非理想检测下多雷达网络节点选择与辐射资源联合优化分配算法
TN957; 该文针对分布式相控阵多雷达网络的多目标跟踪场景,研究非理想检测条件下的节点选择与辐射资源联合优化分配算法.首先,根据分布式相控阵多雷达网络构成、目标运动模型、雷达量测模型以及雷达节点检测情况,推导非理想检测下以雷达节点选择、辐射功率和信号带宽为变量的贝叶斯克拉默-拉奥下界(BCRLB)闭式解析表达式,并以此作为多目标跟踪精度衡量指标.在此基础上,以最小化系统各雷达节点对所有目标的总辐射功率为优化目标,以满足目标跟踪精度门限以及给定的系统射频辐射资源限制为约束条件,建立非理想检测条件下多雷达网络节点选择与辐射资源联合优化分配模型,对各时刻雷达节点选择、辐射功率和信号带宽等参数进行联...
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| Published in | 雷达学报 Vol. 13; no. 3; pp. 565 - 583 |
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| Main Authors | , , , , |
| Format | Journal Article |
| Language | Chinese |
| Published |
南京航空航天大学雷达成像与微波光子技术教育部重点实验室 南京 210016%西安电子科技大学雷达信号处理国家重点实验室 西安 710071%北京控制与电子技术研究所 北京 100045
01.06.2024
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| Subjects | |
| Online Access | Get full text |
| ISSN | 2095-283X |
| DOI | 10.12000/JR23081 |
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| Abstract | TN957; 该文针对分布式相控阵多雷达网络的多目标跟踪场景,研究非理想检测条件下的节点选择与辐射资源联合优化分配算法.首先,根据分布式相控阵多雷达网络构成、目标运动模型、雷达量测模型以及雷达节点检测情况,推导非理想检测下以雷达节点选择、辐射功率和信号带宽为变量的贝叶斯克拉默-拉奥下界(BCRLB)闭式解析表达式,并以此作为多目标跟踪精度衡量指标.在此基础上,以最小化系统各雷达节点对所有目标的总辐射功率为优化目标,以满足目标跟踪精度门限以及给定的系统射频辐射资源限制为约束条件,建立非理想检测条件下多雷达网络节点选择与辐射资源联合优化分配模型,对各时刻雷达节点选择、辐射功率和信号带宽等参数进行联合优化设计,以提升多雷达网络的射频隐身性能.最后,针对上述非线性、非凸优化问题,采用基于障碍函数法和循环最小化算法的4步分解算法进行求解.仿真结果表明,与现有算法相比,所提算法能在满足给定多目标跟踪精度的条件下有效降低分布式相控阵多雷达网络的总辐射功率,至少降低了约32.3%,从而提升其射频隐身性能. |
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| AbstractList | TN957; 该文针对分布式相控阵多雷达网络的多目标跟踪场景,研究非理想检测条件下的节点选择与辐射资源联合优化分配算法.首先,根据分布式相控阵多雷达网络构成、目标运动模型、雷达量测模型以及雷达节点检测情况,推导非理想检测下以雷达节点选择、辐射功率和信号带宽为变量的贝叶斯克拉默-拉奥下界(BCRLB)闭式解析表达式,并以此作为多目标跟踪精度衡量指标.在此基础上,以最小化系统各雷达节点对所有目标的总辐射功率为优化目标,以满足目标跟踪精度门限以及给定的系统射频辐射资源限制为约束条件,建立非理想检测条件下多雷达网络节点选择与辐射资源联合优化分配模型,对各时刻雷达节点选择、辐射功率和信号带宽等参数进行联合优化设计,以提升多雷达网络的射频隐身性能.最后,针对上述非线性、非凸优化问题,采用基于障碍函数法和循环最小化算法的4步分解算法进行求解.仿真结果表明,与现有算法相比,所提算法能在满足给定多目标跟踪精度的条件下有效降低分布式相控阵多雷达网络的总辐射功率,至少降低了约32.3%,从而提升其射频隐身性能. |
| Abstract_FL | In this study,a collaborative radar selection and transmit resource allocation strategy is proposed for multitarget tracking applications in multiple distributed phased array radar networks with imperfect detection performance.The closed-form expression for the Bayesian Cramér-Rao Lower Bound(BCRLB)with imperfect detection performance is obtained and adopted as the criterion function to characterize the precision of target state estimates.The key concept of the developed strategy is to collaboratively adjust the radar node selection,transmitted power,and effective bandwidth allocation of multiple distributed phased array radar networks to minimize the total transmit power consumption in an imperfect detection environment.This will be achieved under the constraints of the predetermined tracking accuracy requirements of multiple targets and several illumination resource budgets to improve its radio frequency stealth performance.The results revealed that the formulated problem is a mixed-integer programming,nonlinear,and nonconvex optimization model.By incorporating the barrier function approach and cyclic minimization technique,an efficient four-step-based solution methodology is proposed to solve the resulting optimization problem.The numerical simulation examples demonstrate that the proposed strategy can effectively reduce the total power consumption of multiple distributed phased array radar networks by at least 32.3%and improve its radio frequency stealth performance while meeting the given multitarget tracking accuracy requirements compared with other existing algorithms. |
| Author | 严俊坤 唐志诚 王子微 时晨光 周建江 |
| AuthorAffiliation | 南京航空航天大学雷达成像与微波光子技术教育部重点实验室 南京 210016%西安电子科技大学雷达信号处理国家重点实验室 西安 710071%北京控制与电子技术研究所 北京 100045 |
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| Author_FL | WANG Ziwei SHI Chenguang ZHOU Jianjiang YAN Junkun TANG Zhicheng |
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| DocumentTitle_FL | Joint Collaborative Radar Selection and Transmit Resource Allocation in Multiple Distributed Radar Networks with Imperfect Detection Performance |
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| Keywords | Imperfect detection 分布式多雷达网络 非理想检测 贝叶斯克拉默-拉奥下界 Multitarget tracking Bayesian Cramér-Rao Lower Bound(BCRLB) 雷达资源分配 多目标跟踪 Radar resource allocation Multiple distributed radar networks |
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| PublicationTitle | 雷达学报 |
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| Publisher | 南京航空航天大学雷达成像与微波光子技术教育部重点实验室 南京 210016%西安电子科技大学雷达信号处理国家重点实验室 西安 710071%北京控制与电子技术研究所 北京 100045 |
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| Snippet | TN957; 该文针对分布式相控阵多雷达网络的多目标跟踪场景,研究非理想检测条件下的节点选择与辐射资源联合优化分配算法.首先,根据分布式相控阵多雷达网络构成、目标运动模... |
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| Title | 非理想检测下多雷达网络节点选择与辐射资源联合优化分配算法 |
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