利用多途时延的被动目标定位方法

本文研究了在海洋波导环境中利用多途时延信息进行水下目标被动定位的方法。理论分析了在等声速理想海洋波导环境中,多途时延信息随时间变化的规律及其与目标运动状态之间的联系。分析结果表明,不需要已知声线类型而仅利用多途时延信息即可实现浅海波导环境中水下目标的被动定位。利用多途时延信息,当有两条声线到达时可以估计运动目标的归一化径向速度;当有三条声线到达时,可实现水下运动目标距离、径向速度的估计。最后利用仿真和实验数据对上述结论进行了验证。     

用子空间旋转不变法同时估计水下多目标的距离和方位

提出了一种可在单次回波内同时完成方位和时延估计的高分辨新方法,它采用于空间旋转不变法（ＥＳＰＭＴ方法）的思路构造两个子阵,通过对其自相关矩阵和互相关矩阵的广义特征分解,用特征值估计多目标方位,用特征向量估计多目标时延,利用特征值和特征矢量的对应关系自动实现方位和时延参数的配对．计算机仿真结果表明,该方法的分辨能力、估计精度和正确配对概率都优于常规方法,较好地实现了水下多目标距离和方位的同时估计及配对,进而可对多目标进行定位．     

一种水下三维被动定位技术

本文给出了一种三维被动定位方法。该方法利用三元水平阵和二元垂直阵实现对目标的三维定位。由三元水平阵首先求得目标斜距和目标方位,在此基础上利用垂直阵估计目标深度坐标,最后综合已有测量结果来求解目标水平坐标。本文还通过仿真分析了该方法的定位性能。     

小型矢量阵深海被动定位方法

文中提出一种适用于深海条件下并已知各项有关环境参数时,利用七元小型矢量立体阵,借助测定目标辐射噪声由不同途径自声源到达接收点的天顶角及方位角的结果,依据射线声学方法求得目标方位、距离和所在深度的被动定位方法。给出了矢量阵依多极子原理进行波束形成的计算公式,并就一种简单水文模型,给出解析计算公式。     

基于粒子滤波的多普勒信息辅助目标定位跟踪算法

多基地声呐探测系统主要通过测量回波的时延和方位信息进行目标定位与跟踪,定位精度受声速、时延和方位测量误差的影响较大,可以通过多普勒信息辅助进一步提高定位跟踪精度。现有的多普勒信息辅助定位跟踪算法多适用于单基地声呐系统,多基地中的多普勒测量值与目标状态的关系更为复杂,需要研究新的融合方法。该文提出了一种适用于多基地声呐系统的多普勒信息辅助采样重要性重采样目标定位跟踪算法,将多普勒信息融入到粒子滤波的重采样过程,使重采样后的粒子集合更逼近目标的真实状态分布,从而提高了目标定位跟踪精度。数值仿真实验结果表明,提出的目标定位跟踪算法可以有效融合多普勒信息,提升目标定位跟踪精度。     

分布式浮标阵水下高速运动声源三维被动定位

给出一种用于垂直爬升弹道三维坐标精确测量的分布式浮标网络超长基线宽带被动定位技术。考虑四个呈正方形布局的浮标节点,利用水平方位角交汇的定位方法测量上浮弹道的水平x、y坐标,水平方位角估计由灵巧的声矢量传感器替代常规阵得到,并给出定向误差小于0.4°的湖试结果;利用直达声和海面反射声之间的时延差提取弹道的垂直坐标z,并给出了高速运动目标垂直爬升弹道的海试测量结果,弹道测量误差小于10 m。      

拖曳式水平鱼探仪海上试验研究

为了简化设备组成,方便操作使用,降低设备成本,对拖曳式水平鱼探仪采用了被动工作方式,利用监测鱼群噪声以确定鱼群方位。采用水平拖曳方式时,对拖体内两个矢量水听器所接收信号进行本船噪声抵消运算,有效地降低了本船噪声干扰,从而保证了必要的目标检测距离。利用矢量水听器所测得声压与质点振速的相关性,借助非线性最优化技术,按照单矢量水听器多目标定向方法,解算并输出显示各目标方位。根据具体要求,可以显示目标的地理方位,也可以显示目标相对于本船的方位。     

一种矢量水听器基阵模拟器的设计

矢量水听器的每个阵元同时测量声场中声矢量和质点振速的3个分量,相对于声压水听器阵来说,矢量阵获取声场中更多的信息。利用矢量阵所获得速度场的信息可以去除目标方位估计中的 180°模糊。模拟器可以模拟实际海洋环境中目标的辐射特性和噪声特性,应用模拟器可以有效地缩短声纳的研制周期。本文提出一种矢量水听器基阵模拟器的设计方案,该方案解决了矢量阵中宽带信号的90°移相问题、时延精确控制问题和宽带噪声的谱状控制问题。     

