匹配滤波在SAR目标单个散射部件检测中的应用

The application of matched filter in detecting single scattering parts of SAR targets

目的目标部分缺失是SAR(synthetic aperture radar)ATR(automatic target recognition)中的难点问题,实现SAR目标散射部件级别的检测可以有效解决这一问题。方法基于目标的部件级别3维电磁散射模型提出了一种基于匹配滤波的单个散射部件检测方法。该方法通过模型预测单个散射部件的图像构造匹配滤波器,并通过在模型3维参数域的调整实现了匹配滤波器在3维空间的滑动,得到最佳的部件检测位置和最大相关系数。为克服方位角估计不准的限制,采用了领域搜索寻找最佳检测结果。按照散射部件的强度由强至弱序惯检测各个散射部件。采用CLEAN算法去除部件之间的相互干扰。结果在简易坦克部件级3维电磁散射模型基础上,利用电磁仿真数据、暗室数据以及MSTAR(moving and stationary target acquisition and recognition)干扰数据进行了单个散射部件检测实验,实验结果表明,本文方法可以很好地检测出实测图像中存在的目标散射部件,并且可以检测出缺失的散射部件。结论本文提出了基于匹配滤波器的散射部件检测方法,实验证明了该方法的有效性。

Objective Part absence is a difficult problem in Synthetic Aperture Radar （SAR） Automatic Target Recognition. However, such problem can be resolved to some extent by detecting the single scattering part of the target in the measured SAR data. Method This study proposes a matched filter-based approach to detect single scattering part on the basis of the part-level 3-D scattering model of the target; this approach can well predict the scattering properties of the whole target and the single scattering part comprising the target. The following steps are used in applying the matched filter approach in detecting single scattering part： First, a matched filter is built according to the image of the single scattering part predicted by the scattering model. Second, the matched filter slides in the 3-D parameter domain detects the best position of the scattering part that is appropriate for the measured SAR image and determines the maximum correlation coefficientto enhance detection precision. Moreover, in terms of the imprecision of azimuth estimation, the premiumposition is explored in the neighborhood to obtain the best result. According to the intensity of all visible scattering parts under the present position, the strongest to the weakest parts are detected sequentially. The interference from the neighboring scattering part disturbs the detection of the present scattering part. The CLEAN algorithm is employed to overcome this problem and to eliminate the interference of the other scattering parts. Result A part-level 3-D scattering model of a simple tank is used in this study. Experiments are conducted on the basis of electromagnetically simulated data, dark-room measured data of the simple tank, and MSTAR （ moving and stationary target acquisition and recognition） data, which are used as interference. Results demonstrate that the proposed method can detect existing scattering parts in the measured image, as well as find the absent parts. In addition, interfering data can be excluded from the experiments. Conclusion This study proposes a single scattering part detection method for SAR target. Experiment results confirm the efficiency of the method.