation between front cavity length and constriction area as evidenced by a positive correlation between TFX and TFY .One subject (Subject 7)showed only very weak correlations other than the strong trading relation between tongue back height and tongue front horizontal position.3.4. Analysis of acoustic and articulatory variabilitiesThe results in Section 3.3indicate that most subjects exhibited two of three hypothesized articulatory trading relationships that act to reduce acoustic variability.Furthermore,as described in Section 2.4,it is unlikely or impossible for a subject to utilize all three trading relations because they counteract one another.However,it is still possible that the significant correlations that violate the trading relations could effectively “override”the beneficial articulatory tradeoffs,potentially nullifying or even reversingtheFigures 4-6.Sample lingual articulations used by Subjects 4-6to produce /r/in the five phonetic contexts.For each context,two schematized tongues shapes and a palatal trace are shown.Each tongue shape schematic was formed by connecting the three tongue transducers with straight lines.The tongue shape at the F3minimum for /r/is drawn with solid lines.The tongue shape 70ms prior to the F3minimum is drawn with dashed lines.Figure 8.Tongue configurations at the F3minimum of /r/for each of the seven speakers.For each utterance,the threetongue transducer positions are connected by straight lines.The tongue configurations for all repetitions in all phoneticcontexts are superimposed for each speaker.Figure 7.Sample lingual articulations used by Subject 7to produce /r/in the five phonetic contexts.For each context,two schematized tongues shapes and a palatal trace are shown.Each tongue shape schematic was formed by connecting the three tongue transducers with straight lines.The tongue shape at the F3minimum for /r/is drawn with solid lines.The tongue shape 70ms prior to the F3minimum is drawn with dashed lines.effect of the utilized trading relations on acoustic variability.It is therefore necessary to estimate the net effect of all three articulatory covariances, as outlined in Section 2.5.F3variance estimates with and without covariance terms (Equations 2and 3,respectively)were calculated using the tongue back height,tongue front horizontal position,and tongue front height transducer coordinates.The corresponding F3standard deviations were then averaged across subjects.The values for each speaker were estimated using multiple linear regression across utterances and time bins and are provided in Table 2;the value of for a particular time bin was simply the residual of the regression in that time bin.R 2values for the F3fit (without the residual term)ranged from 0.75to 0.87for the different subjects,with an average R 2of 0.79.If covariances are high and the actual effect of an articulator’s position on F3is very low,the regression analysis can possibly result in estimates of transducer contributions that have the wrong sign,which could in turn cause some articulatory covariances to decrease estimated F3variability when in reality they increase or have no significant effect on F3variability.The fact that none of the transducer contribution estimates produced by the regression were of the opposite sign as expected from acoustic theory considerations and the MRI-based area function analysis indicates that this potential problem did not affect our results.F3standard deviation estimates with and without covariance terms are shown in Figure 18as a function of time starting at the F3minimum for /r/,averaged across subjects.(Standard deviations were plotted in place of variances to produce values whose units are Hz.)Also plotted is the standard deviation obtained from measured values of F3.When articulatory covariances are included,the F3standard deviation estimate is equal to the measured F3standard deviation;this is as expected because of the inclusion of the residual term in the variance estimate calculations.The solid line in the figure thus represents both the measured F3standard deviation and the estimated F3standard deviation including the covariance terms.When articulatory covariances are removed from the estimates,the estimated F3standard deviation increases substantially.The dashed line in Figure 18represents estimated F3standard deviation without covariances using the three tongue transducer coordinates.According to this estimate,then,F3standard deviation would be 105%higher at the acoustic center of /r/if the articulatory tradeoffs had not been present.Figure 9.Averaged tongue configurationsat the F3minimum of /r/for each of theseven speakers.The averaged positions ofthe three tongue transducer positions foreach of the five phonetic contexts areconnected by straight lines.A i E。

Particle Filtering Approaches for Multiple Acoustic Source Detection and2-D Direction of Arrival Estimation Using a Single Acoustic Vector Sensor Xionghu Zhong,Member,IEEE,and A.B.Premkumar,Senior Member,IEEEAbstract—This paper considers the problem of tracking mul-tiple acoustic sources using a single acoustic vector sensor(A VS). Firstly,a particlefiltering(PF)approach is developed to track the direction of arrivals offixed and known number of sources.Sec-ondly,a more realistic tracking scenario which assumes that the number of acoustic sources is unknown and time-varying is con-sidered.A randomfinite set(RFS)framework is employed to char-acterize the randomness of the state process,i.e.,the dynamics of source motion and the number of active sources,as well as the measurement process.As deriving a closed-form solution for the multi-source probability density is difficult,a particlefiltering ap-proach is employed to arrive at a computationally tractable ap-proximation of the RFS densities.The proposed RFS-PF algorithm is able to simultaneously detect and track multiple sources.Simu-lations under different tracking scenarios demonstrate the ability of the proposed approaches in tracking multiple acoustic sources. Index Terms—Acoustic vector sensor,detection and tracking,di-rection of arrival,particlefiltering,randomfinite set.I.I NTRODUCTIOND ETECTION,localization and tracking of2-D(azimuthand elevation)direction of