摘要
在密集杂波环境中,将目标检测与跟踪视为两个独立的阶段的传统信号处理方式以及辐射资源优化算法难以适用。而利用检测跟踪一体化的闭环回路,合理优化检测门限和射频辐射资源,可以进一步提升组网雷达的射频隐身性能。于是,本文提出了目标检测跟踪场景下组网雷达检测门限与驻留时间联合优化算法。采用检测跟踪一体化结构,通过将跟踪器的信息反馈至贝叶斯检测器,自适应调整检测门限,进而提升对目标的跟踪精度。首先,推导了波门内平均检测概率作为衡量目标检测性能的衡量指标,并引入了信息衰减因子,推导了预测贝叶斯克拉美-罗下界作为目标跟踪性能的衡量指标。其次,以满足一定的目标检测性能和跟踪性能需求以及有限的组网雷达驻留时间资源为约束条件,建立目标检测跟踪场景下组网雷达检测门限与驻留时间联合优化模型,通过联合优化各部雷达的检测门限与驻留时间,最小化组网雷达的总驻留时间资源消耗,提升其射频隐身性能。在此基础上,结合序贯二次规划算法和改进的概率数据互联算法对上述问题进行求解。仿真结果表明,与其他算法相比,所提算法能够使组网雷达在满足一定的目标检测跟踪性能的情况下,消耗最少的驻留时间资源,具有最优越的射频隐身性能。
In dense clutter environment,the traditional signal processing methods and radiation resource optimization algo⁃rithms are hard to be applied when target detection and tracking are regarded as two independent stages.By using the closed-loop structure of detection and tracking integration,the detection threshold and radio frequency radiation resource can be reasonably optimized to further improve the radio frequency stealth performance.Therefore,this paper proposes a joint optimization algorithm of detection threshold and dwell time allocation for target detection and tracking in radar net⁃work.By integrating the detection and tracking,and introducing the feedback of the tracker information into the Bayes de⁃tector to adaptively adjust the detection threshold,the tracking accuracy of the target can be improved.Firstly,the aver⁃age detection probability in associated gate is derived as the metric for target detection performance.With the information reduction factor,the predicted Bayesian Cramér-Rao Lower Bound is derived as the metric for target tracking perfor⁃mance.Secondly,based on the constraints of certain target detection and tracking performance requirements,limited dwell time resource,the joint optimization model of detection threshold and dwell time allocation for target detection and tracking in radar network is established.By optimizing the detection threshold and dwell time of each radar,the total dwell time resource consumption of radar network is minimized to improve its radio frequency stealth performance.Furthermore,the problem is solved by combining sequential quadratic programming algorithm and improved probabilistic data associa⁃tion algorithm.The simulation results show that compared with other algorithms,the proposed algorithm can consume the least dwell time resource to meet the certain target detection and tracking performance requirements and achieve the best radio frequency stealth performance.
作者
时晨光
石兆
周建江
SHI Chenguang;SHI Zhao;ZHOU Jianjiang(Key Laboratory of Radar Imaging and Microwave Photonics,Ministry of Education,Nanjing University of Aeronautics and Astronautics,Nanjing,Jiangsu 211106,China)
出处
《信号处理》
CSCD
北大核心
2023年第7期1155-1164,共10页
Journal of Signal Processing
基金
国家自然科学基金面上项目(62271247)
装备预研重点实验室基金(6142401200402)
国防基础科研计划资助项目(JCKY2021210B004)
航空科学基金(20200020052002,20200020052005)
国防科技创新特区项目
南京航空航天大学前瞻布局科研专项资金
雷达成像与微波光子技术教育部重点实验室(南京航空航天大学)。
关键词
射频隐身
组网雷达
检测跟踪一体化
检测门限
驻留时间
radio frequency stealth
radar network
detection and tracking
detection probability
dwell time
作者简介
通讯作者:时晨光,男,1989年生,河南洛阳人。南京航空航天大学电子信息工程学院副教授,博士生导师,主要研究方向为飞行器射频隐身技术、组网雷达系统协同感知、多传感器信息融合与管理等。E-mail:scg_space@163.com;石兆,男,1999年生,陕西渭南人。南京航空航天大学电子信息工程学院硕士研究生,主要研究方向为飞行器射频隐身技术。E-mail:shizhao@nuaa.edu.cn;周建江,男,1962年生,江苏南通人。南京航空航天大学电子信息工程学院教授,博士生导师,主要研究方向为隐身技术、雷达目标特性分析与特征控制等。E-mail:zjjee@nuaa.edu.cn。