稀疏矢量阵信号栅瓣及对称伪峰干扰抑制

稀疏矢量阵进行宽带信号处理时,强目标的栅瓣及对称伪峰会干扰弱目标的检测,提出了一种基于理论干扰预测的加权抑制方法。方法利用矢量阵波束形成先获得强目标的波达方向(Direction Of Arrival,DOA)信息以及目标所在方位各频率的幅度谱信息,再利用理论计算公式获得强目标的栅瓣和对称伪峰角度上对应的各频率点的幅度谱强度信息,通过在方位、频率维度加权的方式对强目标的栅瓣和伪峰干扰进行抑制,来改善在强干扰下的弱目标检测能力。方法也适用于多目标情况,对各个目标依次使用,减少多目标时栅瓣和对称伪峰对方位历程的影响,净化了时间方位历程图。对所提方法给出了理论推导过程并进行了仿真和实验验证,实验结果验证可行。结果表明,新方法可以有效地抑制强目标的栅瓣和对称伪峰干扰,提高弱目标的检测能力,此外,净化后的时间方位历程图更利于弱目标检测和目标数量的估计。      

声矢量传感器阵宽带相干信号子空间最优波束形成

提出了基于矢量传感器阵的宽带相干信号子空间最优波束形成。建立了矢量传感器阵的宽带阵列信号模型,将宽带聚焦思想引入到了矢量传感器阵宽带处理,证明了矢量传感器阵与声压传感器阵宽带聚焦矩阵之间的关系,为矢量传感器阵宽带聚焦矩阵的构造提供了一种方法。推导了基于矢量传感器阵宽带最优波束形成的空间谱,通过空间重采样方法实现矢量传感器阵宽带聚焦,避免了对目标源方位的预估。通过仿真验证了矢量传感器阵具有更优越的性能:可以解宽带相干源;能够实现全空间无模糊定向;可以空间欠采样,因而在不增加计算量的基础上,能够提高阵列处理的性能;克服了传统声压传感器线阵端射方向上,目标方位估计性能下降的缺点。     

Detection of number of sources and DOA estimation based on the combined information processing of pressure and particle velocity using acoustic vector sensor array

In order to solve the problem of DOA(direction of arrival)estimation of underwater remote targets,a novel subspace-decomposition method based on the cross covariance matrix of the pressure and the particle velocity of acoustic vector sensor arrays(AVSA)was proposed. Whereafter,using spatio-temporal virtual tapped-delay-line,a new eigenvector-based criteria of detection of number of sources and of subspace partition is also presented.The theoretical analysis shows that the new source detection and direction finding method is different from existing AVSA based DOA estimation methods using particle velocity information of acoustic vector sensor(AVS)as an independent array element.It is entirely based on the combined information processing of pressure and particle velocity,has better estimation performance than existing methods in isotropic noise field.Computer simulations with data from lake trials demonstrate,the proposed method is effective and obviously outperforms existing methods in resolution and accuracy in the case of low signal-to-noise ratio(SNR).     

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。     

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.     

On the angular error of intensity vector based direction of arrival estimation in reverberant sound fields

An acoustic vector sensor provides measurements of both the pressure and particle velocity of a sound field in which it is placed. These measurements are vectorial in nature and can be used for the purpose of source localization. A straightforward approach towards determining the direction of arrival (DOA) utilizes the acoustic intensity vector, which is the product of pressure and particle velocity. The accuracy of an intensity vector based DOA estimator in the presence of noise has been analyzed previously. In this paper, the effects of reverberation upon the accuracy of such a DOA estimator are examined. It is shown that particular realizations of reverberation differ from an ideal isotropically diffuse field, and induce an estimation bias which is dependent upon the room impulse responses (RIRs). The limited knowledge available pertaining the RIRs is expressed statistically by employing the diffuse qualities of reverberation to extend Polack's statistical RIR model. Expressions for evaluating the typical bias magnitude as well as its probability distribution are derived.     

Turboprop and rotary-wing aircraft flight parameter estimation using both narrow-band and broadband passive acoustic signal-processing methods

Flight parameter estimation methods for an airborne acoustic source can be divided into two categories, depending on whether the narrow-band lines or the broadband component of the received signal spectrum is processed to estimate the flight parameters. This paper provides a common framework for the formulation and test of two flight parameter estimation methods: one narrow band, the other broadband. The performances of the two methods are evaluated by applying them to the same acoustic data set, which is recorded by a planar array of passive acoustic sensors during multiple transits of a turboprop fixed-wing aircraft and two types of rotary-wing aircraft. The narrow-band method, which is based on a kinematic model that assumes the source travels in a straight line at constant speed and altitude, requires time-frequency analysis of the acoustic signal received by a single sensor during each aircraft transit. The broadband method is based on the same kinematic model, but requires observing the temporal variation of the differential time of arrival of the acoustic signal at each pair of sensors that comprises the planar array. Generalized cross correlation of each pair of sensor outputs using a cross-spectral phase transform prefilter provides instantaneous estimates of the differential times of arrival of the signal as the acoustic wavefront traverses the array.     

