基于单平台探测概率模型的水下无人集群部署规划算法

生雪莉; 李鹏飞; 郭龙祥; 陆 典; 韩 笑

doi:10.11993/j.issn.2096-3920.2019.02.011

基于单平台探测概率模型的水下无人集群部署规划算法

doi: 10.11993/j.issn.2096-3920.2019.02.011

1.
哈尔滨工程大学水声技术重点实验室, 哈尔滨, 150001
2.
海洋信息获取与安全工信部重点实验室哈尔滨工程大学, 工业和信息化部, 哈尔滨, 150001
3.
哈尔滨工程大学水声工程学院, 哈尔滨, 150001

基金项目: 国家自然科学基金(51779061); 霍英东青年教师基金(151007)资助

详细信息

作者简介:
生雪莉(1979-), 女, 博士, 教授, 主要研究方向为水声信号处理技术.

中图分类号: TJ630.33; TB566
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- 文章访问数: 701
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- 被引次数: 0
出版历程
- 收稿日期: 2018-11-08
- 修回日期: 2018-12-26
- 刊出日期: 2019-04-30

Deployment Planning Algorithm of Unmanned Underwater Swarm Based on Probability Model of Single-platform Detection

1.
Acoustic Science and Technology Laboratory, Harbin Engineering University, Harbin 150001, China
2.
Key Laboratory of Marine Information Acquisition and SecurityHarbin Engineering University, Ministry of Industry and Information Technology, Harbin 150001, China
3.
College of Underwater Acoustic Engineering, Harbin Engineering University, Harbin 150001, China

摘要

摘要: 在执行海洋环境监测、近海勘探及军事战术侦察等任务时, 水下无人集群探测的探测性能取决于集群内平台的部署规划及单个平台的探测性能模型。文中基于主动声呐信息流程和海军水面舰艇模型(NISSM), 引入了单平台区域探测的概率模型, 提出一种基于布谷鸟搜索算法, 采用高斯变异算子和锦标赛选择机制的指定区域内无人平台部署规划算法, 并进行了仿真验证。仿真结果表明: 单平台探测概率模型能够量化地给出区域内各点的探测概率, 有效反映受平台自身参数及海洋环境约束引起的平台探测信息的不确定性, 且平台探测能力的衰减程度与虚警概率相关。文中的无人平台部署规划算法较布谷鸟算法性能优异、进化曲线斜率更陡、收敛速度更快, 不同数量平台基于该算法部署规划后的区域有效探测覆盖率较随机部署高0.2, 达0.8以上。文中的研究可对任务区域无人集群的布放提供参考。
- 水下无人集群 /
- 单平台探测概率模型 /
- 无人平台部署规划算法 /
- 区域有效探测覆盖率
Abstract: In marine environment monitoring, offshore exploration, military tactical reconnaissance and other missions, the detection performance of unmanned underwater swarm depends on the deployment planning of swarm and the detection performance model of single platform. In this paper, a probability model of single platform for area detection is proposed based on the active sonar process and the navy interim surface ship model(NISSM) sonar model. An unmanned platform deployment planning algorithm in a specified area using a Gaussian mutation operator and a tournament selection mechanism is proposed based on cuckoo search algorithm. Simulation result indicates that the probability model of single-platform detection can give detection probability of each point in a region quantitatively, and can effectively reflect the uncertainty of detection information, which is induced by the restriction of platform’s parameter and marine environment. And the attenuation of the platform detection capability relates to the false alarm probability. The proposed algorithm performs better than the cuckoo search algorithm in terms of higher slope of the evolution curve, and faster convergence speed. For different number of platforms, the effective detection coverage rate of the unmanned platform deployment planning algorithm is more than 0.8, 0.2 higher than that of the random deployment.
- unmanned underwater swarm /
- single-platform detection probability model /
- unmanned platform deployment planning algorithm /
- effective detection coverage rate

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参考文献(11)

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