多目标跟踪下的分布式MIMO雷达资源联合优化算法

宋喜玉; 任修坤; 郑娜娥; 田英华

doi:10.7652/xjtuxb201810015

您当前的位置：

首页 >

文章列表页 >

多目标跟踪下的分布式MIMO雷达资源联合优化算法

更新时间：2025-07-09

- 多目标跟踪下的分布式MIMO雷达资源联合优化算法
- A Joint Resource Optimization Algorithm of Distributed MIMO Radar Systems for Multiple Targets Tracking
- 西安交通大学学报 2018年52卷第10期页码：110-115+123
- 作者机构：
  
  战略支援部队信息工程大学,郑州,450001
- 作者简介：
- 基金信息：
  
  : 2018-02-07。作者简介: 宋喜玉(1992-),女,硕士生:郑娜娥(通信作者),女,博士,讲师。基金项目: 国家自然科学基金资助项目(61401469,41301481,61401513);国家科技重大专项资助项目(2013ZX03006003-006)
- DOI：10.7652/xjtuxb201810015
  中图分类号： TN958
- 网络首发：2018-10-10，
  
  纸质出版：2018
- 稿件说明：
移动端阅览
宋喜玉, 任修坤, 郑娜娥, 等. 多目标跟踪下的分布式MIMO雷达资源联合优化算法[J]. 西安交通大学学报, 2018,52(10):110-115+123.

A Joint Resource Optimization Algorithm of Distributed MIMO Radar Systems for Multiple Targets Tracking[J]. 2018, 52(10): 110-115+123.
宋喜玉, 任修坤, 郑娜娥, 等. 多目标跟踪下的分布式MIMO雷达资源联合优化算法[J]. 西安交通大学学报, 2018,52(10):110-115+123. DOI： 10.7652/xjtuxb201810015.

A Joint Resource Optimization Algorithm of Distributed MIMO Radar Systems for Multiple Targets Tracking[J]. 2018, 52(10): 110-115+123. DOI： 10.7652/xjtuxb201810015.

摘要

针对现有分布式MIMO雷达资源联合分配多集中于发射端阵元与功率的分配

未同时考虑接收阵元的优化

且缺乏对任意雷达布阵形势下系统跟踪能力和资源需求量估算等问题

提出多目标跟踪下的分布式MIMO雷达资源联合优化算法。首先

计算多目标位置误差的最大值

以最小化该最大值为目标函数; 其次

在发射和接收阵元总数量有限、发射总功率给定的条件下

建立收发阵元选取与功率分配联合的资源优化模型; 然后

结合启发式搜索算法和连续参数凸近似算法

采用循环最小化的方式对该问题进行求解; 最后

在给定大小的实验环境中

对目标运动轨迹确定和随机两种场景进行实验。实验结果表明

系统发射总功率一定时

选取的发射阵元个数要明显少于接收阵元个数。相比于现有MIMO雷达资源分配研究

所提算法能够估算出在任意雷达布阵形势下系统的最低目标跟踪精度、个数和相应的最少资源需求量

对雷达系统的结构设计和资源储备具有一定的参考价值。

Abstract

A joint resource optimization algorithm of distributed MIMO radar system for multiple targets tracking is proposed to solve the problems that existing researches on joint resource allocations for distributed MIMO radar systems focus on only transmitters and system power without optimization of receivers

and lack estimation of tracking capability and resource demands for random radar layouts. Firstly

the maximum of Cramer-Rao lower bound in multiple targets location is calculated and the objective is to minimize the maximum value. Next

an optimization model that considers transmitting power

transmitters and receivers is established under constraints of transmitting power and total number of selected transmitters and receivers. Then

a joint resource optimization algorithm based on cyclic minimization is proposed to solve the problem via combining the heuristic algorithm for antenna selection and the sequential parametric convex approximation algorithm for power allocation. Experimental results of static and random target trajectories in a given size of environment show that the number of selected transmitters is smaller than that of receivers when the total transmitting power is limited. Comparisons with existing resource allocation researches show that the proposed algorithm can evaluate the least target tracking accuracy

the number of targets

and the minimum corresponding resource demands of the system in any radar array situation. The algorithm may have some reference value for the structure design and resource reserve of distributed MIMO radar systems.

关键词

Keywords

references

HAIMOVICH A, BLUM R, CIMINI L. MIMO radar with widely separated antennas [J]. IEEE Signal Processing Magazine, 2008, 25(1): 116-129.

DEB D, BHATTACHARJEE R, VENGADARAJAN A. Resource manager for MIMO radar [C]∥ Proceedings of the IEEE Radar Conference. Piscataway, NJ, USA: IEEE, 2015: 71-75.

