数据采集与处理2024，Vol.39Issue(6)：1470-1478,9.DOI:10.16337/j.1004-9037.2024.06.015
基于自适应平滑KF-PDA算法的舰船单目标跟踪
Single Target Tracking of Ships Based on Adaptive Smoothing KF-PDA Algorithm
摘要
Abstract
In view of high computational complexity of the probability data association(PDA)algorithm in cluttered environments,a data association method based on the PDA algorithm is designed.When the number of measurement points in the wavegate exceeds a certain threshold,the PDA algorithm is employed to update the target state.When the number of measurement points falls below or equals the threshold,a nearest-neighbor approach is used to filter the target measurement points.Subsequently,the Kalman filter(KF)algorithm is utilized to achieve fast filtering updates in cluttered environments.Additionally,the paper proposes an adaptive interval smoothing method that dynamically corrects the smoothing interval to achieve reverse smoothing of the overall state estimation.This approach aims to improve the algorithm's accuracy.Experimental results of various clutter environments demonstrate that the proposed method effectively enhances the estimation accuracy of the system state while ensuring tracking efficiency.Moreover,the results validate the robustness and effectiveness of the method compared to the PDA algorithm and the KF-PDA algorithm.关键词
自适应平滑区间/卡尔曼滤波算法/概率数据互联算法/状态估计Key words
adaptive smoothing interval/Kalman filtering algorithm/probability data association(PDA)algorithm/state estimation分类
信息技术与安全科学引用本文复制引用
任明亮,贾志强,盛庆红,孙珠磊..基于自适应平滑KF-PDA算法的舰船单目标跟踪[J].数据采集与处理,2024,39(6):1470-1478,9.基金项目
国家自然科学基金(42301384) （42301384）
装备预研重点实验室基金(HTKJ2021KL504013). （HTKJ2021KL504013）
