非高斯噪声环境下分布式阵列DOA估计算法  

DOA estimation for distributed arrays in non-Gaussian noise environment

作　　者：李森[1] 吕梦然 母采凤 LI Sen;LV Meng-ran;MU Cai-feng(Information Science and Technology College,Dalian Maritime University,Dalian 116026,China)

机构地区：[1]大连海事大学信息科学技术学院,辽宁大连116026

出　　处：《大连海事大学学报》2022年第3期87-94,共8页Journal of Dalian Maritime University

基　　金：国家自然科学基金面上项目(61971083);中央高校基本科研业务费专项资金资助项目(3132019341)。

摘　　要：针对非高斯脉冲噪声环境下分布式阵列波达方向(DOA)估计算法性能退化问题,以Alpha稳定分布为脉冲噪声模型,首先,利用分数低阶变换和压缩变换两种非线性变换方法对阵列接收信号进行预处理以有效抑制脉冲噪声;然后,基于预处理后数据的协方差矩阵,提出两种鲁棒的双尺度酉ESPRIT(U-DS-ESPRIT)算法;最后,对分布式阵列在Alpha稳定分布脉冲噪声环境下DOA估计的克拉美罗界(CRB)进行分析。仿真结果表明,在脉冲噪声环境下,两种鲁棒双尺度酉ESPRIT算法的估计性能明显好于传统基于二阶协方差矩阵的双尺度酉ESPRIT算法,且基于压缩变换的双尺度酉ESPRIT算法的估计性能更接近于CRB。Aiming at the performance degradation of distributed array direction of arrival(DOA) estimation algorithm in non-Gaussian impulse noise environment, Alpha stable distribution was taken as impulse noise model. Firstly, two nonlinear transform methods, fractional low order transform and compression transform, were used to preprocess the array received signal to effectively suppress impulse noise. Then, two robust dual-size unitary ESPRIT(U-DS-ESPRIT) algorithms were proposed based on the covariance matrix of the preprocessed data. Finally, the Cramer Rao bound(CRB) of DOA estimation for distributed arrays in Alpha stable distributed impulse noise environment was analyzed. Simulation results show that in impulse noise environment, the estimation performance of the two robust U-DS-ESPRIT algorithms proposed in this paper is significantly better than that of the U-DS-ESPRIT algorithm based on traditional covariance matrix, and the estimation performance of the U-DS-ESPRIT algorithm based on compression transformation is much closer to CRB.

关 键 词：ALPHA稳定分布 分布式阵列 DOA估计 非线性变换 克拉美罗界(CRB) 

分 类 号：TN911.7[电子电信—通信与信息系统]