基于MIC的目标定位跟踪算法研究
Research on target location and tracking algorithm based on MIC
孙兆宇 1廖相平 1马鹏飞1
作者信息
- 1. 西藏大学 信息科学技术学院,西藏 拉萨 850032
- 折叠
摘要
文章针对双基阵纯方位的目标运动分析这一复杂问题,提出了一种方位信息数据关联技术.在空气中,通过对目标及观测数据进行修正迭代关联(Modified Iterative Correlation,MIC),并运用扩展卡尔曼滤波(Extended Kalman Filter,EKF)算法和无迹卡尔曼滤波(Unscented Kalman Filter,UKF)算法进行目标跟踪.仿真结果表明:不仅在水下,在空气中经过MIC算法后2 种滤波算法均适用于运动目标实时跟踪,但UKF算法具有更好的跟踪效果.文章给出了在不同噪声水平下的跟踪误差曲线和跟踪轨迹图,以验证算法的有效性和优越性.
Abstract
Aiming at the complex problem of underwater dual array azimuth-only target motion analysis,this paper proposes a azimuth-data association technology.In the air,Modified Iterative Correlation is performed by modifying the target and the observed data,and the target is tracked by Extended Kalman Filter algorithm and Unscented Kalman Filter algorithm.The simulation results show that the two filtering algorithms are suitable for real-time tracking of moving targets not only under water,but also in air after the spatiotemporal correlation(IATS)algorithm,but the Untracked Kalman Filter algorithm has better tracking effect.The tracking error curve and tracking track graph under different noise levels are given to verify the effectiveness and superiority of the algorithm.
关键词
纯方位/目标跟踪/扩展卡尔曼滤波/无迹卡尔曼滤波Key words
azimuth only/target tracking/Extended Kalman Filter/Untraced Kalman Filter引用本文复制引用
出版年
2024
NETL
NSTL
万方数据