arrivals(DOA)of multiple acoustic sources in a noisy environment are important topics in signal processing and have many applications such as room speech enhancement,underwater target surveillance,sonar and acoustic radar signal processing.The tasks are traditionally performed by using an array equipped with several pressure sensors together with estimation techniques developed based on the acoustic pressure measurements[1],[2].However,such techniques usually require either an array with large aperture or multiple hybrid arrays.In recent years,a new technology namely acoustic vector sensor(A VS)has been widely employed for acoustic source detection and localization,and different signal processing algorithms have been developed accordingly [3]–[25].Acoustic vector sensor employs a co-located sensor structure which consists of two or three orthogonally oriented velocity sensors and an optional pressure sensor[26],[27].It measuresManuscript received November17,2011;revised March21,2012;accepted May02,2012.Date of publication May17,2012;date of current version August 07,2012.The associate editor coordinating the review of this manuscript and approving it for publication was Prof.Joseph Tabrikian.The authors are with the School of Computer Engineering,College of Engineering,Nanyang Technological University,Singapore,639798(e-mail: xhzhong@.sg;asannamalai@.sg).Color versions of one or more of thefigures in this paper are available online at .Digital Object Identifier10.1109/TSP.2012.2199987acoustic pressure as well as particle velocity at sensor posi-tion.Given an A VS with three velocity components located at the origin of the three-dimensional(-,-and-coordinates) space,the sensor manifold has the form(1) where thefirst component represents the output of pressure sensor,and the rest three components are the velocity response along three directions respectively.The anglesand are the azimuth and the elevation tively.The structure suggests that A VS has following advantages over traditional pressure sensors.1)It produces both the azimuth and elevation information andenables2-D DOA estimation with a single vector sensor.2)Its elevation ranges between and allows elevationangle estimation3)The manifold is independent of the source’s frequency,which makes A VS suitable for wideband source signal or scenarios where the source’s signal frequency is unknowna priori.Due to a number of advantages mentioned above,both the the-oretical aspects and the applications of A VS have been widely studied in the last decade[3]–[25].A VS is used for infrasonic measuring in the ocean environment in[26].In[28],it has been theoretically proved that a single A VS is able to uniquely iden-tify up to two arbitrary distributed acoustic sources.A VS wasfirst introduced in signal processing and acoustic source localization problems in[3].An intensity based algo-rithm that uses both the pressure and particle velocity vector, and a velocity covariance based algorithm that uses only the particle velocity vector are fully presented in[5].A maximum likelihood based DOA estimation algorithm is developed in [28].The conventional beamforming(Bartlett beamforming) and Capon beamforming for2-D DOA estimation using acoustic vector sensors are investigated in[9].It shows that both the azimuth and elevation can be unambiguously estimated by using an A VS array.Further,the subspace based approaches such as MUSIC[12],[17]and ESPRIT[7],[10],[12],[15]have been used for A VS localization problem.The problem of2-D DOA estimation using a single A VS is particularly addressed and investigated in[14].More practically,A VS localization in impulsive noise environments and shallow ocean environments are investigated by employing fractional lower order statistics [29]and subspace intersection method[24],respectively.The1053-587X/$31.00©2012IEEEapplication of A VS in the room reverberant environment is studied in[30].The authors in[31]employ a towed A VS to track angles and frequencies of sperm whales.The existing2-D DOA estimation schemes assume that the source is static and extensively rely on localization approaches. Further,for DOA estimation of multiple sources,the number of sources is usually assumed to be known andfixed.These assumptions are often violated in real applications since the sources(e.g.,submarines in underwater or speakers in the room environment)are in fact dynamic,and the number of sources may be unknown and time-varying.Although the narrowband detection of acoustic source using A VS is addressed in[21],it cannot identify the number of sources and its use is limited in the narrowband scenario.For dynamic source,it is desired to model the source motion as well as the A VS measurements,and develop a multi-source tracking approach to detect the number of sources and track the DOA of each source simultaneously.To the best of authors’knowledge,no such a method has yet been derived for multiple A VS DOA estimation problem.In recent past,particlefiltering(PF)[32],[33]has been found to be effective in coping with nonlinear and non-Gaussian system models and has been widely employed for target tracking problems.It employs a number of particles to repre-sent the probability density function(PDF)of the unknown state vector,and evaluate the importance weights of these parti-cles according to the source dynamic model and the likelihood. Subsequently,the particles are duplicated/discarded according to the high/low importance weights,and the resampled particles are able to represent the posterior PDF of the state.For more details of the PF and its application to the tracking problem, the reader is referred to two books[34],[35].PF has been em-ployed for array signal based multiple target tracking in[36]. Also,it has been successfully used for underwater acoustic source and geoacoustic tracking problems[37],[38],and room acoustic source tracking problem[39],[40].Using A VS and such a PF scheme to track a single acoustic source has been recently studied in[41]–[43].In this paper,a PF is developed to track the2-D DOAs of multiple acoustic sources using an A VS.Firstly,the tracking problem in which the number of sources is assumed to be known andfixed at all time steps is considered.A constant