摘要
针对由于阵列导向矢量存在估计误差及接收数据协方差矩阵估计不准确使得常规Capon波束形成算法性能显著下降的问题,提出一种基于协方差矩阵重构的稳健Capon算法用于改善其稳健性。所提方法首先基于线性收缩估计对接收数据协方差矩阵进行重构,以得到较为准确的协方差矩阵估计,并更新信号加干扰子空间,使得信号子空间与噪声子空间严格正交,而后将失配导向矢量投影至所更新子空间,从而求得优化接收权。仿真结果验证了算法的有效性。
The existence of steering vector estimation error and covariance matrix estimation uncertainty leads to the serious performance degradation of the traditional Capon beamforming. To improve the robustness of the Capon method, a covariance matrix reconstruction based robust Capon beamforming algorithm is proposed in this paper. Based on the linear shrinkage estimation, the developed method firstly reconstructs the receiving data covariance ma- trix to obtain the rather better estimation of eovariance matrix, and then updates the signal plus interference subspace to make the signal subspace and noise subspace orthogonal strictly. Following that, the mismatched steering vector is projected onto the updated subspace, and hence an optimized receiving weight can he obtained. The simulation re- suits demonstrate the efficiency of the proposed algorithm.
出处
《计算机仿真》
北大核心
2017年第5期209-212,共4页
Computer Simulation
基金
国家自然科学基金资助项目(61271379
61301258)
