Multi-sensor system deployment planning method for underwater surveillance based on formation characteristics

作     者：Yan, Zheping Cai, Sijia Hou, Shuping Zhang, Mingyao 

作者机构：Harbin Engn Univ Coll Intelligent Syst Sci & Engn Harbin 150001 Peoples R China Harbin Engn Univ Qingdao Innovat & Dev Ctr Qingdao 266000 Peoples R China Harbin Engn Univ Coll Mech & Elect Engn Harbin 150001 Peoples R China 

出 版 物：《AD HOC NETWORKS》 (Ad Hoc Netw.)

年 卷 期：2025年第170卷

核心收录：

学科分类：0810[工学-信息与通信工程] 0809[工学-电子科学与技术（可授工学、理学学位）] 08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：National Nature Science Foundation of China [42327901  52071102] 

主　　题：Multi-sensor system Multi-objective optimization Underwater surveillance Non-dominated sorting genetic algorithm Mean-Shift clustering Barrier coverage 

摘      要：The deployment planning issue for a multi-sensor system comprising a limited number of sensors designed to detect underwater intrusion targets is defined as a multi-objective NP-hard problem. This problem is constituted by two competing and incommensurable optimization objectives: larger sensor coverage and higher probability of detecting intrusion targets. The map of the mission area is transformed into a topological map through the application of polygon fitting and segmentation based on Delaunay triangulation. This study employs a characteristics-based non-dominated sorting genetic algorithm (CBNSGA) to address the deployment planning issue of the multi-sensor system. In this algorithm, Mean-Shift clustering is employed to yield characteristics information through the clustering of the multi-sensor system formation. Subsequently, this information is employed to enhance the crossover, mutation, and selection strategies. Adaptive parameters are designed to accelerate convergence and avoid local optima. Additionally, the Cauchy inverse cumulative distribution operator is employed to enhance the mutation step. The feasibility and effectiveness of the CBNSGA in multi-sensor system deployment planning are demonstrated through simulation and comparison with other algorithms.