velocity(CV)model[44]is used to model the source dynamics. The covariance matrices of source signal and the measurement noise process are unknown in practice.These parameters are regarded as nuisance parameters and estimated by using a maximum likelihood estimator.The likelihood of particles is consequently concentrated likelihood and formulated based on the measurement sequence and the estimated covariance matrices.Due to a sample-based representation of the posterior PDF of the state vector,PF is able to cope with the nonlinear measurement model and well suited for DOA estimation.It is observed that the mainlobe of the likelihood function is spread under low signal-to-noise ratio(SNR)environments.Therefore, the likelihood function is further exponentially weighted to generate a sharper peak and to emphasize the particles sampled at high likelihood area.A Rao–Blackwellization step is used to marginalize out the velocity component of the state and thus reduce the dimension of the PF.The key advantage of the proposed PF tracking algorithm is that it incorporates both the temporal and spatial information,and hence it is able to estimate the DOA accurately and efficiently even though the source is dynamic in a low SNR environment.Secondly,we consider a more challenging problem where both the source motion dynamics and the number of sources are assumed to be unknown and time-varying.The unknown parameters of interest are thus the number of sources as well as the corresponding2-D DOAs.Also we consider a more practical sensor model in which the measurements can either be regular signals emitted by sources or be strange signals due to transient interferences.The former is modeled by A VS signal model and the later is modeled by using an empty set.Both the source dy-namic model and the sensor measurement model are thus with a random geometry and all the randomness can be encapsulated in a randomfinite set(RFS)framework.Generally,RFS frame-work neglects the intrinsic data association between sources and measurements,and has been found promising for multi-object tracking problem[45]–[49].In the state space,each element of a RFS is a random vector which can be employed to describe the source motion dynamics,and the cardinality is a random variable that can be used to model the time-varying number of sources.Similar structure can also be constructed for the col-lected measurements.Subsequently,a PF implementation for the RFS state tracking is also developed to obtain a computa-tionally tractable approximation of the RFS probability densi-ties.For rigorous mathematical description of RFS framework and its application in multi-object tracking problem,the reader is referred to[45]–[49].Particularly,RFS is employed for room acoustic source detection and tracking in[47].The core contribution of this work is that full probabilistic model based approaches have been derived for A VS based multiple acoustic source tracking pared to the existing RFS approaches[46],[47],the main contributions are double fold:Rao-Blackwellization step is employed to marginalize out the source velocity and both regular and irreg-ular signals are modeled.Particularly,the RFS-PF algorithm developed here is able to simultaneously detect and track multiple acoustic sources based on the received A VS signals. The rest of this paper is organized as follows.In Section II,the A VS signal model and particlefiltering method are introduced. Section III presents the tracking algorithm developed for known andfixed number of sources.The enhanced likelihood model and the Rao-Blackwellization step are also formulated. Section IV presents the RFS-PF tracking algorithm developed for unknown and time-varying number of acoustic sources.Per-formance metric and discussions regarding real application of the proposed approaches are presented in Section V.Simulated experiments are organized in Section VI.Finally,conclusions are drawn and future directions of this work are discussed in Section VII.II.P ROBLEM F ORMULATIONThis section provides a brief review on DOA estimation based on A VS acoustic signal.The signal model for an A VS is introducedfirst.A.AVS Measurement ModelThe goal of this paper is to develop an approach to detect and track dynamic acoustic sources simultaneously.The number of sources as well as the position of each source are thus assumedZHONG AND PREMKUMAR:PF APPROACHES FOR MULTIPLE ACOUSTIC SOURCE DETECTION AND2-D DOA ESTIMATION USING A SINGLE A VS4721to be time-varying.Wefirstly formulate the A VS signal model for multiple dynamic sources.Assume that there are simultaneously active acoustic source signals arriving at an A VS at discrete time.The source signals can be written in a collection given as(2)where is a wide-band signal,i.e.,. It has an independent and identically distributed(i.i.d.)random amplitude and random phase.The phase is assumed to be distributed over.Further assume that the th source signal is emitted at a2-D direction given by(3)with and denoting the azimuth and the elevation anglesAcoustic vector sensor measures the acoustic pressure as well as three component particle velocities.Let be the unit direc-tion vector pointing from the origin toward the source position, and factorized by a constant term,given as(4) where and represent the ambient density and the propa-gation speed of the acoustic wave in the medium respectively. Using a phasor representation,the received signal model for an A VS located at can be written as[5](5) where and represent the corre-sponding pressure and velocity noise terms separately.isthe time delay of the th wave between the sensor and the origin of the coordinate system,i.e.,.For an acoustic source that moves relatively the DOA can be assumed to be stable if a small number of snapshots are processed at each time step.Assume that snapshots are taken into account at time step,the number of sources is thus and the snapshots of the source signal can be written as(6) where.The noise and received data matrices can be expressed as(7)(8) where.Accordingly,is used to express the DOA.Equation(5)can thus be written as(9) where(10)and(11) is the steering vector.The received signal includes both the az-imuth and elevation information,and can be