应用分数低阶循环相关估计单电磁矢量传感器的波达方向和极化参数

提出了一种在α和高斯混合噪声以及循环平稳干扰并存背景下基于分数低阶循环相关(FLOCC)联合估计单电磁矢量传感器波达方向(DOA)和极化参数的多重信号分类(MUSIC)方法。该方法利用信号的循环平稳特性,采用分数低阶循环相关函数抑制α和高斯混合噪声以及循环平稳干扰信号;然后利用MUSIC方法对单电磁矢量传感器的DOA和极化参数进行联合估计,并利用DOA参数与极化参数的相互独立性,将传统MUSIC方法的四维搜索简化为两次二维搜索,从而有效地减少该算法的计算量。对所提算法与基于分数低阶矩的MUSIC算法进行了实验对比。结果显示:提出的方法可充分地抑制与待测信号循环频率相异的任意循环平稳干扰信号;在α和高斯混合信噪比为0dB,信干比为3dB时,估计得到的DOA和极化参数的均方根误差分别为0.3°和0.7°,明显优于基于分数低阶矩的MUSIC方法。

Estimation of DOA and polarition parameters for single electromagnetic vector sensor based on FLOCC

A Fractional Lower Order Cyclic Correlation (FLOCC)-based MUSIC method was proposed for estimation of the Direction of Arrival (DOA) and polarization parameters for a single electromagnetic vector sensor in mixed α and Gaussian noises and cycle stable interference signals. On the basis of the cyclic stability of signals, the FLOCC function was used to suppress the cyclic stationary disturbance signal and the mixed α and Gaussian noises. Then, MUSIC method was used to estimate the DOA and polarization parameters of the single electromagnetic vector sensor, and the mutual independence between the DOA parameters and the polarization parameters was used to simplify the four dimensional search of traditional MUSIC method into two times of two dimensional search to reduce the calculated amount of the algorithm. The proposed algorithm was compared with the traditional MUSIC method based on fractional lower order moment in the simulation. The results show that the proposed method can sufficiently suppress any of cyclic stationary disturbances with different cycle frequencies. When the mixed signal to noise ratio of α and Gaussian noises is 0 dB and the signal to interference ratio is 3 dB, the root mean square error of the estimation of DOA and polarization parameters is 0.3° and 0.7°, respectively, being superior to that of the traditional MUSIC method.