多传感器交叉提示技术在传感器联盟中的应用

庞策; 黄树彩; 刘锦昌; 赵炜; 韦道知

doi:10.7652/xjtuxb201707021

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多传感器交叉提示技术在传感器联盟中的应用

更新时间：2025-07-09

- 多传感器交叉提示技术在传感器联盟中的应用
- Application of Multi-Sensor Cross Cueing Technology in Sensor Alliance
- 西安交通大学学报 2017年51卷第7期页码：148-155
- 作者机构：
  
  空军工程大学防空反导学院,西安,710051
- 作者简介：
- 基金信息：
  
  : 2017-01-18。作者简介: 庞策(1993—),男,硕士生;黄树彩(通信作者),男,教授。基金项目: 国家自然科学基金资助项目(61573374);国家自然科学基金青年基金资助项目(61503408);航空科学基金资助项目(20150196006)
- DOI：10.7652/xjtuxb201707021
  中图分类号： TN215
- 网络首发：2017-07-10，
  
  纸质出版：2017
- 稿件说明：
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庞策, 黄树彩, 刘锦昌, 等. 多传感器交叉提示技术在传感器联盟中的应用[J]. 西安交通大学学报, 2017,51(7):148-155.

Application of Multi-Sensor Cross Cueing Technology in Sensor Alliance[J]. 2017, 51(7): 148-155.
庞策, 黄树彩, 刘锦昌, 等. 多传感器交叉提示技术在传感器联盟中的应用[J]. 西安交通大学学报, 2017,51(7):148-155. DOI： 10.7652/xjtuxb201707021.

Application of Multi-Sensor Cross Cueing Technology in Sensor Alliance[J]. 2017, 51(7): 148-155. DOI： 10.7652/xjtuxb201707021.

摘要

围绕多传感器交叉提示技术在传感器联盟中的应用展开研究

用多传感器交叉提示技术组建并更新传感器联盟

解决传感器联盟的动态控制问题。在建立传感器联盟组建过程中

以节省传感器资源和提高传感器资源利用率为目的建立目标函数

将单目标跟踪精度需求作为约束条件

建立了传感器联盟模型。在传感器联盟更新过程中

提出预测更新的传感器管理结构。设计基于多维协商的多传感器交叉提示分布式算法

用于求解及更新传感器联盟方案。仿真实验表明了文中模型的有效性

与拍卖算法和粒子群算法相比

所提算法收敛速度快

求解质量较好; 与测量更新的结构相比

预测更新的传感器管理结构更适应于作战态势变化较快的情形。

Abstract

The study on the application of multi-sensor cross cueing technology in sensor alliance was conducted

where multi-sensor cross cueing technology is used to build and update sensor alliances to solve the problem of dynamic control of sensor alliances. When building a sensor alliance

the objective function is built aiming at saving sensor resource and enhancing the resource utilization; and when updating a sensor alliance

the sensor management structure predict then update is presented. The multi-sensor cross cueing distributed algorithm based on multi-dimensional consultation was designed for resolving and updating the sensor alliance scheme. The simulation results indicate that the model in this paper is effective. Compared with auction algorithm and particle swarm

the convergence rate of the algorithm proposed in this paper is the fastest and with better results. Compared with the method of detect

then update the method of predict then update is more suitable to the condition where the combat situation often changes quickly.

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Keywords

references

ZHANG G F, JIANG J G, XIA N, et al. Solutions of complicated coalition generation based on discrete particle swarm optimization [J]. Acta Eletronica Sinica, 2007, 35(2): 323-327.

CHEN W, FU Y. Cooperative distributed target tracking algorithm in mobile wireless sensor networks [J]. Journal of Control Theory Applications, 2011, 9(2): 155-164.

SHEN X J, VARSHNEY P K. Sensor selection based on generalized information gain for target tracking in large sensor networks [J]. IEEE Transactions on Signal Processing, 2014, 62(2): 363-375.

KALANDROS M, PAO L Y. Covariance control for multi-sensor systems [J]. IEEE Transactions on Aerospace and Electronic Systems, 2002, 38(4): 1138-1157.

HOANG H G, VO B T. Sensor management for multi-target tracking via multi-Beronoulli filtering [J]. Automatic, 2014, 50(2): 1135-1142.

赵建华, 张陵, 孙清. 利用粒子群算法的传感器优化布置及结构损伤识别研究 [J]. 西安交通大学学报, 2015, 49(1): 79-85.

ZHAO Jianhua, ZHANG Ling, SUN Qing. Optimal placement of sensors for structural damage identification using improved particle swarm optimization [J]. Journal of Xi'an Jiaotong University, 2015, 49(1): 79-85.

SEVERSON T A, DEREK A P. Distributed multi-target search and track assignment with consensus-based coordination [J]. IEEE Sensors Journal, 2015, 15(2): 864-875.

PANESCU D, PASCAL C. An extended contract net protocol with direct negotiation of managers [M]∥ Service Orientation in Holonic and Multi-Agent Manufacturing and Robotics. Berlin, Germany: Springer, 2014: 81-95.

GUPTA A K, GALLASCH G E. Equivalence class verification of the contract net protocol extension [J]. International Journal on Software Tools for Technology Transfer, 2016, 18(6): 685-706.

ZHONG L, HUANG Q, WU F. et al. TRADE: A truthful online combinatorial auction for spectrum allocation in cognitive radio networks [J]. Wireless Communication Mobile Computing, 2015, 15(9): 1320-1330.

方德亮, 冉晓旻, 李鸥. 一种能量有效的分布式传感器管理算法 [J]. 西安电子科技大学学报(自然科学版), 2017, 44(2): 182-187.

FANG Deliang, RAN Xiaomin, LI Ou. Energy efficient distributed sensor management algorithm [J]. Journal of Xidian University, 2017, 44(2): 182-187.

SEVERSON T A, DEREK A P. Distributed multi-target search and track assignment with consensus-based coordination [J]. IEEE Sensors Journal, 2015, 15(2): 864-875.

BENTLEY E S, KONDI L P, MATYJAS J D. Effective resource management in visual sensor networks with MPSK [J]. Signal Processing Letters, 2013, 20(8): 739-742.

ZHENG Y, OZDEMIR O, NIU R, et al. New conditional posterior Cramér-Rao lower bounds for nonlinear sequential Bayesian estimation [J]. IEEE Transactions on Signal Processing, 2012, 60(10): 5549-5556.

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