used for2-D DOA estimation.The measurement equation is the A VS data model(9).As-sume that1)the noise terms in(9)are independent identically distributed(i.i.d.),zero-mean complex circular Gaussian pro-cesses and are independent from different channels and2)the source signal and the noise are independent.The PDF of the measurements can be written as(12)where represents a multivariate complex Gaussian distribution with mean and covariance matrix.The source signal process and noise process are characterized by their co-variance matrices given by(13)(14) where is an th order identity matrix,and and are the noise variances for the pressure and velocity components re-spectively.The corresponding covariance matrix is given as(15)We are now faced a2-D DOA estimation problem with un-known nuisance parameters,and.B.Source Motion ModelDOA estimation based on the localization approaches such as beamforming and subspace methods only use the spatial in-formation from the current measurements.Since the DOAs be-tween adjacent time steps are highly correlated,it is desired to model the source motion trajectories and estimate the source DOA by incorporating the temporal information(implied in the source dynamic model).In this section,the CV is introduced to model the source motion.Assume that the sources move with a velocity(in rad/s), for.The source state can be constructed by cascading the DOA and the motion velocity,i.e.,.The CV model[44]is employed here to model the source dynamics and is given as(16)where the coefficient matrix and are defined,respectively, by(17) where represents the time period in seconds between the previous and current time step,and denotes the Kronecker product,and is a zero-mean real Gaussian process(i.e.,4722IEEE TRANSACTIONS ON SIGNAL PROCESSING,VOL.60,NO.9,SEPTEMBER2012)with)used to model the turbulence on the source velocity.represents a diag-onal matrix with main diagonal entry and0elsewhere.For the source states,we have following assumptions:•each active source follows the CV motion model described in(16);•the source motions are independent of each other;The polar system based CV model(16)has been widely em-ployed for DOA tracking problems in[42],[43],and[50]. C.Sequential Monte Carlo EstimationLet denote all measurements ob-tained until time step,and be the collection of states.The task is to estimate the posterior recursively.The solution based on Bayesiantowards to this problem can be given as follows:•Predict:(18)•Update:(19) In this recursion,is the posterior distribution estimated at the last time step,and is the prior distribution for the current time step.The Bayesian recursion states that given both the posterior distribution of the state esti-mated at the previous time step and system models,the cur-rent probability distribution of the state can be obtained recur-sively.Although Kalmanfilter can be used to solve the Bayesian recursion in(18)and(19),its use is limited in the case of linear and Gaussian system models.However,the PF that provides an excellent solution to the nonlinear problem is employed in the work[32].The core idea of PF is that it uses a set of particles and importance weights of these particles to approximate the posterior distribution.Assuming that particles are used to ap-proximate the above Bayesian recursion,the PDFis represented by.The whole procedure of PF processing can be following.At time step, the particles are sampled according to an importance function, given by(20) The importance weights of the particles are then evaluated by(21) Usually,the optimal importance function,i.e.,is able to provide minimum estimation variance.However,this importance function cannot be obtained in a straightforward manner.One alternative is to employ a prior importance func-tion.Given the state particles,for at pre-vious time step,the are sampled at the current time step according to the source dynamic model(16),given by(22)The particles are thus weighted according to,where is the nor-malized weight.After the resampling scheme,the posterior distribution of the state is thus approximated by(23) where is a Dirac-delta function.For slow DOA motion and simple trajectories,the CV model is able to model the source motion accurately and the particles can be drawn from the prior importance function effectively.The remaining task is then con-struct appropriate likelihood function to evaluate the importance of these particles.III.T RACKING A F IXED AND K NOWN N UMBER OFA COUSTIC S OURCESTracking a known andfixed number of multiple acoustic sources using an A VS is considered in this section.This work can be regarded as an extension of our previous investigation of tracking a single acoustic source in[43].The main difference comes from the derivation of the likelihood and formulation of the importance function.In addition,a Rao–Blackwellization step is employed here to marginalize out the velocity compo-nent of the state.The general idea of2-D DOA tracking using PF will form the basis of our solution to the more compli-cated problem in the next section in which an unknown and time-varying number of sources is considered.A.Concentrated Likelihood ModelSince the measurement noise process is assumed to be Gaussian,the likelihood function can be written as(24)where denotes the determinant,and represents the trace operation.is an estimate of the covariance matrix of the A VS measurements given by(25)where superscript represents the Hermitian transpose.The statistics of source signal and noise process are unknown in practice.Taking all these parameters into account will result in a high-dimensional problem.Here,we use a concentrated like-lihood function which estimates the nuisance parameters based on a maximum likelihood estimator.According to[5],the con-centrated likelihood function can be written as(26)ZHONG AND PREMKUMAR:PF APPROACHES FOR MULTIPLE ACOUSTIC SOURCE DETECTION AND2-D DOA ESTIMATION USING A SINGLE A VS4723where(27)(28) The likelihood is then concentrated on the parameters of in-terest,the2-D DOA.The DOA estimates can be obtained by implementing a2-D search over the possible DOA range which maximizes(26).However,such a method is computation-ally expensive since a2-D search is required.In this work,we