面向区域覆盖的多传感器优化布站

doi:10.3969/j.issn.1009-086x.2018.06.015

现代防御技术 ›› 2018, Vol. 46 ›› Issue (6): 94-101.DOI: 10.3969/j.issn.1009-086x.2018.06.015

面向区域覆盖的多传感器优化布站

俞宙¹, 单甘霖¹, 段修生^{1, 2}

1. 陆军工程大学石家庄校区, 河北石家庄 050003;
2. 石家庄铁道大学, 河北石家庄 050003

出版日期:2018-11-30 发布日期:2020-10-22
作者简介:俞宙(1994-), 男, 江苏盱眙人。硕士生, 主要从事信息融合和传感器管理。通信地址:050003 河北省石家庄市新华区和平西路97号二系火控教研室 E-mail:yyyyzhou@163.com

Multi-Sensor Optimal Deployment for Area Coverage

YU Zhou¹, SHAN Gan-lin¹, DUAN Xiu-sheng^{1, 2}

1.Army Engineering University, Shijiangzhuang Compus, Hebei Shijiazhuang 050003, China;
2.Shijiazhuang Tiedao University, Hebei Shijiazhuang 050003, China

Online:2018-11-30 Published:2020-10-22

摘要/Abstract

摘要： 针对约束条件下传感器优化布站问题, 提出了一种基于遗传粒子群算法(GA-PSO)的多传感器优化布站方法。首先网格化战场地理环境, 依据战场地理环境和战术条件建立布站约束矩阵;然后考虑任务需求, 建立基于探测覆盖率的目标优化函数;最后采用遗传粒子群算法求解传感器最优布站位置。仿真实验验证了所提方法的有效性和合理性。

关键词: 协同探测, 区域覆盖, 战场地理, 战术条件, 多传感器, 优化布站, 遗传粒子群算法

Abstract: To solve the problem of sensor optimal deployment in the constrained conditions, a multi-sensor optimal deployment method is proposed based on genetic algorithm particle swarm optimization (GA-PSO). The method firstly meshes the battlefield geography environment and establishes the constraint matrix of deployment according to the battlefield geography environment and tactical conditions. Then, the objective optimization function based on detection coverage is established. Finally, the GA-PSO is used to solve the optimal position of the sensor. The simulation verifies the effectiveness and rationality of the proposed method.

Key words: collaborative detection, area coverage, battlefield geography, tactical conditions, multi-sensor, optimal deployment, genetic algorithm particle swarm optimization(GA-PSO)

中图分类号:

俞宙, 单甘霖, 段修生. 面向区域覆盖的多传感器优化布站[J]. 现代防御技术, 2018, 46(6): 94-101.

YU Zhou, SHAN Gan-lin, DUAN Xiu-sheng. Multi-Sensor Optimal Deployment for Area Coverage[J]. Modern Defense Technology, 2018, 46(6): 94-101.

