丁琳涛,
汪飞,
周建江
南京航空航天大学雷达成像与微波光子教育部重点实验室 南京 210016
基金项目:国家自然科学基金(61801212)，国防科技创新特区资助，中国博士后科学基金面上项目(2019M650113)，江苏省自然科学基金青年基金项目(BK20180423)
详细信息
作者简介:时晨光：男，1989年生，副教授，博士，研究方向为飞行器射频隐身技术，组网雷达资源管理，多平台传感器协同等
丁琳涛：男，1997年生，硕士生，研究方向为组网雷达资源管理
汪飞：男，1976年生，副教授，博士，研究方向为飞行器射频隐身技术、雷达信号处理、阵列信号处理等
周建江：男，1962年生，教授，博士，研究方向为飞行器射频隐身技术、雷达目标特性分析、航空电子信息系统设计等
通讯作者:时晨光 scg_space@163.com
中图分类号:TN953计量
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被引次数:0
出版历程
收稿日期:2020-07-30
修回日期:2020-12-09
网络出版日期:2020-12-22
刊出日期:2021-03-22
Radio Frequency Stealth-based Optimal Radio Frequency Resource Allocation Algorithm for Multiple-target Tracking in Radar Network
Chenguang SHI,,Lintao DING,
Fei WANG,
Jianjiang ZHOU
Key Laboratory of Radar Imaging and Microwave Photonics, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China
Funds:The National Natural Science Foundation of China (61801212), The National Defense Science and Technology Innovation Special Zones, China Postdoctoral Science Foundation (2019M650113), The Natural Science Foundation of Jiangsu Province (BK20180423)
摘要
摘要:针对组网雷达系统多目标跟踪场景，该文提出一种面向射频(RF)隐身的组网雷达射频辐射资源优化分配算法。首先，采用目标跟踪误差的贝叶斯克拉美-罗下界(BCRLB)作为目标跟踪性能指标。其次，以各雷达照射目标的驻留时间资源和辐射功率资源加权和为优化目标，以BCRLB不大于给定目标跟踪精度阈值及系统射频辐射资源作为约束条件，建立了包含雷达节点分配方式、驻留时间和辐射功率3个优化变量的优化模型。然后，采用两步分解法对上述优化模型进行了求解，即先固定雷达节点选择，利用内点法对简化后的非凸非线性优化模型进行求解，之后再通过匈牙利算法确定最佳雷达节点分配方式。仿真结果表明，相较于辐射资源均匀分配算法，所提算法可以有效降低组网雷达的射频资源消耗，提升系统射频隐身性能。
关键词:射频隐身/
组网雷达/
多目标跟踪/
资源优化分配
Abstract:In the scenario of multi-target tracking by a radar network system, a Radio Frequency (RF) stealth-based optimal RF resource allocation algorithm in radar network is proposed. Firstly, the Bayesian Cramer-Rao Lower Bound (BCRLB) of target tracking error is used as the target tracking performance index. Secondly, the optimization model is established which includes three optimization variables: radar node selection, dwell time and radiation power. In this model, the objective function is the weighted sum of the dwell time resources and radiation power resources of each radar, the constraint condition can be conclude that the BCRLB must be less than the given threshold and the system RF radiation resources must be between the upper and lower limits. Then, the two-step decomposition method is used to solve the above optimization model. The radar node selection is fixed first, then the interior point method is used to solve the simplified non-convex nonlinear optimization model, and then the Hungarian algorithm is used to determine the best radar node selection mode. The simulation results show that compared with uniform resource allocation algorithm, the proposed algorithm can effectively reduce the RF resource consumption of the radar network and improve the RF stealth performance of the system.
Key words:Radio Frequency (RF) stealth/
Radar network/
Multi-target tracking/
Optimal resource allocation
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