will introduce a particlefiltering approach to estimate the2-D DOA,by which the2-D search can be avoided.We draw state samples randomly over the2-D DOA space.The likelihood for particles can thus be obtained by substituting the particle state into the likelihood function(26).Generally,when the particles are closer to the ground truth state,a larger likelihood will be produced.Consequently these particles are weighted more sig-nificantly and are more likely to be selected for state estimation. An alternative method to formulate the likelihood is pre-sented[33],where uninformative prior density for the nuisance parameters are specifiedfirst,and these parameters are inte-grated out from the problem.Another advantage of using PF tracking approach to estimate the2-D DOA is that it models the source dynamics and employs both temporal information(from the source dynamic model)and the spatial information(from the measurements)to track the DOAs,while the localization approaches only uses the spatial information.It can be observed in Section II-C that the particles are in fact weighted by their likelihood when the prior importance func-tion is employed.It is desired that the particles around ground truth will present a large likelihood and weighted significantly larger than those far away from the ground truth.Hence,these particles which are more potential to the state estimation can be replicated.However,it is well known that the mainlobe of concentrated likelihood function(26)is usually spread andflat due to the low SNR environment.The particles sampled close to the ground truth cannot be significantly weighted.Another drawback of likelihood function(26)is that it has an exponen-tial factor.When the number of snapshots is very large (e.g.,),the likelihood value becomes extremely small and may be truncated to zero in computer implementation.It is thus necessary to reshape the likelihood function and make it more amenable to our problem.To eliminate the effect due to large,the likelihood is ex-ponentially weighted by.Hence the effect due to the number of snapshots is canceled.On the other hand,the likelihood function becomesflat and the particles cannot be weighted ef-ficiently in the low SNR scenario.We further exponentially weight the likelihood by a constant value.Hence,the like-lihood function will be more peaky and the weight of particles which are located at high likelihood area can be enhanced.The likelihood function(26)can now be written as(29)where.After this normalization and weighting,the like-lihood function is reshaped and the weight of particles which are sampled at the high likelihood area can be enhanced.This step is important since it is able to help the subsequent resampling algorithm to select and replicate the particles more efficiently.B.Rao-Blackwellization StepGiven the transition and likelihood models derived above, formulating the PF algorithm for A VS source tracking is straightforward.It can be observed from the CV model that the state is constructed by the position component and velocity component,and the source position holds a linear relationship with the velocity.The position state can be regarded as a measurement of the velocity component.The CV model(16) can be decomposed as an auxiliary state space model,given as(30)(31) As previously defined,the noise variance of velocity state process is,and the noise variance of auxiliary mea-surement process(position state process)is.Thus the velocity component of the state can be marginalized out by using a Kalmanfilter(KF),and only the position part needs to be handled by using the PF.Such a technique is also referred to as Rao-Blackwellization[34]and widely used for the state estimation where part of state space equations are linear and Gaussian[34],[35].Using Bayesian theorem,the posterior distribution of the whole state can be written as(32) in which is analytically tractable and is estimated by PF approximation.Since part ofcan be estimated optimally(by using a KF),the dimension of the state to be processed by PF can be reduced. Consequently,the Rao-Blackwellization based PF is able to provide better estimates than the standard PF when the same number of particles are used[34].The KF marginalization can be summarized as follows:(33)(34)(35)(36)(37)(38) For KF implementation,the velocity state and its variances are initialized as and,respectively.The complete tracking steps are summarized in Algorithm1. Thefiltering algorithm is quite general and can also be used for multiple target tracking based on other sensor models,i.e.,tra-ditional acoustic pressure sensors.Since the DOA states in the4724IEEE TRANSACTIONS ON SIGNAL PROCESSING,VOL.60,NO.9,SEPTEMBER2012particles are with an arbitrary order,extracting thefinal state es-timates by taking the expectation of the particles will not make any sense.In this paper,a K-means algorithm is employed to cluster the particles,and thefinal estimation is obtained from the centroids of these clusters.It is observed that using one step K-means implementation is able to provide accurate estimates. It is worth mentioning that due to the advantage of A VS steering vector,the DOA tracking algorithm does not require the fre-quency information of each individual source,and is appropriate for both the narrow-band and wideband acoustic source tracking problem.Algorithm1:RB-PF for A VS2-D DOA tracking. Initialization:for,draw particles,where is obtained from MUSIC method;set the initial weight;for to do1)calculate the covariance matrix according to(25);for to do2)compute the likelihood from(26);3)compute the importance weight:end4)normalize the weight;5)resample the particles according to the weights;6)Kalmanfiltering according to(33)to(38);7)draw particles according to(31);8)output the estimates by using one step K-meansmethod.endIV.T RACKING AN U NKNOWN AND T IME-V ARYINGN UMBER OF S OURCESThe previous section illustrated the PF algorithm for known andfixed number of acoustic sources tracking.In practice,the number of sources is actually unknown and time-varying.It is thus necessary to consider detection and tracking of mul-tiple acoustic source jointly using an A VS.This section presents our solution towards to tracking an unknown and