微弱信号源的和波束定向方法与分裂波束定向方法的性能比较

本文讨论水下辐射噪声源的精确定向问题，给出被动声纳和波束定向与分裂波束定向方法的性能比较。指出在一定信噪比下，分裂波束精确测向技术比和波束定向技术具有较高的定向精度。但是，随着信噪比的下降，两者趋于一致。推导了估计定向精度的分析表达式，给出在直线阵和圆弧阵情况下，延时估计和声源入射角偏差之间的换算公式和数值模拟结果。同时给出数字式声纳用以计算入射信号左波束和右波束数据的互谱来实现分裂波束定向的方法。     

互谱域MVDR自适应时延估计方法研究

针对窄带信号,通过构造互谱时间序列,在互谱域建立了平稳时间序列时延估计的最小方差无畸变响应(MVDR)滤波器模型;利用分段近似处理,类比空间MVDR自适应算法,给出了其具体算法(Algorithm of MVDR in cross spectral domain,CSMVDR);进行了数值仿真实验研究和海上实验数据处理。数值仿真与实验数据处理结果初步验证了CSMVDR时延估计对于舰船辐射噪声的适用性,CSMVDR时延估计有比相关检测更好的时延估计性能,能够提高信噪比增益和时延估计精度。     

脉冲压缩与互相关联合的合成孔径声呐回波时延补偿

针对合成孔径声呐中阵元相位不一致导致互相关时延补偿算法对成像质量提升效果有限的问题,提出了一种脉冲压缩与互相关联合的回波时延补偿算法.该算法利用脉冲压缩回波的互相关对原始回波相位畸变进行校正,实现粗补偿;联合脉冲压缩与偏移相位中心算法实现精细时延补偿,对不同合成孔径位置各阵元回波时延差实现了较为准确的估计,增强了成像效果。试验数据经该算法处理后,回波时延得到较为精确的补偿,地貌成像结果的亮度、对比度等统计特性得到不同程度的提高,且纹理细节增多;典型线缆目标的成像聚焦加深,成像长度误差约由5%减小为0.8%。试验结果显示,该算法对互相关时延补偿方法改进效果明显,验证了算法的可行性、有效性。      

基于二指向性接收阵元强度差的定向方法

水声领域中常用的高频定向算法通常基于时延或相位,这些方法受半波长布阵的限制,当信号频率超过一定限度时会产生角度模糊,从而影响方位估计效果。本文提出利用声轴方向有一定开角的有指向性水听器来引入不同阵元接收信号的强度差,利用强度差来估计目标的方位。这种方法由于不涉及相位或时延信息,一定条件下解决了高频声源定向过程中的角度模糊问题,并通过仿真和试验数据对算法性能进行了验证。     

基于马尔科夫链蒙特卡罗的时延估计算法

针对无源雷达中时延估计辐射源信号未知的情况,构建了一种新的时延最大似然估计模型.根据模型特点利用快速傅里叶变换(FFT)的计算方法实现时延估计.为了提高估计的精度,采用马尔科夫链蒙特卡罗(MCMC)抽样的方法估计时延值.该方法不需峰值检测,可直接给出时延估计结果.并推导了该模型下的时延估计的克拉美罗界(CRLB).仿真实验表明,MCMC算法可适用于窄带和宽带信号的时延估计;在样本相同的条件下,MCMC算法估计精度高于重要性采样(IS)算法和基于峰值检测的ML算法,计算复杂度低于IS算法,且MCMC算法可直接估计采样间隔非整数倍的时延.     

