基于自适应新生目标强度的概率假设密度滤波

系统仿真学报 ›› 2015, Vol. 27 ›› Issue (11): 2741-2747.

• 信息、控制、决策与仿真 • 上一篇下一篇

基于自适应新生目标强度的概率假设密度滤波

吴静静^1,2, 尤丽华^1,2, 王瑶¹, 宋淑娟¹

1.机械工程学院江南大学,无锡 214122;
2.江苏省食品先进制造装备技术重点实验室,无锡 214122

收稿日期:2014-07-22 修回日期:2014-12-20 出版日期:2015-11-08 发布日期:2020-08-05
作者简介:吴静静(1982-),女,安徽滁州,博士,研究方向为数字图像处理、模式识别及信息融合;尤丽华(1955-),女,江苏淮安,副教授,研究方向为机电一体化与图像检测技术。
基金资助:
国家自然科学基金项目(61305016)

Probability Hypothesis Density Filter Based on Adaptive Target Birth Intensity

Wu Jingjing^1,2, You Lihua^1,2, Wang Yao¹, Song Shujuan¹

1. School of Mechanical Engineering, Jiangnan University, Wuxi 214122, China;
2. Jiangsu Key Laboratory of Advanced Food Manufacturing Equipment and Technology, Wuxi 214122, China

Received:2014-07-22 Revised:2014-12-20 Online:2015-11-08 Published:2020-08-05

摘要/Abstract

摘要： 针对概率假设密度滤波器(Probability Hypothesis Density,PHD)无法跟踪未知起始位置新生目标的问题,提出一种具有自适应新生目标强度的PHD滤波器。采用航迹起始技术检测新生目标的位置,根据检测位置构造新生目标强度函数,提出新生目标强度的在线估计算法。在PHD滤波框架下,引入新生目标强度更新机制,采用更新的新生目标强度完成PHD滤波的递推,并给出了基于自适应新生目标强度PHD的高斯混合实现算法。仿真结果表明：该方法改进了PHD滤波的多目标跟踪性能,能够有效跟踪任意时刻未知位置的新生目标。

关键词: 多目标跟踪, 概率假设密度, 新生目标强度, 在线估计, 高斯混合

Abstract: For probability hypothesis density (PHD) filter, that was not able to track birth targets of unknown position, PHD filter with adaptive target birth intensity was proposed. The track initiation algorithm was employed to detect positions of promising birth targets which were used to form the intensity function of birth targets, and an online estimation algorithm of spontaneous birth intensity was proposed. Adaptive target birth intensity was combined with the recursion of the PHD filter, and a solution to the PHD filter based on adaptive target birth intensity for linear Gaussian target dynamics was proposed. Simulation results demonstrate that the proposed tracker improves on effectively tracking birth targets of unknown positions in the scenario at any time.

Key words: multi-target tracking, probability hypothesis density, birth target intensity, online estimation, Gaussian mixture

中图分类号:

TP391

吴静静, 尤丽华, 王瑶, 宋淑娟. 基于自适应新生目标强度的概率假设密度滤波[J]. 系统仿真学报, 2015, 27(11): 2741-2747.

Wu Jingjing, You Lihua, Wang Yao, Song Shujuan. Probability Hypothesis Density Filter Based on Adaptive Target Birth Intensity[J]. Journal of System Simulation, 2015, 27(11): 2741-2747.

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基于自适应新生目标强度的概率假设密度滤波

Probability Hypothesis Density Filter Based on Adaptive Target Birth Intensity

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