time-varying number of sources.Essentially,an RFS framework is formu-lated to characterize the randomness of source dynamics as well as measurement uncertainties.The RFS state process is intro-ducedfirst.It is worth mentioning that the RFS state model for-mulated here is similar to that in[47].A.RFS State Model FormulationFor simultaneously detecting and tracking of unknown number of multiple acoustic sources,the parameters of interest will be the number of sources as well as the2-D DOA of each source.The state of a single source at current time step is stated as,for.All the parameters of interest can be characterized by using a singlefinite set,given as(39)where is the number of sources,with representing the cardinality.Given a realization of the RFS state at previous time step,the source state at current step is modeled by(40)where is the state vector of sources born at time step ,1and denotes the RFS of states that have survived at time step.is the initial state vector under the birth hy-pothesis.The DOA part of all new born states is assumed to be uniformly distributed over the possible DOA range,and the velocity part is assumed to be a Gaussian distribution around a certain velocity.is thus given as(41)For the birth process,we assume the following:•at most one source is born at a time step;•where is the maximum number of sources at each time step.Thefirst assumption is employed to simplify the problem.Also it is plausible to make such an assumption since the number of sources we considered here is relatively small.In practice,it is possible that multiple sources turn up simultaneously.Fur-ther,the maximum number of sources in the surveillance area is bounded at,i.e.,.This means that when,the new born state vector is an empty set,i.e., .It is observed in[28]that for a single A VS,up to two sources can be uniquely identified.Hence,is chosen in this work.2The source birth process can thus be formulated as(42) where and are the hypotheses for birth process and non-birth processes,respectively.The surviving state set can be formulated by considering a death process. Assume that and are the hypotheses for death process and non-death processes,respectively.When a death process happens,the corresponding state will be set as empty, and the remaining states will evolve following the motion dy-namic(16).can thus be given asforth source;.(43) 1Since the time-varying number of sources is considered,the source dynamics is not only the source motion itself,but also source birth and death process.In this paper,we use birth and death processes to describe the source appearance and disappearance in the tracking scene,and accordingly,the terminology‘born’is employed to represent that new source appears in the surveillance area,and ‘die’refers to existing source which disappears from the surveillance area.2Note that when the number of sources is larger than two,an A VS array could always be employed.。

CHALLENGEResidents living in Welzow near the mining bridge were complaining about environmental noise. In order to reduce noise pollution, the acoustic sources of the bucket-wheel excavator needed to be localized. SOLUTIONThe Acoustic Camera as a mobile system allows high flexibility for outdoor measurements. Fast measurement and quick analysis enables users to easily identify sources as well as additional measurement positions of interest. With complete measurement set-up and postprocessing of the data, it takes only a few hours to completely identify the loudest sources on large machinery. The sound sources on the excavator can be precisely identified without stopping its operation. Once these sound sources are localized, they can be eliminated to reduce the effects of noise pollution.gfai tech GmbH Volmerstraße 3 12489 Berlin | Germany Ph.: +49 30 814563-750Fax: +49 30 814563-755E-Mail:****************www.gfaitech.de2D Outdoor MeasurementTHE ACOUSTIC CAMERA FOR ENVIRONMENTAL NOISE ANALYSIS AND HEAVY EQUIPMENTBENEFITS• Fast and easy set-up• No expensive machine downtime• Long distance measurement capability• Mobile system for flexible measurement locations• Advanced algorithms for precise localizationMEASUREMENT Measurement Object Microphone Array SoftwareData Acquisition Strip mining excavator Star48 AC Pro NoiseImage 4 Acoustic Photo 2D Recorder Spectral Photo Advanced Algorithms Data Recorder mcdRecThe Acoustic Camera was set up as a mobile system for full flexibility using a Star Array with 48 microphone channels. After an overview measurement from 150 meters away, the acoustic hot spots were localized. After the quick overview analysis, additional measurements were conducted closer to the sound sources for a more detailed analysis.www.gfaitech.de Page 2/2RESULTFor a reliable sound analysis, background noise was minimized by applying A-weighting to all data. In the first measurement from 150 meters distance, the main sources could be easily identified. In Fig. 1, the powerhouse and the derrick jib clearly stand out as the loudest areas.The second measurement was conducted closer to the derrick jib. As result of this measurement, the redirection point of the jib was identified as one of the loudest sources. A third measurement was made from a position on the bank with direct view to the jib. Several additional measurements were conducted from that position. A detailed analysis in the frequency domain was conducted using advanced algorithms in NoiseImage.The analysis using the HDR algorithm (High Dynamic Range) shows different sources and reflections on the ground within a dynamic of 35 dB(A). In the spectrogram (Fig. 3), the “banging” sounds are clearly visible. In order to find their location, these areas are simply marked as basis for the calculation region of the acoustic photo. The sound sources can be precisely identifiedas showninFig. 4. The broadband rattle sounds were produced by theshovel guidesimpacting the guide blockjust below the point of redirection.Fig. 1, left: powerhouse and derrick jib,right: derrick jibFig. 2direct view of the derrick jibFig. 3 Acoustic photo and spectrogram with a marked frequency range of 700 Hz - 1,1kHzFig. 4Acoustic photo and spectrogram withE-Mail:****************。

