MVDR多波束方位—时延—多普勒三维解卷滤波及算法

发布时间：2018-10-10 12:00

【摘要】：主动声纳在空间平面波处理中感兴趣的目标参量为水平方位。空间域处理,目标参量估计的高可靠和高分辨力需要进行波前设计,使阵响应函数集中。波方程揭示着空-时具有对偶性。主动声呐在时间域处理中感兴趣的参量是目标距离和径向速度,它们无法直接观测得到,需要通过估计与其对应的时延和多普勒参量而获得。时间域处理,目标参量估计的高可靠和高分辨力需要进行波形设计,使模糊度函数时延-多普勒两维集中。一维时间信号用时延-多普勒两维函数——模糊度函数来描述其时频联合特性,其本质是匹配滤波器。检测和估计总是相伴随进行的,在高斯噪声背景下,两者的最佳处理器均是数据和拷贝相关的匹配滤波器。时间匹配包括时延匹配滤波和时延-多普勒匹配滤波,空间波束形成包括平面波波束形成和波导环境下的匹配场波束形成。本文根据窄带情况下的空-时可分解性,先进行空间处理再时间处理,得到空-时相关结果。空间波束形成将阵元域转换到波束域,本文采用能连续观察的多波束系统。最小方差无失真(Minimum Variance Distortionless Response, MVDR)波束形成可以抑制干扰来提高空间分辨力。根据空-时对偶性,本文提出,在波束域进行MVDR方位-时延-多普勒三维干扰抑制,来提高其三维分辨力。由测量信号估计目标参数是由果到因的逆问题求解,匹配是正向拟合来解决逆问题,解卷是逆向解决逆问题。本文提出的解卷算法是从最小鉴别准则出发的Richardson-Lucy(R-L)迭代解卷算法。空间波束形成后的测量信号与发射信号的两维匹配,是模糊的时延-多普勒两维函数——采样互模糊度函数,其期望建模为发射信号自模糊度函数和目标反射性密度函数的两维卷积。利用R-L算法对该期望进行两维解卷积,消除发射信号引起的时延-多普勒模糊,重构出目标反射性密度函数,进而进一步获得高分辨的多目标的距离和径向速度参量估计。三维MVDR干扰抑制结合该R-L迭代解卷滤波形成了本文的MVDR多波束方位-时延-多普勒三维解卷滤波系统,仿真和实验处理结果均验证了该三维处理系统的有效性。
[Abstract]:The target parameter of active sonar in spatial plane wave processing is horizontal azimuth. In spatial domain, the high reliability and high resolution of target parameter estimation need to be designed to make the array response function concentrated. The wave equation reveals the duality of space-time. The parameters of interest to active sonar in time domain processing are target distance and radial velocity which can not be directly observed and need to be obtained by estimating the corresponding time delay and Doppler parameters. In time domain processing, the high reliability and high resolution of target parameter estimation need to be designed to make the ambiguity function time-delay and Doppler two dimensional concentration. In one-dimensional time signals, the time-frequency joint property is described by the time-frequency ambiguity function, which is a time-Doppler two-dimension function, which is essentially a matched filter. Detection and estimation are always accompanied by Gao Si noise background, the optimal processor of both is data and copy correlation matching filter. Time matching includes time-delay matched filtering and delay-Doppler matched filtering. Space beamforming includes plane wave beam formation and matched field beamforming in waveguide environment. According to the space-time decomposability in narrow-band case, the space-time correlation results are obtained by spatial processing and time processing. Spatial beamforming converts the array element domain to the beamspace. In this paper, a continuous observation multibeam system is used. Minimum variance distortionless (Minimum Variance Distortionless Response, MVDR) beamforming can suppress interference and improve spatial resolution. According to the space-time duality, the MVDR azimuth time-delay Doppler 3D interference suppression is proposed in the beamspace to improve its 3D resolution. The inverse problem of estimating the target parameters from the measurement signal to the cause is solved, the matching is positive fitting to solve the inverse problem, and the deconvolution is the reverse solution to the inverse problem. The deconvolution algorithm proposed in this paper is a Richardson-Lucy (R-L) iterative deconvolution algorithm based on the minimum discriminant criterion. The two dimensional matching between the measured signal and the transmitted signal after beamforming is a fuzzy time-delay Doppler two-dimensional function sampling mutual ambiguity function. The desired model is a two dimensional convolution between the self ambiguity function of the transmitted signal and the reflection density function of the target. The R-L algorithm is used to deconvolution this expectation in order to eliminate the time-delay Doppler ambiguity caused by the transmitted signal and reconstruct the reflection density function of the target. Then the distance and radial velocity parameter estimation of the high resolution multi-target is obtained. Three-dimensional MVDR interference suppression and R-L iterative deconvolution filtering are combined to form the MVDR multi-beam azimuth time-delay Doppler three-dimensional deconvolution filtering system. The simulation and experimental results show the effectiveness of the system.
【学位授予单位】：浙江大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：TN713

【相似文献】