电子学报2016，Vol.44Issue(6)：1314-1321,8.DOI:10.3969/j.issn.0372-2112.2016.06.008
基于贝叶斯压缩感知的FD-MIMO雷达Off-Gri d目标稀疏成像
Bayesian Co mpressive Sensing-Based Sparse I maging for Off-Grid Target in Frequency Diverse MIMO Radar
摘要
Abstract
Conventional compressive sensing (CS)imaging methods rely on the assumption that all scatterers in the ima-ging scene are located exactly on the pre-defined grids.However,since the scatterers are distributed in a continuous scene,the off-grid problem inevitably exists,which makes basis mismatch between echo measurement and the assumed sensing matrix,and leads to considerable performance degradation by CS-based methods.Therefore,this paper investigates the sparse imaging for off-grid target in frequency diverse multiple-input multiple-output (FD-MIMO)radar.A sparse autofocus imaging method based on Bayesian compressive sensing (SAF-BCS)is proposed.It employs the technique of variational Bayesian inference to achieve the imaging of off-grid scatterres in light of the criterion of maximum a posteriori (MAP).Compared with the conventional sparse re-covery algorithms,the proposed method adequately utilizing the prior information of the target,is able to automatically tune pa-rameters,and thus can provide a better capability to correct the off-grid errors,and to estimate the noise power,etc.Simulation re-sults confirm that SAF-BCS is not sensitive to grid discretization,and has a robust imaging performance.关键词
贝叶斯压缩感知/FD-MIMO雷达/Off-grid目标/变分贝叶斯学习/稀疏自聚焦成像Key words
Bayesian compressive sensing/FD-MIMO radar/off-grid target/variational Bayesian inference/sparse autofocus imaging分类
电子信息工程引用本文复制引用
王天云,陆新飞,丁丽,尹治平,陈卫东..基于贝叶斯压缩感知的FD-MIMO雷达Off-Gri d目标稀疏成像[J].电子学报,2016,44(6):1314-1321,8.基金项目
国家自然科学基金（No．61172155，No．61401140，No．61403421）；国家863计划项目资助课题 （）