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握手hardware description language（HDL）硬件描述语言hatch孵化，舱口headend数据转发器headway进展，前进heliograph 日光仪helium氦气herein在此，如此heritage世袭财产，遗产heuristic启发的，启发程序hexadecimal 16 进制的hexagon六边形hifi （high fidelity）高保真（音乐）highlight突出，突显，强调hindsight事后聪明histogram直方图holding circuit 保持电路homodyne零差式的host主机hub中心，网络集线器Hubble telescope哈勃望远镜hue色调Huffman encoding Huffman 编码hull外壳，船身hunch预感，直觉的想法hybrid混合，混合物hydrologic 水文的hydrology水文学hydrophone 水听器hype广告，人为刺激hypothesis 假设Iignition燃烧，点火IIR （infinite impulse responsefilter）无限冲击响应滤波器image registration 图像配准imagery像，图像imagingradiometer 辐射成像仪imitator仿冒者immune免疫的，不受影响的immutable不可变更的impartial公正的，不偏不倚的impedance 阻抗impede妨碍，阻止imperative势在必行的impinge撞击，射到impose施加impress印，铭刻，加载in absentia 缺席的In agreement with …与--- 一致/不冲突In nature性质上in series 串接inadequacy不够，不足inadequate 不够的inadvertently漫不经心地in-building建筑物内的incident入射的incompetence 无能increment 增量incur招致，蒙受，引起index of refraction 折射率indexing mechanism 索弓|机制indistinguishable 难以分辨的induce感应，遭致inductance 电感infection 传染inference 推论inferior差的，处于劣势的infinity无穷大inflation 通货膨胀informatics信息科学information hiding 信息隐藏informative提供信息的informed 有知识的，有见闻的infrared红外线，红外的infra-red红外线的，红外线infrastructure 基础设施ingredient成分，因素inherently内在地，本质上inheritance遗产，遗传inhibition 禁止，压制inhomogeneity 不均匀性initiative主动的行动insane 有精神病的，愚蠢的instantaneously 瞬时地instantaneous 瞬时的insulate 绝缘insulate绝缘，隔离intact完好的，完整的integer 整数integral 积分integrate求积分integrated circuits 集成电路integrator 积分机integrity完整性intelligence 智能，情报intelligent 智能的Intensity 强度interact交互作用interactivity 交互interactivity 交互性interchangeably可互换地，不区分地interconnected 互联的interdisciplinary 跨学科的interface 接口interlace相间，隔行扫描interleave 交织interleaving 交叉，交织interleaving 交织，交错intermediary中间的，媒介的interminable无限的，冗长的intermittently 间歇地internal medicine 内科学interoperability 互操作性interpolate 内插interrogator询问者，质询者interrupt 中断intersection 交叉点intertwining 缠绕在一起interval 间隔intervene插入，干预intervening 期间的intrigue引起兴趣，吸引introductory介绍性的，引导性的intrusion 入侵intuitive直觉的inundation洪水，大水invasive入侵的，侵略性的inverse反转的，逆irrefutable不能反驳的irregular不规则的,无规律的irrevocable不可变更的isotope同位素ISP互联网业务供应商Jjaggedness起伏不平，不规则jamming 干扰jitter抖动，颤抖Julius Caesar朱利叶斯•恺撒junk垃圾justify证明是必要的Kkeep pace with…与…保持一致步伐kernel核，核心keying键控（法） kink扭结，绞缠klystron速调管Llaptop computer膝上电脑/笔记本电脑laser激光latch锁存（器）latency等待时间，时间延迟latency延迟，潜伏期law suit司法诉讼lax宽松的，不严格的layout布局，布线leading edge （脉冲的）前沿legacy祖先遗留之物legible可识别的，清楚的legion军团，众多的人lend itself to…有助于，适合于lend oneself to有助于，适宜于levee大堤lidar激光雷达likelihood可能性，似然性limelight众人注目的中心linearity 线性line-of-sight 视线linkage联合，结合lithographic平板印刷的litigious好诉讼的，好争论的live concert实况音乐会live multimedia实时多媒体load leveling负载平衡logarithm 对数logarithmic 对数的login登录lookup table 查找表lossless无损的lossy有损耗的loudspeaker 扬声器lump块，使…成块lumpedelement 集总元件lumped system集总系统Mmachine vision 机器视觉magneticresonance 磁共振magneticresonanceimaging （MRI）磁共振成像magnetron磁电管，磁控管magnitude大小，数量maiden name婚前的姓/娘家的姓mainframe大型计算机mainstream 主流maintainability可维护性Malicious恶意的malignant恶性的malware恶意软件mandatory命令的，必须的mangrove 红树manifestation 显示，证明manipulate处理，操作manipulation 操作，处理mantissa 尾数map映射marginally有限度地Marital婚姻的maritime航海的market share市场份额Mars火星marsh沼泽，湿地marvel奇异之事maser迈泽massive巨大的matrix矩阵mature成熟mean均值measure测度，度量mechanism 机制median filter中值滤波mediocre不好不坏的，通常medium access control （MAC）媒体访问控制megabyte兆字节megaphone扩音器melt熔化mental精神的，智力的merge合并metabolism新陈代谢metallic金属的metallization 金属化metamorphose使变形，变态meteorological 气象的methodical有方法的，有系统的metropolitan 都市的micrometer 微米（10 6 m）micron微米microstrip antenna 微带天线middleware 中间件mill作坊，工厂millennium 千年mimic模仿mimic模仿miniature小型的miniaturization 小型化minority 少数minutia 细节（minutiae）misfiring误触发mismatch失配，不匹配mitigate 使缓和，减轻mixer混频器mobility移动性modality形态，式样modem调制解调器modular-2 模2 的module模块modulo模，取模的moisture湿气，水份moment 矩mono单一，单声道monochromatic 单色的monochrome 单色的monotypic 单型的moral道德，寓意morbidity发病率Morse code莫尔斯电码mortal人的，不免一死的mosaic马赛克，拼图motherboard 母板motion blur运动模糊motivation动机，推动力MRI磁共振成像multi-carrier 多载波multicast组播，多播multimedia authoring 多媒体制作multimode fibers 多模光纤multipath fading 多径衰落multipath 多径multiplex多样的，多路复用multiplex 复用multiplication 乘法multiply 相乘multiprocessor 多处理器multi-spectral 多光谱的multitude多数，大众mutual information 互信息Nnand与非nanometer 纳米（10 9 m）narration叙述，解说navigate 航行negligence疏忽，玩忽行为negligible可忽略的netlist电子设计中的联接性network traffic网络数据流neurobiology神经生物学neurology神经病学neuron神经元，神经细胞niche有利可图的专门市场non-field programmable非现场可编程的nonlinearity 非线性normal垂直的，法线的normalize归一化，标准化normative规范的，标准的nor或非notion概念novelty新奇，新鲜事物number base 数制numerical数值的nutrient 营养Oobjective 目的object-oriented面向对象的oblique倾斜的obsolete过时的，陈旧的obstetrics 产科obviate避免，使成为不必要oceanographer 海洋学家offline离线的，非实时的offset voltage drift补偿电压的漂移offset偏移量olfactory嗅觉的，嗅觉器官onboard logic （电路）板上逻辑ongoing进行中的Ongoing正在进行的op amp运放的简写opaque不透明的operationalamplifier 运算放大器operator算子，算符optical fiber 光纤orientation 方向originate 发源originate来源于orthogonal 正交的orthogonality 正交性orthomode transducer 直接式收发转换器oscillate 振荡oscillator 振荡器otology耳科学out of focus未聚焦，聚焦不良的outbound向外的outdated过时的outpace赶过，超越output swing输出电压变化范围outset开头，最初outward 向外overconfidence 过分自信overhead 开销overlap 重叠overlook忽视，俯视ozone臭氧Ppacket （数据）包pager寻呼机paging寻呼pan-tilt-zoom平摇、俯仰、变焦parabolic抛物线的paradigm范例，样式parallel logic circuitry 并行逻辑电路parallel 并行parallel并行，平行parameter 参数parameters 参数parasitic寄生的parity奇偶性partition分割，分区passive被动的，无源的patch 片pathology病理学pattern 模式payroll工资单，员工清单pediatrics 小儿科penetrate穿透，渗透Penetration穿透，入侵perception感觉，感知，领悟perceptual 感官的peripheral外围的，外围设备perpendicular 垂直的perspective透视图，透视的pertinent相关的，切题的perusal精读，细读pervade弥漫于，流行于phase相位，相角Phenomenal显著的，异常的phosphorous 磷的photoelectric effect 光电效应photomask光掩模photometrically在摄影光度方面photon光子physician内科医生physiology 生理学pico-cell微微蜂窝pilot signal导频信号pilot引导，试用pinpoint准确地定位pitch音调，程度pixel像素placement 放置plasma等离子体platform 平台platitude陈词滥调，老生常谈plausible貌似合理的plea请求，恳求plug插入polar极坐标的polarization 极化，偏振polarization 偏振，极化polymorphism 多形态polysilicon 多层硅pool把…集中使用popularization大众化，流行portability 便携性portrayal描绘，肖像pose摆放，提出，陈述potential 潜力power of two 2的幂power 幂precision精度，精确的predominant占主导地位的prefix 前缀preform预制品prelude 序言premature未成熟的premise 前提premises （经营）场地premise 前提presampling 预采样prescribed 预定的presentation layer 表示层preset预置presetable可预置的prevalent流行的prior to…在•…之前priority queueing按优先级的排序prism 棱镜privilege 特权procure获得，取得product 乘积productivity生产力，工作效率Profession 职业professional field 专业领域Professional专业人员professionally 