基于协方差矩阵重构的方向图保形算法

Conformal algorithm of a directional graph based on covariance matrix reconstruction

现代雷达探测过程中需要采用自适应波束形成技术,在干扰处形成零陷从而消除干扰的影响。然而,波束产生零陷的同时也会导致主瓣波束产生畸变,严重降低了目标检测能力,针对波束保形问题,提出了一种具有波束保形的(worst-case performance optimization,WCPO)最差性能最优化算法。该算法通过对空间中不包含目标信号的区域进行积分来获得一个重构的干扰-噪声协方差矩阵,接着引入一个二次惩罚项使得重构的协方差矩阵满足凸优化条件,最后通过凸优化理论得到权矢量的最优解。区别于传统WCPO算法,该算法在相同条件下有着更高的输出信干噪比(signal-to-jamming noise ratio,SINR),并能在主瓣同时存在多个干扰,且不需要干扰信号先验信息的情况下实现主瓣波束保形。仿真验证了算法的有效性。

In the process of modern radar detection,adaptive beamforming technology is used to form a null trap at the jamming position so as to eliminate its influence.However,the null of the beam also leads to the distortion of the main lobe beam,which seriously reduces the ability of detecting the target.In this paper,a worst-case performance optimization(WCPO)algorithm is obtained to deal with beam conformation.The algorithm obtains a reconstructed jamming noise covariance matrix by integrating the region that does not contain the target signal in the space,then introduces a quadratic penalty term to make the reconstructed covariance matrix meet the convex optimization condition,and finally obtains the optimal solution of the weight vector through the convex optimization theory.Compared with the traditional WCPO algorithm,the proposed algorithm has a higher output signal-to-jamming noise ratio under the same conditions,and can realize the main lobe beam shape preservation when there is multiple jamming in the main lobe without prior information of jamming signals.The simulation verifies the effectiveness of the algorithm.