半经验关系与匹配场联合处理的爆炸声源快速定位

爆炸声源位置的快速准确获取对声源级测量和声传播计算具有重要意义。为了解决利用单一水听器进行爆炸声源定位时难以获得较好的定位效率和精度的问题,提出了一种基于半经验关系与匹配场联合处理的爆炸声源快速定位方法。首先通过爆炸声源满足的半经验关系,对爆炸位置进行预估,缩小匹配参数的搜索范围;同时,在基于多途时延差匹配定位理论的基础上,利用爆炸声源的半经验关系建立联合匹配定位方法,引入气泡脉动周期和冲击波峰值增加匹配物理信息,实现爆炸声源深度和距离精确反演。仿真分析与2013年南海水下爆炸声试验数据分析结果表明,一次气泡脉动周期与多途时延差的联合匹配可提高对爆炸声源深度的估计精度;冲击波峰值与多途时延差的联合匹配可提高对距离的估计精度。额外匹配量的引入减少了估计精度对接收阵元个数的依赖,能够实现用单阵元快速准确地进行爆炸源位置的估计。      

吸顶式传声器阵列阵元坐标标定方法

提出了一种吸顶式传声器阵列阵元坐标的标定方法。针对在混响声场中,时延估计算法性能严重下降从而导致在标定传声器阵元坐标时产生较大误差的问题,提出了利用脉冲声源作为标定声源,并且截取脉冲源直达声的方法来抑制混响声场的影响,提高传声器阵元坐标标定的精度。建立了阵元坐标标定的误差分析模型,并以白噪声和脉冲声源作为标定声源进行数据仿真和对比分析。仿真结果表明,使用脉冲声源作为标定声源能有效地抑制混响声场的影响,获得传声器阵列阵元的准确坐标。同时,在封闭的房间内建立起孔径为3.5 m、64阵元的螺旋状吸顶传声器阵列进行了实验研究,实验结果验证了本文提出方法的有效性。     

相关峰细化的精确时延估计快速算法研究

研究精确计算相关峰的方法,提高时延估计精度,改进传统的CZT算法,计算细化的频谱,降低了标准FFT计算带来的栅栏效应,利用互谱的前后两段计算相关函数的主峰波形,并建立了新的快速变换算法(FICP),相关峰可以任意“插值”而不增加计算量。采用该方法和模型,可以有针对性地利用有限范围频谱,抑制宽带噪声对时延估计的影响,提高相关峰的检测精度。     

双边相关变换在估计水下噪声源波达方向中的应用

研究双边相关变换高分辨率波束成形去估计水下噪声源波达方向的方法和性能,提出了对水下运动目标进行精确定向的一种高精度定向算法,用分割频带中的能量最大频段的窄带定向结果作为初始角,宽带中的高频分割频带作为处理对象来获得较高的定向精度。仿真数据和实际数据表明,该算法是一种花费时间少、定向精度高、简便实用的宽带定向方法。这种高精度的测向算法为水下两基阵交会测距提供了保证。     

基于宽带无失真波束形成的空气中多声源被动定向方法

将宽带无失真波束形成技术与基于时延的声被动定向方法相结合,针对小孔径基阵,提出了对多个声源的定向方法。该方法把整个观测空间分为若干个不同的测量区域,而后利用基于时延的定向方法定向处于不同测量区域的声源。此方法使基于时延的声被动定向方法具有了一定的多源分辨能力,对提高和改进声被动探测系统在实际使用中的性能有重要意义。仿真计算和空气实验验证了本文所提方法的正确性和实用性。     

分布式矢量传感器对宽带源被动定位的方法研究

本文给出了两种基于矢量传感器的被动定位方法。一般来说，对目标进行被动定位可以通过方位信息或时延信息来实现。单个矢量传感器就可以实现目标方位估计，而对多个矢量传感器接收的信号进行互相关运算即可得到目标对各矢量传感器的时延信息。本文先给出了利用方位信息进行被动定位的方法，然后给出了利用分布式矢量传感器进行方位一时延信息联合被动定位的新方法，并通过仿真分析对这两种方法的定位性能进行了比较。     

Closed-form analytical solutions of the time difference of arrival source location problem for minimal element monitoring arrays

