摘要
针对杂波背景下提升认知MIMO雷达的多运动目标检测问题,基于双互信息准则构建多目标优化模型,结合运动目标冲激响应(TIR)线性变化问题,采用卡尔曼滤波算法估计下一时刻TIR,并采用注水算法求解最优频域波形,然后利用遗传算法合成认知MIMO雷达的时域波形。经仿真验证,所用算法能满足认知MIMO雷达观测多个目标发射波形设计的需要,实现了对运动目标冲激响应的有效估计,相比于传统的固定信号,能够提升多运动目标检测性能。
In order to solve the problem of boosting cognitive MIMO radar for multiple moving target detection in cluttered backgrounds,this paper constructs a multi-target optimization model based on the dual mutual information criterion,takes into account the problem of linear variation of the motion target impulse response(TIR),estimates the TIR at the next moment by using Kalman filtering algorithm.Then the optimal frequency-domain waveforms by using the water-filling algorithm is adopted,and the time-domain waveforms of the cognitive MIMO radar by using the genetic algorithm is synthesized.With simulation verification,the algorithm can meet the needs of MIMO radar to observe multiple targets and realize the effective estimation of the impulse response of moving targets,which can improve the performance of multiple moving targets detection compared with the traditional fixed signal.
作者
沈廷立
张云雷
卢建斌
余国华
SHEN Tingli;ZHANG Yunlei;LU Jianbin;YU Guohua(College of Electronic Engineering,Naval University of Engineering,Wuhan 430033,China;Unit 95780 of PLA,Ningbo 315000,China)
出处
《指挥控制与仿真》
2025年第2期54-62,共9页
Command Control & Simulation
基金
海军工程大学自主研发项目(2022503040)。
关键词
认知MIMO雷达
互信息
多目标检测
卡尔曼滤波
cognitive MIMO radar
mutual information
multi-target detection
Kalman filtering
