海杂波背景下雷达目标检测和性能评估方法

发布时间：2018-03-25 10:54

本文选题：海杂波　切入点：海面目标检测　出处：《西安电子科技大学》2014年硕士论文

【摘要】：海面目标检测雷达在军用和民用方面都有重要的应用。常见的海面目标检测雷达包括机载对海探测雷达、舰载雷达和岸基雷达，这些雷达在工作时不可避免地会受到海杂波的干扰。因此，海杂波特性和海杂波背景下的目标检测研究受到了广泛关注。相干雷达具有速度分辨能力，有利于从杂波背景中检测运动目标，海杂波背景下的相干雷达目标检测逐渐成为一个重要的研究方向。论文围绕海杂波背景下的相干雷达目标检测问题，对高斯和复合高斯模型的相干最优检测进行了类比研究。针对海面目标检测经常遇到的高虚警问题，研究了利用两级自适应检测降低虚警率的算法。针对经典的自适应匹配滤波检测器计算量大的问题，提出了一种利用快速傅里叶变换（FFT）的快速算法。最后研究了雷达对海面上空目标检测的性能评估方法。论文工作具体包括如下三个方面： 1）海杂波基本模型验证和海杂波背景下的基本检测方法研究。首先用实测海杂波数据对常用的海杂波统计模型进行拟合验证。然后基于海杂波的复合高斯模型，介绍了对应的二元假设下的最优似然比检测方法。最后对高斯和复合高斯模型下的检测进行了类比研究，给出了适用于最优似然比检测和广义似然比检测的统一检测框架。 2）海杂波背景下的自适应检测方法研究。对经典的广义似然比检测（GLRT）、自适应匹配滤波（AMF）和自适应归一化匹配滤波（ANMF）三种自适应检测算法作了简要分析，重点对这三种算法的检测性能进行比较。针对自适应检测中杂波协方差矩阵估计技术，，介绍了三种杂波协方差矩阵估计的方法。为了降低AMF检测算法的虚警概率，研究了利用两级自适应检测降低虚警率的算法。为了减小AMF检测算法的计算复杂度，提出了一种基于FFT的AMF快速算法，并用实测海杂波数据证明了这种快速算法在降低计算复杂度的同时，还能保持和AMF检测算法相当的检测性能。 3）海杂波背景下的雷达性能评估方法。雷达性能评估的精度关系到雷达系统设计的成败。论文基于相干处理后的海杂波特性，获得了速度距离二维检测盲区图的产生方法和基于盲区图的雷达性能评估方法。利用该方法得到的评估结果可以实现雷达系统方案、系统参数和信号处理方法的优选。
[Abstract]:The sea surface target detection radar has important applications in both military and civil fields. The common sea surface target detection radar includes airborne sea detection radar, shipborne radar and shore based radar. These radars will inevitably be disturbed by sea clutter in operation. Therefore, the characteristics of sea clutter and the research of target detection in sea clutter background have been paid more and more attention. Coherent radar has the ability of velocity resolution. In order to detect moving targets from clutter background, coherent radar target detection in sea clutter background is becoming an important research direction. In this paper, the coherent optimal detection of Gao Si and complex Gao Si model is studied by analogy. Aiming at the problem of high false alarm often encountered in sea surface target detection, This paper studies the algorithm of reducing false alarm rate by using two-stage adaptive detection, aiming at the problem of large computation of classical adaptive matched filter detector. A fast algorithm based on fast Fourier transform (FFT) is proposed. Finally, the performance evaluation method of radar for target detection over sea surface is studied. The work of this paper includes the following three aspects:. 1) the basic model verification of sea clutter and the basic detection method under sea clutter background. Firstly, the statistical model of sea clutter is fitted with measured sea clutter data. Then, based on the composite Gao Si model of sea clutter, The optimal likelihood ratio detection method based on binary hypothesis is introduced. Finally, an analogical study is made on the detection under Gao Si and the complex Gao Si model, and a unified detection framework suitable for optimal likelihood ratio detection and generalized likelihood ratio detection is presented. 2) the research of adaptive detection method in sea clutter background. Three kinds of adaptive detection algorithms, namely GLRTT, AMF and ANMF), are briefly analyzed, which are based on generalized likelihood ratio (GML) detection, adaptive matched filter (AMF) and adaptive normalized matched filter (ANMF). In order to reduce the false alarm probability of AMF detection algorithm, three methods of clutter covariance matrix estimation in adaptive detection are introduced in order to reduce the false alarm probability. In order to reduce the computational complexity of AMF detection algorithm, a fast AMF algorithm based on FFT is proposed. The measured sea clutter data show that this fast algorithm can reduce the computational complexity while maintaining the detection performance comparable to that of the AMF detection algorithm. 3) Radar performance evaluation method under sea clutter background. The accuracy of radar performance evaluation is related to the success or failure of radar system design. The generation method of velocity distance 2-D blind area map and the method of radar performance evaluation based on blind area map are obtained. The optimal selection of radar system scheme, system parameters and signal processing method can be realized by using the evaluation results obtained by this method.
【学位授予单位】：西安电子科技大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TN957.51

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