空-时相关高斯噪声中基于累积量的联合角度-频率估计算法

Cumulant-Based JAFE Algorithm in the Presence of Spatially and Temporally Correlated Gaussian Noise

提出一种基于累积量的联合角度-频率估计(CB-JAFE)的新算法,用于估计多个独立非高斯信号源的方位和频率参数.同利用空-时数据矩阵奇异值分解的现有联合角度-频率估计(JAFE)算法不同,所提出的算法利用空-时数据的4阶累积量,可有效地抑制具有未知相关结构的空域和时域相关的高斯噪声.仿真结果表明,所提出CB-JAFE算法是有效性的,而且性能上优于现有的JAFE算法.

A cumulant-based joint angle-frequency estimation （CB-JAFE） algorithm for independent non- Gaussian sources was proposed. The proposed algorithm, which employs the fourth-order cumulants of the spatio-temporal data, is applicable to the case of spatially and temporally correlated Gaussian noise with unknown correlation structure. Simulation results are carried out to show the effectiveness of the proposed algorithm and to compare it with the JAFE algorithm.