基于最小方差谱估计的循环平稳信号到达角估计方法

Direction-of-Arrival Estimation Method for Cyclostationary Signals Using the Minimum-Variance Spectral Estimate

文章提出了基于最小方差谱估计的多循环频率到达角估计方法.通过对指数函数进行Jacobi-Anger展开,将目标方向矩阵近似分解为两个独立矩阵相乘的形式,并构造相应的变换矩阵,将多个不同循环频率处阵列输出信号循环相关函数矩阵进行叠加,再利用最小方差谱估计方法实现对目标到达角的估计.新方法克服了已有基于信号循环平稳特性估计方法只利用信号单个循环频率信息的不足.仿真结果证实了新方法的有效性,同时也证实该方法确实具有较单循环频率SC-SSF方法和传统宽带聚焦方法更好的估计性能.

Suffering from the exploitation of the cyclostationary property at only one cycle frequency, the existing SC-SSF algorithm can not reach the best performance. By using the minimum-variance spectral estimate method, a new approach exploiting the cyclostationary property at multiple cycle frequencies is discussed in the paper. Firstly, by using the Jacobi-Anger expansion, the direction matrix can be divided into two parts. Secondly, the transforming matrix can be formed according to the two parts.Thirdly, the minimumvariance spectral estimate method is used to estimate the direction. Simulation results demonstrate the effectiveness and superiority of the new approach over the single-cycle SC-SSF algorithm and the conventional focusing wansform algorithm for wide-band singals.