摘要
米波雷达具有很好的反隐身性能。多输入多输出(MIMO)雷达的波形分集具有高自由度特点,使MIMO雷达在检测和参数估计等方面具有更多优势,故米波MIMO雷达受到广泛研究。而测高是米波MIMO雷达最重要的问题之一。针对米波MIMO雷达测高问题,最大似然和广义多重信号分类方法是米波MIMO阵列雷达测高方法行之有效的算法,但其计算量大,工程中难以接受。该文提出一种基于块正交匹配追踪(BOMP)预处理的方法来降低计算量。首先对MIMO阵列接收数据稀疏化处理,然后通过数学操作将其变形至适合于BOMP算法的信号模型,然后利用粗栅格得到角度粗估计。并以此为初始值中心,取MIMO雷达波束宽度作为搜索范围。仿真结果表明该算法能有效降低搜索类测高算法的计算量。
Meter-wave radar has good anti-stealth performance.The waveform diversity of Multiple-Input Multiple-Output(MIMO)radar can result in a higher degree of freedom,which makes MIMO radar more advantageous in detection and parameter estimation.Therefore,meter-wave MIMO radar has been widely studied.The radar height measurement is one of the most important research problems of the meter-wave MIMO radar.The maximum likelihood and generalized multiple signal classification algorithms are effective for measuring the radar height.However,they feature heavy computation complexity.In this paper,a preprocessing method based on Block Orthogonal Matching Pursuit(BOMP)is proposed to reduce the computation.First,the received data of MIMO array are sparse-processed,and then,using a mathematical operation,they are transformed into a signal model suitable for the BOMP algorithm;then coarse angle estimation is obtained using a large search grid.The coarse angle estimation is taken as the initial value,and the MIMO radar beam width as the search range.The simulation results show that the proposed algorithm can effectively reduce the computation of the search-type height measurement algorithm.
作者
郑桂妹
宋玉伟
胡国平
李槟槟
张栋
ZHENG Guimei;SONG Yuwei;HU Guoping;LI Binbin;ZHANG Dong(Air and Missile Defense College,Air Force Engineering University,Xi’an 710051,China;Air Force Early Warning Academy,Wuhan 430019,China;PLA 66135,Beijing 100041,China)
出处
《雷达学报（中英文）》
CSCD
北大核心
2020年第5期908-915,共8页
Journal of Radars
基金
陕西省青年托举人才项目(20180109)
国家自然科学基金面上项目(61871395,61971438)
陕西省自然科学基金面上项目(2019JM-155,2020JM-345)。
关键词
米波多输入多输出雷达
测高
块正交匹配追踪
最大似然
广义多重信号分类
Meter wave Multiple-Input Multiple-Output(MIMO)radar
Height measurement
Block Orthogonal Matching Pursuit(BOMP)
Maximum likelihood
Generalized MUltiple SIgnal Classification(MUSIC)
