基于M-CAP的三维空时自适应降维算法

Reduced-dimension 3D STAP method based on M-CAP

针对机载雷达的三维空时自适应处理(3DSTAP)存在运算量大和采样数目要求高的问题,提出了一种基于多通道联合自适应处理(M-CAP)的三维空时自适应降维算法,即,先对接收信号进行时域滤波,然后选取被检测通道与其多个相邻通道为一组,进行双迭代自适应降维处理。由于充分利用相关域的信息,迭代求解两个低维的权向量,从而降低了计算复杂度和采样要求。基于仿真和实测数据的实验验证了算法的有效性和稳健性。

For the extremely high computational complexity and sample support requirement of three-dimensional space-time adaptive processing （3D STAP）, a reduced-dimension 3D STAP method for airborne radar is developed on the basis of a multiple Doppler channels joint adaptive processing （M-CAP） method. Firstly, temporal filtering is performed on the 3D space-time received data, and then the output data of M Doppler channels which are the detected Doppler channel and its adjacent channels, is adaptively filtered. By iteratively optimizing two lower dimensional weight vectors based on correlation matrix, both the computational complexity and training requirement are reduced. Experimental results by using the measured data demonstrate the effectiveness of the proposed method.