摘要
本文针对舰载雷达系统自动跟踪运动目标上的问题,通过建立舰船导航雷达目标跟踪信号模型,提出了一种基于改进卡尔曼滤波的舰船雷达目标自动跟踪算法,该算法旨在提高对噪声的抑制作用,提高目标跟踪的精度,增强模型在真实场景下的实用性,解决长时间跟踪后的目标偏移及丢失问题。仿真结果表明,相较于最小二乘法、卡尔曼滤波算法,使用改进卡尔曼滤波算法的舰载雷达系统的跟踪性能以及精确度得到了大幅改善。
This article focuses on the problem of automatic tracking of moving targets in shipborne radar systems.By establishing a target tracking signal model for ship navigation radar,a ship radar target automatic tracking algorithm based on improved Kalman filtering is proposed.The algorithm aims to improve the suppression of noise,enhance the accuracy of target tracking,and enhance the practicality of the model in real scenarios to solve the problem of target offset and loss after long-term tracking.The simulation results show that compared with the least squares method and Kalman filtering algorithm,the tracking performance and accuracy of the shipborne radar system using the improved Kalman filtering algorithm have been significantly improved.
作者
刘轶
王楠
王宠
LIU Yi;WANG Nan;WANG Chong(Military Representative Bureau of Naval Equipment Department in Beijing,Beijing 100071,China;Wuhan Second Ship Design and Research Institute,Wuhan Hubei 430061,China)
出处
《信息与电脑》
2024年第14期148-150,185,共4页
Information & Computer
关键词
卡尔曼滤波
舰船导航雷达
自动跟踪
Kalman filtering
ship navigation radar
automatic tracking