Closed-form analytical solutions are found for the time difference of arrival (TDOA) source location problem. Solutions are found for both two-dimensional (2D) and three-dimensional (3D) source location by formulating the TDOA equations in, respectively, polar and spherical coordinate systems, with the radial direction coincident with the assumed geodesic path of signal propagation to a reference sensor. Quadratic equations for TDOA 2D and 3D source location based on the spherical intersection (SX) scheme, in some cases permitting dual physical solutions, are found for three and four sensor element monitoring arrays, respectively. A method of spherical intersection subarrays (SXSAs) is developed to derive from these quadratic equations globally unique closed-form analytical solutions for TDOA 2D and 3D source location, for four and five sensor element monitoring arrays, respectively. Errors in 2D source location for introduced bias in time differences of arrival are shown to have a strong geometrical dependence. The SXSA and SX methods perform well in terms of accuracy and precision at high levels of arrival time bias for both 2D and 3D source location and are much more efficient than nonlinear least-squares schemes. The SXSA scheme may have particular applicability to accurately solving source location problems in demanding real-time situations.     

Manatee position estimation by passive acoustic localization

Passive sound source localization with sensor arrays is based on the estimation of the time difference of arrival (TDOA), and precise TDOA is required to achieve accurate position estimation. For a majority of practical localization systems (based on TDOA estimation with four sensors in two dimensions), only three time delays are computed to determine the location of interest. This paper presents an approach to determine the position of a manatee by using four hydrophones and all the combinations of the TDOAs available. With four hydrophones, six TDOAs are computed and then combined three by three to get 20 possible points for each position to estimate. Experimental results using the Hilbert envelope peak technique to estimate the TDOAs and the least square method to estimate the position are presented. For the tests conducted it is shown that for a manatee call having a high signal-to-noise ratio, the individual position estimated for each of the 20 combinations of TDOAs lies on a straight line, providing a good estimation of the direction of arrival approximately 85% of the time. However, a good estimation of the position is obtained for a manatee near the hydrophone array approximately 55% of the time.     

基于虚拟仪器的简易声源追踪系统设计

为了在大型粮仓中局部出现害虫鸟类时可以快速找出其位置,解决目前声源定位设备成本高、计算量大实时性差的问题,对波达声差（TDOA）定位技术和互相关时延算法进行研究,提出一种改进了广义互相关时延估计算法,设计实现一种基于虚拟仪器的简易声源追踪系统根据害虫害鼠发出声音进行位置追踪进行粮仓管理。详细介绍了系统软硬件设计实现,系统可以实现参数设置、声源坐标的实时获取、文件存储、三维动态和数值显示等功能。实验结果显示,该系统具有实时性好、精度高、计算量小、工作稳定等特点。     

Distributed sound source localization algorithm with sound velocity calibration in windy environments

A new sound source localization method with sound speed compensation is proposed to reduce the wind influence on the performance of conventional TDOA(Time Difference of Arrival) algorithms. First, the sound speed is described as a set of functions of the unknown source location, to approximate the acoustic velocity field distribution in the wind field. Then,they are introduced into the TDOA algorithm, to construct nonlinear equations. Finally, the particle swarm optimization algorithm is used to estimate the source location. The simulation results show that the proposed algorithm can significantly improve the localization accuracy for different wind velocities, source locations and test area sizes. The experimental results show that the proposed method can reduce localization errors to about 40% of the original error in a four nodes localization system.     

Localization of a sound source in a noisy environment by hyperbolic curves in quefrency domain

Time Difference of Arrivals (TDOAs) of sound waves between microphones have to do with source localization. How well a sound source can be localized depends on how precisely the TDOAs are estimated. Although many ways to estimate TDOA have been proposed, noise always prevents us from finding exact time differences more or less in practice. Cross correlation has been the most prevalent way to estimate time difference, and various cross correlations robust to noise have also been developed. Nevertheless, much remains to be done for exact TDOA estimation under noisy environments. A novel way to show time delays in quefrency domain by removing noise has been proposed, which is called Minimum Variance Cepstrum (MVC). In particular, it is practically desirable to visualize source position with as few number of sensors as possible. Once TDOAs are obtained precisely, it is enough to show the source position in a 2-D plane using hyperbolic curves with only three sensors. In this work, the MVC is adopted to accurately estimate TDOAs under noise, and a way to localize an acoustic source by intersecting hyperbolic curves using the TDOAs between three microphones is proposed. Numerical simulations on TDOA estimation and source localization with white Gaussian noise demonstrated that the proposed method worked well under the noisy environment, and we compared the results with those of other old but well-established cross correlation estimators. In addition, experiments to detect a leaking point on a pipe successfully showed where the leak sound was generated.     