YAN J, LIU H, PU W, et al. Joint beam selection and power allocation for multiple target tracking in netted collocated MIMO radar system [J]. IEEE Transactions on Signal Processing, 2016, 64(24): 6417-6427.

严俊坤. 认知雷达中的资源分配算法研究 [D]. 西安: 西安电子科技大学, 2014: 1-6.

SUN Y, ZHENG N, LI Y, et al. Resource allocation approach for target localization in distributed MIMO radar sensor networks [J]. Systems Engineering Electronics, 2017, 39(2): 304-309.

CHEN Y J, ZHANG Q, LUO Y, et al. Multi-target radar imaging based on phased-MIMO technique: part II Adaptive resource allocation [J]. IEEE Sensors Journal, 2017, 17(19): 6198-6209.

GODRICH H, PETROPULU A P, POOR H V, et al. Sensor selection in distributed multiple-radar architectures for localization: a knapsack problem formulation [J]. IEEE Transactions on Signal Processing, 2012, 60(1): 247-260.

SONG Xiyu, ZHENG Na'e, BAI Ting. Resource allocation schemes for multiple targets tracking in distributed MIMO radar systems [J]. International Journal of Antennas and Propagation, 2017(10): 1-12.

GAO Yongchan, LI Hongbin, HIMED B. Knowledge-aided range-spread target detection for distributed MIMO radar in non-homogeneous environments [J]. IEEE Transactions on Signal Processing, 2017, 65(3): 617-627.

GAO H, WANG J, ZHANG X, et al. Resource allocation in MIMO radar with widely separated antennas for multi-target detection [C]∥ 2014 International Radar Conference. Piscataway, NJ, USA: IEEE, 2014: 7060247.

RADMARD M, CHITGARHA M M, MAJD M N, et al. Antenna placement and power allocation optimization in MIMO detection [J]. IEEE Transactions on Aerospace and Electronic Systems, 2014, 50(2): 1468 -1478.

CHAVALI P, NEHORAI A. Scheduling and power allocation in a cognitive radar network for multiple-target tracking [J]. IEEE Transactions on Signal Processing, 2012, 60(2): 715-729.

GODRICH H, PETROPULU A, POOR H V, et al. Cluster allocation schemes for target tracking in multiple radar architectures [C]∥2011 Conference Record of the 45th Asilomar Conference on Signals, Systems and Computers. Piscataway, NJ, USA: IEEE, 2011: 863-867.

严俊坤, 纠博, 刘宏伟, 等. 一种针对多目标跟踪的多基雷达系统聚类与功率联合分配算法 [J]. 电子与信息学报, 2016, 38(10): 1875-1881.

YAN Junkun, JIU Bo, LIU Hongwei, et al. Joint cluster and power allocation algorithm for multiple targets tracking in multi-static radar systems [J]. Journal of Electronics Information Technology, 2016, 38(10): 1875-1881.

GARCIA N, HAIMOVICH A M, COULON M, et al. Resource allocation in MIMO radar with multiple targets for non-coherent localization [J]. IEEE Transactions on Signal Processing, 2013, 62(10): 2656-2666.

胡捍英, 孙扬, 郑娜娥, 等. 多目标速度估计的分布式MIMO雷达资源分配算法 [J]. 电子与信息学报, 2016, 38(10): 2453-2460.

HU Hanying, SUN Yang, ZHENG Na'e, et al. Resource allocation approach in distributed MIMO radar with multiple targets for velocity estimation [J]. Journal of Electronics Information Technology, 2016, 38(10): 2453-2460.

TICHAVSKY P, MURAVCHIK C H, NEHORAI A. Posterior Cramer-Rao bounds for discrete-time nonlinear filtering [J]. IEEE Transactions on Signal Processing, 1998, 46(2): 1386-1396.

GODRICH H, HAIMOVICH A M, BLUM R S, et al. A MIMO radar system approach to target tracking [C]∥ Conference Record of the 43rd Aslimar Conference on Signals, Systems and Computers. Piscataway, NJ, USA: IEEE, 2009: 1186-1190.

BECK A, BENTAL A, TETRUASHVILI L A. Sequential parametric convex approximation method with applications to non-convex truss topology design problems [J]. Journal of Global Optimization, 2010, 47(1): 29-51.

浏览量

下载量

CSCD

文章被引用时，请邮件提醒。

提交

工具集

关联资源

面向成像任务的宽带MIMO雷达认知波形设计

超临界二氧化碳向心透平轮背间隙内风阻损失及流动特性研究

隧道内燃料电池汽车氢气泄漏扩散特性及影响因素

采用机器学习的大规模并行程序I/O性能建模与预测方法

面向高海拔空冷发电机防晕性能演化规律的电热耦合研究