一种无源雷达高速机动目标检测新方法

A Novel Algorithm for Detection of a Maneuvering Target in Passive Radar

针对无源雷达中高速机动目标在积累时间内出现距离和多普勒徙动,导致检测性能恶化的问题。该文建立了目标信号模型,提出一种基于Keystone变换结合傅里叶变换分段计算的高速机动目标检测方法,通过信号重叠分段划分快时间和慢时间,利用Keystone变换校正径向速度差的距离徙动,再对慢时间进行二次分段,并结合傅里叶变换的分段计算完成径向加速度差的距离和多普勒徙动校正,实现信号相参积累和目标检测。仿真和实测数据结果验证了该方法的有效性。

For passive radar, the maneuvering target causes range cell migration and Doppler cell migration, leading to a detection ability loss. The signal model is established and a novel detection algorithm is proposed to solve the problem. Firstly, the fast and slow time domains are divided by the overlapping segment method and the Keystone transform is adopted in order to correct the range cell migration due to differential velocity. Then the signal is divided into segments second time in the slow time domain. Finally range cell migration and Doppler cell migration induced by differential acceleration are corrected by the segmentation implementation method of the Fourier transform to achieve long term coherent integration. Experiments based oil simulated and practical signals verify the effectiveness of the proposed algorithm.