参考文献 16

[1]	罗俊海, 王章静.多源数据融合和传感器管理[M].北京:清华大学出版社, 2015.LUO Jun-hai, WANG Zhang-jing.Multi-Source Data Fusion and Sensor Management[M].Beijing:Tsinghua University Press, 2015.
[2]	FENG C, WANG G, HE K.A Disposition Algorithm for Radar Netting[C]∥Radar Conference 2013, IET International, IET, 2013:1-4.
[3]	HURLEY S, KHAN M I.Netted Radar:Network Communications Design and Optimisation[J].Ad Hoc Networks, 2011, 9(5):736-751.
[4]	毛滔, 蔺美青, 周建飞.地面防空预警雷达探测概率仿真模型研究[J].空军预警学院学报, 2013(6):430-434.MAO Tao, LIN Mei-qing, ZHOU Jian-fei.Research on Probability Simulation Model of Ground-Based Air Defense Early Warning Radar[J].Journal of Air Force Early Warning Academy, 2013(6):430-434.
[5]	雷雨, 冯新喜, 朱灿彬, 等.2D雷达组网几何定位融合算法[J].系统工程与电子技术, 2011, 33(5):1151-1156.LEI Yu, FENG Xin-xi, ZHU Can-bin, et al.Geometric Location Fusion Algorithm for 2D Radar Networking[J].Systems Engineering and Electronics, 2011, 33 (5):1151-1156.
[6]	ZDEMIR S, ATTEA B A, NDER A.Khalil.Multi-Objective Evolutionary Algorithm Based on Decomposition for Energy Efficient Coverage in Wireless Sensor Networks[J].Wireless Personal Communications, 2013, 71(1):195-215.
[7]	LAVETI G, RAO G S, CHAITANYA D E, et al.TDOA Measurement Based GDOP Analysis for Radio Source Localization[J].Procedia Computer Science, 2016, 85:740-747.
[8]	DASH D, BISHNU A, GUPTA A, et al.Approximation Algorithms for Deployment of Sensors for Line Segment Coverage in Wireless Sensor Networks[J].Wireless Networks, 2013, 19(5):857-870.
[9]	杨仕明, 柯炳清, 薛正辉.基于遗传算法的区域雷达网优化布站方法[J].北京理工大学学报, 2005(6):534-537.YANG Shi-ming, KE Bing-qing, XUE Zheng-hui.Approach to Regional Radar Netting Optimization Based on Genetic Algorithm[J].Transactions of Beijing Institute of Technology, 2005(6):534-537.
[10]	李动, 黄心汉.基于改进遗传算法的雷达网优化布站方法[J].华中科技大学学报:自然科学版, 2013, 41(S1):407-409.LI Dong, HUAG Xin-han.A Radar Netting Optimization Method Based on Modified Genetic Algorithm[J].Journal of Huazhong University of Science and Technology:Natural Science ed, 2013, 41(S1):407-409.
[11]	刘砚菊, 胡杨, 于洋, 等.基于改进粒子群算法的复杂地况下雷达布站优化[J].火力与指挥控制, 2014, 39(9):164-168.LIU Yan-ju, HU Yang, YU Yang, et al.Study of Radar Deployment Under Complex Terrain EnvironmentBased on Improved PSO[J].Fire Control & Command Control, 2014, 39(9):164-168.
[12]	RAHA A, MAITY S, NASKAR M K, et al.An Optimal Sensor Deployment Scheme to Ensure Multi Level Coverage and Connectivity in Wireless Sensor Networks[C]∥Wireless Communications and Mobile Computing Conference.IEEE, 2012:299-304.
[13]	GAO S.Research on Optimum Deployment Problem of Radar[C]∥ISECS International Colloquium on Computing, Communication, Control, and Management, IEEE Computer Society, 2008:466-469.
[14]	蔡婧, 许剑, 李婧娇.基于文化遗传算法的雷达组网优化部署[J].现代防御技术, 2010, 38(6):6-11.CAI Jing, XU Jian, LI Jing-jiao.Genetic Algorithm Based on Cultural Algorithm Applied to Optimal Deployment of Radar Network[J].Modern Defence Technology, 2010, 38(6):6-11.
[15]	HELAL T S, MOZUMDAR P, AKTER L.Evaluating the Performance of Optimal Control Based Sensor Deployment Algorithms for Realistic Terrain Model[C]∥International Conference on Electrical and Computer Engineering, IEEE, 2015:741-744.
[16]	黄山良, 卜卿.防空探测预警系统与技术[M].北京:国防工业出版社, 2015.HUANG Shan-liang, BU Qing.Air Defense Detection and Early Warning System and Technology[M].Beijing:National Defense Industry Press, 2015.

面向区域覆盖的多传感器优化布站

Multi-Sensor Optimal Deployment for Area Coverage

PDF (PC)

可视化

摘要/Abstract

引用本文

使用本文

参考文献 16

相关文章 7

编辑推荐

Metrics

本文评价

[1]	董胜波, 苏琪雅, 于沐尧, 赵青. 协同探测与导引技术发展探讨[J]. 现代防御技术, 2023, 51(3): 75-82.
[2]	马艳艳, 金宏斌, 李浩, 张辉. 改进粒子群算法在雷达组网优化布站中的应用[J]. 现代防御技术, 2020, 48(3): 104-112.
[3]	杨军佳, 叶晨亮, 刘志青, 廉博. SPA和DS证据理论的多传感器航迹关联方法[J]. 现代防御技术, 2018, 46(6): 75-79.
[4]	刘标, 许腾, 刘树锋. 水下目标识别的规划融合算法[J]. 现代防御技术, 2018, 46(6): 64-67.
[5]	董晨, 刘兴科, 周金鹏, 陆志沣. 导弹防御多传感器协同探测任务规划[J]. 现代防御技术, 2018, 46(6): 57-63.
[6]	林菡, 李昌玺, 陈丽娟. MIMO-FNN模型的弹道导弹目标识别方法[J]. 现代防御技术, 2018, 46(6): 36-43.
[7]	刘标, 许腾, 李光. D-S证据理论改进算法提高水下目标识别准确性[J]. 现代防御技术, 2018, 46(1): 120-124.