用基于空间平滑的正交化算法分离相干信号

正交化超分辨算法在大信噪比时性能优良且运算量小,但由于正交化算法是一种信号子空间方法,因而在干扰相干时失效,而空间平滑方法已广泛应用于自适应阵列相干信号的分离.文中提出了3种基于空间平滑的改进正交化算法并给出了计算机仿真结果.第1种方法具有较小的运算量,但当信噪比降低时,性能会严重下降.第2种和第3种方法在运算量增加不多的情况下性能比第1种方法有所改善,尤其是当信噪比较小时.理论分析和计算机仿真结果表明这3种方法是有效的.

Separation of Coherent Signals through Orthogonalization Algorithms Based on Spatial Smoothing

The orthogonalization super-resolution algorithm exibits good performance when signal-to-noise ratio (SNR) is large and has small computation load. It is well known that the orthogonalization algorithm is based on the signal subspace to resolve targets and it fails to work when interfering signals are coherent. The approach of spatial smoothing has been applied to adaptive arrays to separate coherent signals. In this paper, three improved orthogonalization algorithms based on spatial smoothing are proposed and computer simulation results are given. The first method has low computational complexity but yields significant degradation in its performance when SNR decreases. Under the condition of increasing not too much computations, the second and the third method can get better performance than the first especially when SNR is small. Theoretical analysis and computer simulation results show that all the three methods are effective.