回溯降维相干分布式非圆信号DOA快速估计

在相干分布式非圆(CDNC)信号波达方向(DOA)估计中,针对阵列输出矩阵扩展后维数增加带来的较大运算量问题,基于降维的多级维纳滤波(MSWF)技术,引入回溯优化思想,提出了一种快速估计算法。该算法首先利用信号非圆特性扩展阵列输出矩阵,然后通过MSWF递推分解快速求出信号子空间,避免了计算阵列协方差矩阵及特征分解,并且在递推过程中引入回溯优化机制提高了各级匹配滤波器的估计性能,最后由最小二乘(LS)或者总体最小二乘(TLS)得到DOA估计。仿真分析表明,所提算法与相干分布式非圆信号旋转不变子空间算法(CDNC-ESPRIT)性能相当,但复杂度得到了大幅度降低,相比于基于MSWF的非圆信号快速子空间(NC-MSWF-FS)算法,在较小的复杂度代价下大幅度提升了低信噪比时的估计性能,并且对初始参考信号的选取具有了较强的鲁棒性。

Fast DOA estimation for coherently distributed noncircular sources by backtracking reduced dimension

In the estimation of Direction of Arrival (DOA) for coherently distributed noncircular (CDNC) signals,the increase of dimension caused by array output matrix extension can bring a large amount of computation.For the problem,a fast estimation algorithm based on the Multi-Stage Wiener Filter (MSWF) technology is proposed by introducing the idea of backtracking optimization.The proposed algorithm first uses the noncircularity of the signal to extend the array output matrix.The signal subspace is then obtained by using the recursive decomposition characteristic of the MSWF,so as to avoid the computation of the covariance matrix and the characteristic decomposition of the matrix.In the recursive decomposition process,the backtracking optimization mechanism is introduced to improve the estimation performance of the matched filter.The DOA estimation can be obtained by the Least Squares (LS) or the Total Least Squares (TLS).Simulation results show that the performance of the proposed algorithm with a much lower complexity is comparable with the rotation invariant subspace algorithm based on CDNC (CDNC-ESPRIT).Compared to the fast noncircular signal subspaced algorithm based on the MSWF (NC-MSWF-FS),the proposed algorithm can effectively improve performance at lower complexity cost in low signal to noise ratio.The simulation also shows that the proposed algorithm is more robust to the initial reference signal.