摘要
实际阵列测向系统中往往存在幅相、互耦等多种误差,导致阵列测向性能出现严重恶化。为解决在低信噪比、小快拍、多种误差同时存在时的阵列测向失准问题,通过引入信号空域稀疏性,利用贝叶斯稀疏重构技术解决在幅相、互耦误差同时存在时的无源校正及阵列信号方位的联合估计问题,构建了误差存在时的接收信号的超完备模型,得到接收信号的后验概率密度函数。利用EM算法对概率密度函数进行迭代优化并对相应参数进行求解,同时还对阵列误差及信号方位的CRLB进行推导,实验仿真验证了所提方法的有效性。
In the actual array direction finding system, there are often a variety of errors such as amplitude and phase,mutual coupling, which lead to serious deterioration of array direction finding performance. In order to solve the problem of array direction finding misalignment in the presence of low signal-to-noise ratio, small snapshots and multiple errors,the spatial sparsity of signals were introduced, and Bayesian sparse reconstruction technology was used to solve the passive correction and joint estimation of array signal azimuth in the presence of amplitude-phase and mutual coupling errors.The over-complete model of the received signal with error was constructed, and the posterior probability density function of the received signal was obtained. The EM algorithm was used to iteratively optimize the probability density function to solve the corresponding parameters. At the same time, the CRLB of array error and signal azimuth was derived, and by experimental simulation verifies the effectiveness of the proposed method.
作者
王鼎
高卫港
吴志东
WANG Ding;GAO Weigang;WU Zhidong(Institute of Information System Engineering,Information Engineering University,Zhengzhou 450001,China)
出处
《通信学报》
EI
CSCD
北大核心
2022年第9期112-120,共9页
Journal on Communications
基金
国家自然科学基金资助项目(No.62171469,No.62071029)。
关键词
幅相误差
互耦误差
稀疏重构
波达方向估计
amplitude-phase error
mutual coupling error
sparse reconstruction
DOA estimation
