胡子英,
龚琳舒
哈尔滨工程大学自动化学院??哈尔滨??150001
基金项目:国家自然科学基金(61571148, 61871143)，中央高校基本科研基金(HEUCFG201823, HEUCFP201836)，哈尔滨应用技术研发项目(2017R-AQXJ095)
详细信息
作者简介:王伟：男，1979年生，教授，研究方向为MIMO雷达信号处理、组合导航系统和无线电导航
胡子英：男，1994年生，博士生，研究方向为MIMO雷达信号处理及稀疏成像技术
龚琳舒：女，1993年生，硕士生，研究方向为MIMO雷达信号处理及角度估计算法
通讯作者:王伟 wangwei407@hrbeu.edu.cn
中图分类号:TN958计量
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被引次数:0
出版历程
收稿日期:2018-02-02
修回日期:2019-03-22
网络出版日期:2019-03-27
刊出日期:2019-06-01
Adaptive Off-grid Calibration Method for MIMO Radar 3D Imaging
Wei WANG,,Ziying HU,
Linshu GONG
Harbin Engineering University Automation Department, Harbin 150001, China
Funds:The National Natural Science Foundation (61571148, 61871143), The Fundamental Research for the Central University (HEUCFG201823, HEUCFP201836), The Research and Development Project of Application Technology in Harbin (2017R-AQXJ095)
摘要
摘要:在压缩感知成像算法中，真实目标点一般不会恰好落在预先划定的网格点上，这种网格偏离(Off-grid)问题会带来真实回波与测量矩阵之间的失配，严重降低雷达成像的性能。针对多输入多输出(MIMO)雷达3维成像的网格失配问题，该文提出一种自适应的Off-grid校正方法，基于Off-grid目标的稀疏回波模型构造贝叶斯概率密度函数，采用最大后验概率(MAP)方法求解含有失配偏差的稀疏像。与传统方法相比，该方法可以充分利用失配参数的先验信息，自适应地更新参数，降低了失配误差的影响，并能实现对稀疏目标和噪声功率的高精度估计。仿真结果表明，该方法可以有效地实现对网格失配的优化，具有精确且稳定的成像性能。
关键词:MIMO雷达/
Off-grid校正/
3维稀疏成像/
最大后验概率
Abstract:In Compressive Sensing (CS) imaging algorithms, the true targets usually can not locate on the pre-defined grids exactly. Such Off-grid problems result in mismatch between true echo and measurement matrix, which seriously degrades the performance of radar imaging. An adaptive calibration method is proposed to solve the off-grid problems in MIMO radar Three-Dimensional (3D) imaging. Bayesian probability density functions can be constructed based on the sparse echo model of Off-grid targets, and the Maximum A Posteriori (MAP) method is used to obtain sparse imaging with mismatch errors. Compared with the traditional methods, the proposed method can make full use of mismatch parameters’ priori information and adaptively update the parameters, which can reduce the influence of mismatch errors, and achieve high-precision estimation for sparse targets and noise power. Finally, the simulation results confirm that the proposed method can effectively optimize mismatch errors with accurate and stable imaging performance.
Key words:MIMO radar/
Off-grid calibration/
Three-dimensional sparse imaging/
Maximum A Posteriori (MAP)
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