[an error occurred while processing this directive] [an error occurred while processing this directive] [an error occurred while processing this directive]
[an error occurred while processing this directive]

多机协同探测传感器管理

  • 王楠 ,
  • 许蕴山 ,
  • 夏海宝 ,
  • 王俊迪
展开
  • 1 空军工程大学航空机务士官学校, 河南 信阳 464099
    2 空军工程大学, 西安 710038

王楠(1994-),男,陕西咸阳人,硕士研究生,研究方向:传感器管理、雷达资源管理。

收稿日期: 2018-03-02

  网络出版日期: 2025-05-20

The Sensor Management in Multi-fighter Cooperative Detection

  • WANG Nan ,
  • XU Yunshan ,
  • XIA Haibao ,
  • WANG Jundi
Expand
  • 1 Aviation Maintenance NCO Academy, Air Force Engineering Unirersity, Henan Xinyang 464099, China
    2 Aeronautics Engineering College, Air Force Engineering University, Xi'an 710038, China

Received date: 2018-03-02

  Online published: 2025-05-20

摘要

针对作战单元的体系化发展,作战任务通常由多平台协同完成,机载传感器作为获取战场信息的主要设备,必须在应用中对其进行有效的组织协调。文中针对多机协同探测的传感器管理问题进行研究。根据传感器与平台各自的动态特点,设计了一种双层管理系统进行传感器的综合管理,分层是基于物理动态与信息动态的差异进行的。其中基于物理动态的空时划分利用线性规划方法进行优化,基于信息动态的资源管理采用多臂赌博机(multi-armedbandit)模型的UCB(upperconfidencebound)指数方法。

本文引用格式

王楠 , 许蕴山 , 夏海宝 , 王俊迪 . 多机协同探测传感器管理[J]. 弹箭与制导学报, 2019 , 39(2) : 20 -23 . DOI: 10.15892/j.cnki.djzdxb.2019.02.005

Abstract

With the systemization development of operation unit, the operation is achieved by multi-platform cooperative. Airborne sensor offers an essential support for reaching the operation aim which regarded as the main equipment for sensing the battlefield. This paper studies the sensor management in multi-fighter cooperative detection. With the character of sensor and platform a double level management system is designed in the paper depending upon the difference between physical dynamics and information dynamics. In which the optimization of the spatial-temporal allocation basing on physical dynamic is solved by the linear programming. The resource management basing on information is described as a MAB(Multi-Armed Bandit) model and optimized by the UCB (Upper Confidence Bound) index method

[an error occurred while processing this directive]

参考文献

[1]
张金哲, 韩晓明. 基于改进 AHP法的飞机超视距作战能力评估[J]. 火力与指挥控制, 2009, 34 10: 159- 160.
[2]
杨秀珍, 何友, 鞠传文. 多传感器管理系统研究现状与发展趋势[J]. 传感器技术, 2004, 23 1: 5- 8.
[3]
崔博鑫, 许蕴山, 夏海宝,等. 基于任务控制的动态多传感器管理方案[J]. 系统工程与电子技术, 2012, 34 12: 2473- 2478.
[4]
杨秀珍, 何友, 鞠传文. 传感器管理的结构与微观传感器管理仿真[J]. 系统工程与电子技术, 2004, 26(11): 1581-1584.
[5]
NASH J M. Optimal allocation of tracking resource[C]// Proceeding of 1977 IEEE Conference on Decision and Control. [S. l.]: IEEE, 1977: 1177 – 1180.
[6]
HERO A O, COCHRAN D. Sensor management: Past, present, and future[J]. IEEE Sensors Journal, 2011, 11(12): 3064-3075.
[7]
刘钦. 多传感器组网协同跟踪方法研究[D]. 西安:西安电子科技大学, 2013.
[8]
XU B, YANG C Y, MAO S Y, et al. Adaptive search strategy in phased array radars[C]//IEEE. 2001 CIE International Conference on Radar Proceedings. [S.l.]: IEEE, 2001: 250-254.
[9]
WASHBURN R B, SCHNEIDER M K, FOX J J. Stochastic dynamic programming based approaches to sensor resource management[C]//IEEE. Proceedings of the Fifth International Conference on Information Fusion. [S.l.]: IEEE, 2002: 609-615.
[10]
KRISHNAMURTHY V, EVANS R J. Hidden Markov model multiarm bandits: A methodology for beam scheduling in multitarget tracking[J]. IEEE Transactions on Signal Processing, 2001, 49(12): 2893-2908.
[11]
LA SCALAB F, MORAN B. Optimal target tracking with restless bandits[J]. Digital Signal Processing, 2006, 16(5): 479 – 487.
[12]
黄俊园. 认知无线网络序贯频谱感知研究[D]. 武汉: 武汉大学, 2014.
[13]
AUER P, CESA-BIANCHI N, FISCHER P. Finite-time analysis of the multiarmed bandit problem[J]. Machine Learning, 2002, 47(2/3): 235-256.
[14]
GITTINS J C. Bandit processes and dynamic allocation indices[J]. Journal of the Royal Statistical Society: Series B(Methodological) , 1979, 41(2): 148 – 177.
[15]
丁鹭飞, 耿富录, 陈建春. 雷达原理[M]. 3 版. 北京: 电子工业出版社, 2009: 138-141.
[16]
陈红翠. 认知网络中基于赌博机模型的信道选择机制研究[D]. 重庆: 重庆邮电大学, 2016.
[17]
朱江, 陈红翠, 熊加毫. 基于多臂赌博机模型的信道选择[J]. 电讯技术, 2015, 55(10): 1094 – 1100.
文章导航

/

[an error occurred while processing this directive]