矢量声纳高速运动目标稳健高分辨方位估计

针对水声矢量信号处理框架中的高速运动目标低信噪 比小快拍条件下的稳健高分辨方位估计问题, 将压缩感知技术应用于水声矢量信号空间谱估计模型中. 结合声矢量传感器结构特性, 探讨了基于声压振速联合处理的广义时域滤波方法; 结合矩阵空域预滤波理论, 设计了基于阻带约束通带均方误差最大值最小的空域滤波器, 研究了矢量声纳空域预滤波方法; 结合以上分析, 提出了基于压缩感知技术的时空联合滤波高分辨方位估计方法, 给出了方法的数学模型、物理解释及具体实施步骤.理论分析和计算机仿真试验表明, 新方法对于小快拍数 条件下的矢量声纳高速运动目标高分辨方位估计问题, 具有较低的双目标分辨门限和较高的估计精度, 有着良好的应用前景.湖上试验验证了方法的有效性. 关键词： 声矢量传感器 空间谱估计 时空滤波 压缩感知     

传感器网络基于特征值分解的信号被动定位技术

基于传感器网络的信号被动定位技术在电磁学、声学、声呐系统以及传热学等领域具有广泛的应用前景,当传感器网络节点所接收噪声强度不同或传输信道存在阴影衰落效应时,给出了目标信号到达距离比定位关联度量的估计方法与基于信号到达距离比的被动定位算法.将特征值分解技术引入到信号到达距离比定位关联度量估计中,通过接收信号协方差矩阵特征值分解技术估计各节点所接收噪声强度,并通过网络参考节点轮换与特征值分解方法消除阴影衰落效应所引入的定位误差,最后给出该算法的最小二乘定位解.该方法可较好的消除由于节点接收噪声强度不同以及阴影衰落效应等因素所带来的定位性能恶化.     

Direction-of-arrival estimation for extensible acoustic vector sensor array

Aiming at high-resolution estimation of the direction-of-arrival of closely-spaced sources at low signal-to-noise ratio regions, this paper proposes a DOA estimation algorithm that is suitable for an extensible acoustic vector sensor array. Taking the 3D array composed of the minimum number(four) of acoustic vector sensors as the acquisition module, a virtual array having the same structure as the original array structure is extended in the three-dimensional space based on the aperture expansion characteristic of higher-order cumulants. The virtual array and the real array can construct a matrix with rotational invariance, which contains the angular information for estimating DOA. The Cramer-Rao bound of the algorithm are derived. We analyze the influence of SNR, the number of snapshots and the elevation angle on the performance of the algorithm. Simulation results show that the proposed algorithm has better noise suppression ability and higher resolution in DOA estimation than the conventional ESPRIT algorithm using the acoustic vector array. Experiments are conducted to validate the proposed algorithm.     

基于声矢量传感器的分布式定位系统在水下宽带声源定位中的应用

提出了基于声矢量传感器的分布式浮标网络定位系统,研究了不同应用背景下单个声矢量传感器的测向算法,推导了目标DOA估计的Cramer-Rao界,给出了分层海水介质中多个声矢量传感器的几何定位算法。数值仿真结果表明:(1)系统的定位性能强烈依赖于接收信噪比;(2)该系统适用于单一强声源的定位。     

The two-dimensional source location problem for time differences of arrival at minimal element monitoring arrays

The time difference of arrival (TDOA) source localization inverse problem is analyzed for two-dimensional signal propagation detected by a small number of sensor elements in a monitoring array. Nonlinear least-squares solutions are found based on the assumptions of geodesic rays propagating at constant speed. The two-dimensional (2D) TDOA source location problem is shown in the case of three sensors to have dual possible solutions for some combinations of arrival time differences. In the case of four non-collinear sensors, there are unique solutions for all physically possible combinations of time differences. Dual solutions to the three-sensor problem are associated with a small range of arrival time differences but large regions in physical space. The locations of the dual solutions are separated by a wide variety of distances, which in some cases prevent the use of alternative reasoning to remove the ambiguity. Three-sensor TDOA cannot be reliably used for 2D source location unless the source is a priori known to be within either the spatial region spanned by the sensor array or the external zones of unique solution. Determining the minimum number of sensors necessary to unambiguously solve the source location problem assists in cost-effective design of sensor arrays.