一种基于广义旁瓣相消的改进降秩算法

An Improved Reduced Rank Algorithm Based on GSC

在处理大型阵列时,阵元数较多,通常对阵列采用降秩处理可以较好地解决运算量过大的问题。基于广义旁瓣相消器(GSC)框架的降秩变换自适应滤波是各种降秩自适应滤波算法的统一模型。分析了基于GSC框架的几种降秩自适应滤波算法,针对当降秩阶数大于干扰数时方向图旁瓣过高、波形混乱和系统性能下降问题,提出了一种基于GSC框架的改进降秩算法,该算法利用特征子空间对GSC阻塞矩阵加以改进,使用改进后的阻塞矩阵进行降秩自适应处理,仿真结果证明了改进算法可以降低旁瓣电平,并形成较好的波束形状,提高了GSC性能的稳健性。

Dealing with large array with many elements, a good way to solve the problem of large corn putational complexity is reduced-rank adaptive filtering. The reduced-rank transformation adaptive filtering in the Generalized Sidelobe Canceller（GSC） structure is the uniform model for reduced rank adaptive filtering al gorithms. Several reduced rank adaptive filtering algorithms based on GSC structure arc analyzed. When the number of reduced rank is larger than thai of the jamming, the sidelobe rises and the performance of the sys tern declines. To solve the problem, a new algorithm based on GSC is proposed. It uses eigen-subspace to im prove the blocking matrix in GSC structure, then makes use of improved blocking matrix to perform the re duced-rank adaptive filtering. The simulations prove that the new algorithm can lower the sidelobe and form a better beam pattern. The robustness of GSC structure is improved.