提高雷达机动目标检测性能的二维频率域匹配方法

 增加目标信号的积累时间是提高雷达对微弱目标探测能力的主要方法.但是,对于高速运动目标,在长时间相参积累期间,目标回波信号容易产生距离徙动和多普勒走动,若不进行补偿,目标信号能量不能有效积累.传统基于keystone变换的方法仅适用于目标作匀速运动的情形,当目标作机动运动时,距离弯曲不能通过keystone变换进行校正.针对目标作匀加速运动,且高速目标存在多普勒模糊情况,本文提出一种二维匹配滤波新方法,该方法将脉冲压缩后的目标回波转换到距离-多普勒二维频率域,通过构造一补偿函数进行匹配滤波处理.该方法不需要知道目标运动速度参数,由目标径向速度引起的距离走动和径向加速度引起的距离弯曲均能得到很好的消除,另外,所提算法可以有效地利用快速傅里叶变换实现而无需进行插值操作,运算量小.仿真结果表明本文方法具有良好的高速机动目标积累检测性能.

A New Method for Radar Maneuvering Target Detection Based on Matched Filtering in Two-Dimensional Frequency Domain

Increasing integration time can improve the detection performance of weak targets.However,the signal energy could not be effectively accumulated,because the high-speed motion of a target induces range migration and Doppler walk in long-time coherent integration period.Thus the motion compensation is necessary.Unfortunately,the traditional methods based on keystone transform are only suitable for uniform motion targets,while the range curvature of maneuvering targets can not be corrected by keystone transform.In this paper,for moving target with constant acceleration and Doppler ambiguity,a new method is proposed by constructing the two-dimensional compression function in range-Doppler frequency domain,which can eliminate the coupling effect between range and azimuth.This method does not require target velocity parameters and can correct the range migration caused by radial velocity and radial acceleration.The proposed algorithm can be efficiently implemented by using fast Fourier transform without interpolation and thus has low computational complexity.Simulation results show that the proposed algorithm improves the performance for detecting high-speed maneuvering targets.