专业地profile轮廓，姿态programmable controller （PC）可编程控制器programmable可编程的projection 投影proliferate 激增proliferation 激增promote推销，促进prompt提示，激励propagation delay 传播延迟propagation 传播proportion 比例protocol协议，规约prototype原型，样机protrude 突出provably可证明地proximity接近，亲近proxy server代理服务器pseudo random noise 伪随机噪声psychiatry精神病学psycho-acoustic心理声学的PTZcameraPTZ 摄像机punch card穿孔卡片purchase 购买purpose-designed针对目的设计的pursue追求，从事Qquadrangle 四边形quadrature正交，90 相位差quantify量度，表示数量quantitatively 定量地quantization量化quantum量子，量化quest追求，探索queue排队，队列Rradiant辐射的radio astronomy 射电天文学radiograph 射线图radiographic射线图像radioisotope放射性同位素radiology放射学radiometer 辐射计rain fade降雨衰减raster光栅rationality合理性，理性reactive ion etching反应离子刻蚀reactive反应的，反动的real number 实数reasoning 推理reassessment重新评估recipient接收者reconfigurable可重新设置的reconnaissance 侦察reconstruction 重建rectangular 矩形的recur复发，再发生recurrence 重复recurring循环的redundancy 冗余，多余redundant冗余的，多余的reflected反射的reflection 反射reflective 反射的reflex反射，映像refractive index 折射率refractive 折射的regime政权，体制，情态regions-of-interest 感兴趣区register寄存器registration 对准regulations规则，条例regulatory调整的，控制的rehabilitation 康复reinforcement 力口强relaxation松弛，弛豫relay中继，接力release发布，版本relevance有关，适当relief texture凹凸的纹理rematrix重新进行矩阵变换render表示，表现，再现render表现，渲染rendition表现，渲染repeater中继器，转发器replica复制品replication 复制Requisite必需品，必要条件researchinstallation 研究机构reside驻留resistance 电阻resolution 分辨率resonance谐振，共振resonant谐振的resonator谐振器responsive应答的，回答的retrospective 回顾的reveal披露，显示revenue收入，税收revision 修正ridge 脊rigid坚硬的，刚性的rigorous严格的rip撕，拉，劈ripple carry adder纹波进位加法器ripple波纹，波动，飘动rival对手RMS (root mean square)均方根RMS: Royal Mail Ship 皇家邮轮roam漫游robot机器人robotic surgery机器人外科robust牢固，稳健robust稳健的，鲁棒的robustness稳健性，鲁棒性rock-solid磐石般坚固的roll out 展开round robin循环(复用)round四舍五入router路由器routing路由，联线royalty版税，庄严，王权rubric题目，标题Ssalinity 盐度sampler 样品sampling 采样sanitize消毒，使无害saturate 饱和saturation 饱和度scapegoat替罪羊scatter 散射scatterometer 散射计scenario情节，方案scenario情节，剧本，方案scenario情节，方案scenery风景，景物scope范围score得分scramble打乱，使混杂screening筛选，普查sediment沉淀物，沉积seismic地震的seismology 地震学semaphore 旗语seminal开创性的sensitivity敏感性，灵敏度sensor array传感器阵列sensor 传感器，感光器sensory感觉的，传递感觉的serial串行serial-in parallel-out 串进并出serial-in serial-out 串进串出Server服务器shading阴影，明暗shed放射，摆脱shift register移位寄存器shim填片shop floor车间现场shutter 快门signature签字，标识signify表示，象征signify告知，预示silicon 硅simulated annealing 模拟退火simultaneous 同时的single mode fiber 单模光纤sinusoid正弦曲线sinusoidal 正弦的skew歪斜slab厚片，板层sledgehammer 大锤slew rate转换率，斜率slideshow幻灯放映SoC (System onChip)片上系统software title 软件产品solder焊接，焊料sonar声呐sophistication 复杂(性)sophistication 复杂性source源极space shuttle 航天飞机space-borne repeater 天空转发器spacer定位架子sparse稀疏，稀少spatial domain 空间域spatial空间的speaker identification 说话人辨认speaker recognition 说话人识另ijspeaker verification 说话人确认special-purpose 专用species 种，类specification 指标speckle散斑，斑点spectacular 惊人的spectrometer分光光度计spectroradiometer 分光光谱仪speech recognition 语音识另ijspell拼写，迷住splice结合，焊接spoke轮辐sponsor支持，赞助，资助spreadsheet电子表格spur刺激，激励spurious假的，伪造的spurt冲刺，喷射spyware间谍软件squawk box聊天室，论坛stack堆栈standalone独立的，可独立存在的standard deviation 标准差state of the art 最新的static electric 静电的stationary静止的，不变的statute法令，成文法律stem阻止，堵住step-index阶跃（突变）折射率stereo vision 立体视觉stereo立体声stimulus （pl. stimuli）刺激stimulus 刺激strain应力strategy 策略streak条纹striking惊人的，醒目的striking显著的，引人注目的strip剥离stumbling笨手笨脚的sub-carrier 子载波sub-field分领域，子领域submarine海底的，潜水艇sub-pixel亚像素subscription 订购subset子集substantial实质性的，重要的substitute 代替substrate 基底subtle细微的，微妙的subtraction 减法supercomputer超级计算机superheterodyne超夕卜差的superimpose叠加，重叠superior优越的superposition 叠力口superset 超集supply rails电源供给线suppress 抑制surf冲浪，浏览网络surveillance 监视survivability存活，存活可能性susceptible易受影响的swamp沼泽，进退两难之地sweepgenerator扫描发生器switch交换器，交换switching rate 切换速度syllable 音节syllogism三段论，推演synchronization 同步synchronize使同步，同时发生synchronous同步的synchrony 同步（性）syntactical 句法的syntax句法synthesis合成，综合synthesizer合成器Ttactile触觉（的）tamper损害，篡改tape library 磁带库tap-proof防窃听的telehealth远程保健telemedicine远程医疗telemetry遥测^ tele-otoscope 远程耳镜teleradiology远程放射学tele-stethoscope 远程听诊器teletype电传打字机telnet远程登录template模板，样板terahertz 特赫，1012 赫兹terminate 终止terminology 术语terms of contract 合同条款terrestrial地面的，地球上的terrorism恐怖主义tether拴，束缚the literature 文献（总称）thematic题目的，主旋律的theorem 定理theorize使…成为理论threshold 门限，阈值thresholding用阈值分割图像throughput 吞吐量time and attendance station 考勤系统time budget时间限制time slot 时隙time-critical对时间要求苛刻的time-invariant 时不变的timing diagram 时序图tint色彩tolerance偏差，容差，宽容度tomography 断层成像术 underestimate 低估 vowel 元音tooling 工具作业underestimation 低估 voxel 体（像）素topographic 地形的，地形学的 undergo 经历voyager 旅行者，探索者 topology 拓扑，布局universal 普遍的，宇宙的 vulnerable 易受攻击的towed streamer 拖曳飘带式水听器 阵unjustified 不可验证的 unmanned 无人的Wtrace 痕迹、微量 unpack 解开wafer 晶片，薄酥饼 track 跟踪unprecedented 前所未有的，空前 wagon 四轮马车tradeoff 折中，妥协 的Wall Street Journal 华尔街日报 trailing edge 后沿，下降沿 unquoted 未注明的waveform 波形 transact 处理，交易 unsigned band 未签约的乐队 waveguide 波导transaction 办理，交割 untie 解开，松开wavelet 小波 transceiver 收发器up converter 上变频器wee 微小的transducer 传感器，变换器 up-down counter 可逆计数器 weighted coding 加权编码 transferfunctions 传递函数 useability 可用性weighted 加权的 transfer 迁移，传递 used up 竭尽全力的，用尽了 well-suited 很适合于 transient 瞬态的utilization 利用wetland 湿地transistor 晶体管 translation 平移 Vwhereby （关系副词）靠那个 wide-ranging 范围广的 transmission line 传输线 vacuum tube 真空管，电子管 wiretapping 搭线窃听 transmission 透射vacuum 真空，真空的 woofer 低音喇叭transmitted 透射的，发射的 valve 阀word of data 数据中的“字” transparent 透明的，可透过的 van 货车，篷车word processor 文字处理软件 transponder 应答器，转发器 vapor deposition 汽相淀积，蒸镀 worm 蠕虫transverse 横向的 vapor 汽，蒸汽 worst-case value 最不利的数值trash 垃圾，废弃traveling wave tube 行波管 variable 变量 variation 变种 ZTriad 三个一组，三合一vegetation 植物 zero-crossing 过零点 tricky 机敏的，狡猾的 trigger 触发 trimming 微调Trojan horse 特洛伊木马Trojan 特洛伊（木马） tTerahertz 特赫（1012Hz ） tumble 摔跤 tunable 可调节的 tune 调谐 turnaround 周转，转向UUHF （ultra-high frequency ）特高频 ultraviolet 紫外线，紫外的 umbrella term 有多种含义的名词 unambiguous 不模糊的，不含糊的 unary 元的 unauthorized 未被授权的 uncertainty 不确定性uncommitted 未指定的，不受约束underappreciated 认识不足的，被低估的vendor 供应商 verification 确认versatility 多用途，多样性 version 版本 veterinarian 兽医 vice versa 反之亦然 vicinity 邻近，附近video conferencing 视频（电视）会 议video stream 视频（数据）流video-conferencing 视频会议 virtualshorting plane 虚拟短路平 面virtual system 虚拟系统 virtual 虚拟的，实际起作用的 virtually 事实上，几乎是 virus 病毒 visual perception 视觉 visualization 可视化，形象化 viz.（拉丁语 videlicet ）就是说volume 音量voluntary 自发的，自愿的zonation 成带，分区。