基于解卷积的自适应空间谱估计方法  

An Adaptive Spatial Spectral Estimation Method Based on Deconvolution

作　　者：邱岚[1] 谢于晨[1] QIU Lan;XIE Yuchen(Department of Information Engineering, Jiangxi University of Technology, Nanchang 330098, China)

机构地区：[1]江西科技学院信息工程学院,江西南昌330098

出　　处：《探测与控制学报》2021年第1期61-67,共7页Journal of Detection & Control

基　　金：江西省教育厅科学技术研究项目资助(GJJ180983)。

摘　　要：针对自适应空间谱估计方法背景级对目标空间方位角分布值估计的影响问题,提出了基于解卷积的自适应空间谱估计方法。该方法首先在自适应空间谱估计方法输出空间谱基础上,采用类狄利克函数和空间谱归一化平均背景级实现点扩展函数设计;然后利用点扩展函数和图像复原中Richardson-Lucy迭代方法对自适应空间谱估计结果进行解卷积,降低背景级及其对目标空间方位角分布值估计的影响。数值仿真和实测数据处理结果表明:该方法作为一种后置处理方法,继承了自适应空间谱估计方法高分辨估计能力,空间谱峰值更加“尖锐”;信号谱级比较低时,通过增加迭代次数使其输出空间谱背景级远低于自适应空间谱方法和分子阵处理方法,具有更好的目标空间方位角分布估计能力。For the problem of influence of background level on estimating target spatial azimuth distribution value,an adaptive spatial spectrum estimation method based on deconvolution was proposed.Firstly,based on output spatial spectrum of adaptive spatial spectrum estimation method,the point scattering function was designed with Dirichlet-like function and normalized average background level of spatial spectrum.Then,the output results of adaptive spatial spectrum estimation method were deconvolution with point scattering function and Richardson-Lucy iterative method of image restoration,and the background level and its influence on estimating target spatial azimuth distribution value was reduced.The results of numerical simulation and measured data showed that,this method was a post-processing method,inherited the high resolution performance of the adaptive spatial spectrum estimation method,which had more sharp peak value,and could output lower background level via increasing the number of iteration than adaptive spatial spectrum estimation method and sub-array method,and had better performance of estimating target spatial azimuth distribution value.

关 键 词：自适应空间谱估计 空间方位角分布值 后置处理 解卷积 背景级 

分 类 号：TN912[电子电信—通信与信息系统]