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Finite sensor selection algorithm in distributed MIMO radar for joint target tracking and detection 认领 引用 被引量：7
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作者 ZHANG Haowei XIE Junwei +2 位作者 GE Jiaang ZHANG Zhaojian LU Wenlong 《Journal of Systems Engineering and Electronics》 SCIE CSCD 2020年第2期290-302,共13页
Due to the requirement of anti-interception and the limitation of processing capability of the fusion center, the subarray selection is very important for the distributed multiple-input multiple-output(MIMO) radar sys... Due to the requirement of anti-interception and the limitation of processing capability of the fusion center, the subarray selection is very important for the distributed multiple-input multiple-output(MIMO) radar system, especially in the hostile environment. In such conditions, an efficient subarray selection strategy is proposed for MIMO radar performing tasks of target tracking and detection. The goal of the proposed strategy is to minimize the worst-case predicted posterior Cramer-Rao lower bound(PCRLB) while maximizing the detection probability for a certain region. It is shown that the subarray selection problem is NP-hard, and a modified particle swarm optimization(MPSO) algorithm is developed as the solution strategy. A large number of simulations verify that the MPSO can provide close performance to the exhaustive search(ES) algorithm. Furthermore, the MPSO has the advantages of simpler structure and lower computational complexity than the multi-start local search algorithm. 展开更多
关键词 distributed multiple-input multiple-output(MIMO)radar subarray selection target tracking target detection particle swarm optimization(PSO)
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Modified OMP method for multi-target parameter estimation in frequency-agile distributed MIMO radar 认领 引用 被引量：3
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作者 XING Wenge ZHOU Chuanrui WANG Chunlei 《Journal of Systems Engineering and Electronics》 SCIE CSCD 2022年第5期1089-1094,共6页
Introducing frequency agility into a distributed multipleinput multiple-output(MIMO)radar can significantly enhance its anti-jamming ability.However,it would cause the sidelobe pedestal problem in multi-target paramet... Introducing frequency agility into a distributed multipleinput multiple-output(MIMO)radar can significantly enhance its anti-jamming ability.However,it would cause the sidelobe pedestal problem in multi-target parameter estimation.Sparse recovery is an effective way to address this problem,but it cannot be directly utilized for multi-target parameter estimation in frequency-agile distributed MIMO radars due to spatial diversity.In this paper,we propose an algorithm for multi-target parameter estimation according to the signal model of frequency-agile distributed MIMO radars,by modifying the orthogonal matching pursuit(OMP)algorithm.The effectiveness of the proposed method is then verified by simulation results. 展开更多
关键词 distributed multiple-input multiple-output(MIMO)radar multi-target parameter estimation frequency agility modified orthogonal matching pursuit(OMP)method
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Joint resource allocation scheme for target tracking in distributed MIMO radar systems 认领 引用 被引量：2
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作者 ZHENG Na’e SUN Yang +1 位作者 SONG Xiyu CHEN Song 《Journal of Systems Engineering and Electronics》 SCIE CSCD 2019年第4期709-719,共11页
A joint resource allocation scheme concerned with the sensor subset,power and bandwidth for range-only target tracking in multiple-input multiple-output(MIMO)radar systems is proposed.By selecting an optimal subset of... A joint resource allocation scheme concerned with the sensor subset,power and bandwidth for range-only target tracking in multiple-input multiple-output(MIMO)radar systems is proposed.By selecting an optimal subset of sensors with the predetermined size and implementing the power allocation and bandwidth strategies among them,this algorithm can help achieving a better performance within the same resource constraints.Firstly,the Bayesian Cramer-Rao bound(BCRB)is derived from it.Secondly,a criterion for minimizing the BCRB at the target location among all targets tracking in a certain range is derived.Thirdly,the optimization problem involved with three variable vectors is formulated,which can be simplified by deriving the relationship between the optimal power allocation vector and the bandwidth allocation vector.Then,the simplified optimization problem is solved by the cyclic minimization algorithm incorporated with the sequential parametric convex approximation(SPCA)algorithm.Finally,the validity of the proposed method is demonstrated with simulation results. 展开更多
关键词 distributed multiple-input multiple-output(MIMO)radar target tracking joint resource alloction sensor subset selection(SSS) optimal power and bandwidth allocation(OPBA)
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Adapitive waveform design for distributed OFDM MIMO radar system in multi-target scenario 认领 引用 被引量：4
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作者 Haitao WANG Junpeng YU +1 位作者 Wenzhen YU De BEN 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2018年第3期567-574,共8页
In order to improve detection and estimation performance of distributed OrthogonalFrequency-Division Multiplexing（OFDM） Multiple-Input Multiple-Output（MIMO） radar system in multi-target scene, we propose a novel a... In order to improve detection and estimation performance of distributed OrthogonalFrequency-Division Multiplexing（OFDM） Multiple-Input Multiple-Output（MIMO） radar system in multi-target scene, we propose a novel approach of Adaptive Waveform Design（AWD） based on a constrained Multi-Objective Optimization（MOO）. The sparse measurement model of this radar system is derived, and the method based on decomposed Dantzig selectors is applied for the sparse recovery according to the block structures of the sparse vector and the system matrix. An AWD approach is proposed, which optimizes two objective functions, namely minimizing the upper bound of the recovery error and maximizing the weakest-target return, by adjusting the complex weights of the emitting waveform amplitudes. Several numerical simulations are provided and their results show that the detection and estimation performance of the radar system is improved significantly when this MOO-based AWD approach is applied to the distributed OFDM MIMO radar system. Especially, we verify the effectiveness of our AWD approach when the available samples are reduced severally and the technique of compressed sensing is introduced. 展开更多
关键词 Adaptive waveform design Compressed sensing Distributed radar Multi-objective optimization Multiple-input multipleoutput Orthogonal-frequencydivision multiplexing
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基于双站距离的分布式MIMO雷达鲁棒目标定位方法研究 认领 引用
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作者 陶思瑜 文贡坚 +1 位作者 宋海波 周恩吉 《雷达科学与技术》 北大核心 2026年第3期248-257,270,共10页
在分布式多输入多输出(Multiple-Input Multiple-Output,MIMO)雷达中,部分通道产生的低质量双站距离(Bistatic Range,BR)测量值会显著降低常规间接法的目标定位精度。针对这一问题,本文基于Tukey损失函数构建鲁棒估计器,并采用迭代重加... 在分布式多输入多输出(Multiple-Input Multiple-Output,MIMO)雷达中,部分通道产生的低质量双站距离(Bistatic Range,BR)测量值会显著降低常规间接法的目标定位精度。针对这一问题,本文基于Tukey损失函数构建鲁棒估计器,并采用迭代重加权非线性最小二乘(Iterative Reweighted Nonlinear Least Squares,IRNLS)法进行高效求解。该方法可作为一种通用的后处理模块,有效提升现有间接法在存在异常值场景下的目标定位性能。此外,通过大量的仿真实验探究了该鲁棒估计器与不同现有间接法结合后,在不同信噪比下的最优边界参数。进一步地,建立了最优边界参数与信噪比之间的近似关系模型。最后,本文还定量分析了引入该鲁棒估计器所带来的计算复杂度增量问题。 展开更多
关键词 分布式多输入多输出雷达 双站距离 Tukey损失函数 鲁棒定位 迭代重加权非线性最小二乘法
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