指挥控制与仿真2024，Vol.46Issue(3)：95-101,7.DOI:10.3969/j.issn.1673-3819.2024.03.014
基于深度学习的纯方位水下目标机动检测
Bearing-only underwater target maneuver detection based on deep learning
陈建润 1毛卫宁1
作者信息
- 1. 东南大学信息科学与工程学院,江苏 南京 210096
- 折叠
摘要
Abstract
Two bearing-only maneuver detection methods based on deep learning are proposed to address the problems of long detection delay and low accuracy of existing bearing-only maneuver detection methods for underwater targets.The bearing observations of the target in the constant velocity(CV)motion state and constant turning(CT)motion state are used as the training data set.The target motion pattern classification and bearing prediction are realized through the Long short-term memory(LSTM)neural network,and then realize the maneuver detection of underwater targets based on motion pattern clas-sification and bearing prediction.The simulation results show that compared with the traditional bearing prediction maneuver detection method,this method reduces the bearing observation error and has a lower sensitivity of target maneuver magnitude,and has a higher maneuver detection accuracy and reduces the maneuver detection delay.关键词
纯方位/机动检测/LSTM网络/运动模式/方位预测Key words
bearing-only/maneuver detection/LSTM network/movement pattern/bearing prediction引用本文复制引用
陈建润,毛卫宁..基于深度学习的纯方位水下目标机动检测[J].指挥控制与仿真,2024,46(3):95-101,7.
