基于空海异构无人平台的水下目标搜索与跟踪  

Underwater Target Search and Tracking Based on Air-Sea Heterogeneous Unmanned Platform

作　　者：丁文俊[1,2,3,4] 柴亚军 杨宇贤 刘佳敏 毛昭勇 DING Wenjun;CHAI Yajun;YANG Yuxian;LIU Jiamin;MAO Zhaoyong(Unmanned System Research Institute,Northwestern Polytechnical University,Xi’an 710072,China;Research Institute of Xi’an Jiaotong University,Hangzhou 311200,China;National Key Laboratory of Unmanned Aerial Vehicle Technology,Xi’an 710072,China;Integrated Research and Development Platform of Unmanned Aerial Vehicle Technology,Xi’an 710072,China)

机构地区：[1]西北工业大学无人系统技术研究院,陕西西安710072 [2]浙江西安交通大学研究院,浙江杭州311200 [3]无人飞行器技术全国重点实验室,陕西西安710072 [4]无人机技术集成攻关大平台,陕西西安710072

出　　处：《水下无人系统学报》2024年第2期237-249,共13页Journal of Unmanned Undersea Systems

基　　金：国家自然科学基金项目(51909206);中国博士后科学基金项目(2021M692616);陕西省自然科学基础研究计划项目(2024JC-YBMS-300);中央高校基本科研业务费专项资金项目(31020200QD044).

摘　　要：海上异构无人系统可有效提高复杂任务的完成效率。文中采用自主水下航行器(AUV)和无人机(UAV)来完成近海海域内未知水下目标的搜索与跟踪任务。首先,描述了水下目标搜索跟踪任务,将任务过程分为目标搜索和目标跟踪阶段,2个阶段的目标分别是使AUV&UAV总搜索空间最大化以及AUV与水下目标的末端位置误差最小;然后,建立AUV&UAV跨域协同搜索模型,并设定模型中AUV和UAV探测范围和通信距离等约束条件;最后,在跨域协同搜索与路径跟踪规划中,基于传统粒子群算法,加入自适应学习因子调控策略和精英保存策略,生成搜索与跟踪路径。仿真实验表明,采用改进粒子群优化算法的AUV&UAV异构无人系统能够更高效地完成水下目标搜索与跟踪任务。The marine heterogeneous unmanned systems can effectively enhance the implementation efficiency of complex missions.In this paper,autonomous undersea vehicles(AUVs)and unmanned aerial vehicles(UAVs)were used for searching and tracking unknown underwater targets in offshore waters.First,the underwater target search and tracking mission was described,and the mission was divided into two stages:target search and target tracking,with the objectives of maximizing the total search space of the AUV&UAV system and minimizing the end position error between the AUV and the underwater target,respectively.Then,a cross-domain collaborative search model of the AUV&UAV system was established,and constraints such as detection range and communication distance for AUVs and UAVs in the model were set.Finally,based on the traditional particle swarm optimization algorithm,an adaptive learning factor regulation strategy and an elite preservation strategy were employed for cross-domain collaborative search and tracking path planning,and search and tracking paths were generated.The simulation experiment demonstrates that the heterogeneous AUV&UAV system based on an improved particle swarm optimization algorithm can more efficiently search and track underwater targets.

关 键 词：跨域无人系统 自主水下航行器 无人机 改进粒子群优化算法 

分 类 号：TJ630.32[兵器科学与技术—武器系统与运用工程] U674[交通运输工程—船舶及航道工程]