MIMO声呐的双尺度旋转不变子空间波达方向估计*

为了提高单基地多输入多输出(Multiple-Input Multiple-Output, MIMO)声呐阵列的波达方向(Direction of arrival, DOA)估计性能,提出了双尺度旋转不变子空间(Dual-Resolution Estimation of Signal Parameters via Rotational Invariance Techniques, DR-ESPRIT)算法。结合MIMO阵列虚拟阵列的结构特征,首先利用ESPRIT算法通过各条虚拟线阵内、基线间距不大于半波长的子阵间的旋转不变关系得到无模糊的粗估计结果,之后利用虚拟线阵间、基线较长的子阵间的旋转不变关系得到一组有模糊的精估计结果。参考粗估计结果对精估计结果进行解模糊,最终得到高精度无模糊的角度估计结果。为了降低运算复杂度,利用该思路对降维ESPRIT算法也进行改进,提出了双尺度降维ESPRIT算法。仿真试验首先验证了与传统算法相比,双尺度类DOA估计算法能够有效提高角度估计精度。此外,还分析了MIMO声呐阵列的发射、接收阵元的幅相扰动误差对算法角度估计性能的影响。     

基于时频差的正交容积卡尔曼滤波跟踪算法

针对基于时频差测量的无源跟踪中面临的非线性估计问题, 提出一种正交容积卡尔曼滤波跟踪算法. 该算法在容积卡尔曼滤波算法的基础上, 通过引入特定正交矩阵改进容积采样方法, 在高维状态估计下减小因采样产生的误差, 在没有增加计算量的前提下, 有效提高收敛速度及跟踪精度. 仿真结果表明, 在基于到达时差和到达频差的联合无源跟踪问题中, 与扩展卡尔曼滤波及容积卡尔曼滤波算法相比, 本文所提算法在跟踪性能上有明显提升.     

输气管道泄漏的波达时差交叉定位方法*

为了实现对管道泄漏位置的三维定位,该文提出一种基于波达时差法的交叉定位方法。将传感器阵列布放在不同位置,通过波达时差法获取远场泄漏声源的两组空间方位信息,对两组方位交叉求取空间伪交点从而完成定位。建立泄漏定位实验平台,分析了多种互相关方法以及阵列孔径、布放间距、泄漏位置等因素对延时估计和定位精度的影响。实验结果表明:选取基本互相关法对泄漏信号的10 500 Hz分量进行互相关分析,能够获取稳定的延时估计结果;在有效信号检测范围内,增大阵列孔径和布放间距能有效减少误差;该文方法相较于现有波达时差法能有效提高距离原点4 m以上泄漏位置的定位精度。     

基于DSP的电动汽车锂电池荷电状态估算的研究与实现

锂电池荷电状态(SOC)的准确估算是电动汽车能源管理的关键技术。为了提高锂电池SOC的估算精度,将无迹卡尔曼滤波(UKF)应用于锂电池SOC估算,以减小拓展卡尔曼滤波(EKF)简单线性化带来的误差。搭建电池检测系统的硬件平台,以TMS320F28335型数字信号处理器(DSP)为主控芯片(MCU),实现电压、电流、温度的检测及UKF算法,并设计了相关的电池测试实验。实验结果表明,UKF可以实时估算锂电池SOC,估算误差在4%以内,高于传统的拓展卡尔曼滤波(EKF)。