严俊坤,,
王鹏辉,
刘宏伟
西安电子科技大学雷达信号处理国家重点实验室 西安 710071
基金项目:国家自然科学基金(62071345)，国家****科学基金(61525105)，高等学校学科创新引智计划(111 project, B18039)，陕西省自然科学基金(2020JQ-297)，中国航空科学基金(201920081002)，雷达信号处理国家重点实验室基金(61424010406)
详细信息
作者简介:戴金辉：男，1993年生，博士生，研究方向为网络化雷达资源分配、目标跟踪
严俊坤：男，1987年生，副教授，博士生导师，研究方向为认知雷达、目标跟踪与定位、协同探测等
王鹏辉：男，1984年生，副教授，硕士生导师，研究方向为雷达自动目标识别、机器学习与模式识别等
刘宏伟：男，1971年生，教授，博士生导师，研究方向为网络化雷达、宽带雷达信号处理、雷达自动目标识别、自适应和阵列信号处理及目标检测等
通讯作者:严俊坤 jkyan@xidian.edu.cn
中图分类号:TN958计量
文章访问数:433
HTML全文浏览量:225
PDF下载量:42
被引次数:0
出版历程
收稿日期:2020-10-12
修回日期:2021-01-02
网络出版日期:2021-01-07
刊出日期:2021-09-16
Target Capacity Based Power Allocation Scheme in Radar Network
Jinhui DAI,Junkun YAN,,
Penghui WANG,
Hongwei LIU
National Laboratory of Radar Signal Processing, Xidian University, Xi’an 710071, China
Funds:The National Natural Science Foundation of China (62071345), The National Science Fund for Distinguished Yong Scholars (61525105), The Fund for Foreign Scholars in University Research and Teaching Programs (111 project, B18039), The Natural Science Foundation of Shaanxi Province (2020JQ-297), The Aeronautical Science Foundation of China (201920081002), The Foundation of National Radar Signal Processing Laboratory (61424010406)
摘要
摘要:针对现有网络化雷达功率资源利用率低的问题，该文提出一种基于目标容量的功率分配(TC-PA)方案以提升保精度跟踪目标个数。TC-PA方案首先将网络化雷达功率分配模型制定为非光滑非凸优化问题；而后引入Sigmoid函数将原问题松弛为光滑非凸优化问题；最后运用近端非精确增广拉格朗日乘子法(PI-ALMM)对松弛后的非凸问题进行求解。仿真结果表明，PI-ALMM对于求解线性约束非凸优化问题可以较快地收敛到一个稳态点。另外，相比传统功率均分方法和遗传算法，所提TC-PA方案可以最大限度地提升目标容量。
关键词:网络化雷达/
多目标跟踪/
资源分配/
非凸优化
Abstract:In view of the fact that low power resource utilization rate exists in radar network, a Target Capacity based Power Allocation (TC-PA) scheme is proposed to increase the number of the targets that satisfy tracking accuracy requirements. Firstly, this scheme formulates the power allocation model of radar network as a non-smooth and non-convex optimization problem. Then the original problem is relaxed into a smooth and non-convex problem through introducing Sigmoid function. Finally, the relaxed non-convex problem is solved by utilizing the Proximal Inexact Augmented Lagrangian Multiplier Method (PI-ALMM). Simulation results show that the PI-ALMM can quickly converge to a stationary point for solving the non-convex optimization problem with linear constraints. Moreover, the proposed TC-PA scheme outperforms the traditional uniform power allocation method and genetic algorithm, in terms of target capacity.
Key words:Radar network/
Multiple target tracking/
Resource allocation/
Non-convex optimization
PDF全文下载地址:
https://jeit.ac.cn/article/exportPdf?id=4daa16c1-84e9-4915-af7f-b90668d2b7ac
