强空时杂波背景下自适应处理的稳健方法

对于机载雷达在强杂波背景中的自适应信号处理问题,提出了改进的静态方向图控制方法。新方法在原有架构上加入了二次波束方向图约束,并利用Taylor级数近似来估计其解。把自适应处理限制于变换域中的一个局域处理区域得到改进的降秩波束空间空时自适应处理架构。该架构中信号阻塞矩阵由围绕感兴趣单元的少量角度多普勒单元组成。把上述两种方法相结合得到一种稳健空时自适应处理方法。该方法能有效抑制杂波而同时保持低旁瓣,对采样要求低,大大减少了运算量。数值实验结果证明了所提方法的有效性。

Robust Algorithm for Adaptive Processing in Strong Space time Clutter Envirnment

A novel Quiescent Pattern Control(QPC) approach was proposed for airborne radar weak signal detection in strong space-time clutter environment.The new QPC approach imposed quadratic beampattern constraints in the adaptive processing and exploited the Taylor series approximation to estimate the solution.Adaptive processing was restricted to a Localized Processing Region(LPR) in the transform domain thus an improved rank-reduced beamspace space-time adaptive processing architecture was obtained.In the architecture,the blocking matrix consisted of angle-Doppler bins surrounding the bin of interest.The proposed approach was combined with the improved reduced-rank beamspace Space-Time Adaptive Processing(STAP) techniques to obtain a robust STAP method.The approach can cancel clutter while maintain low sidelobe more efficiently.It had low sample support requirement and strong robust implementation.It can also decrease computation load efficiently.Performance analysis was carried out using simulated data.The results proved the effectiveness of the proposed approach.