考虑锚节点位置不确定的水下目标定位算法研究  

Research on Underwater Target Localization Algorithm Considering the Uncertainty of Anchor Position

作　　者：闫敬[1] 张婷 尤康林 商志刚 杨晛 罗小元[1] YAN Jing;ZHANG Ting;YOU Kanglin;SHANG Zhigang;YANG Xian;LUO Xiaoyuan(Institute of Electrical Engineering,Yanshan University,Qinhuangdao 066099,China;Institute of Underwater Acoustic Engineering,Harbin Engineering University,Harbin 150001,China)

机构地区：[1]燕山大学电气工程学院,秦皇岛066099 [2]哈尔滨工程大学水声工程学院,哈尔滨150001

出　　处：《电子与信息学报》2024年第1期67-73,共7页Journal of Electronics & Information Technology

基　　金：国家自然科学基金(62222314,61973263,62033011);河北省青年拔尖人才计划(BJ2020031);河北省自然科学基金(F2022203001,F2021203056);河北省中央引导地方基金(226Z3201G)。

摘　　要：考虑时钟异步和声波分层效应的影响,该文研究了当测量过程受到未知噪声干扰,且锚节点位置不确定时水下目标节点的定位问题。首先构造了水下节点间飞行时间模型,设计了一种交互式异步通信协议,建立了最小化定位误差的优化目标函数。然后提出了一种基于深度强化学习的水下目标定位算法,并采用层归一化来改进深度神经网络,进一步提高模型的泛化能力。最后,仿真和实验结果验证所提方法的有效性。Considering the effects of an asynchronous clock and acoustic stratification,the localization problem of an underwater target node was studied when the measurement process was disrupted by unknown noise and the anchor position was uncertain.The time of flight model between underwater nodes is constructed,an interactive asynchronous communication protocol is designed,and an optimization objective function to minimize the localization error is established.An underwater target localization algorithm based on deep reinforcement learning is proposed,and layer normalization is used to improve the generalization ability of the model.Finally,simulation and experimental results validate the effectiveness of the proposed method.

关 键 词：水下无线传感网络 定位 锚节点不确定 深度强化学习 

分 类 号：TN929.3[电子电信—通信与信息系统]