A Bayesian Approach to Track Multiple Extended Targets Using Particle Filter for Nonlinear System

Han Yulan; Han Chongzhao

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A Bayesian Approach to Track Multiple Extended Targets Using Particle Filter for Nonlinear System

机译：非线性系统中使用粒子滤波的贝叶斯跟踪多个扩展目标的方法

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摘要

To track multiple extended targets for the nonlinear system, this paper employs the idea of the particle filter to track kinematic states and shape formation of extended targets. First, the Bayesian framework is proposed for multiple extended targets to jointly estimate multiple extended target state and association hypothesis. Furthermore, a joint proposal distribution is defined for the multiple extended target state and association hypothesis. Then, the Bayesian framework of multiple extended target tracking is implemented by the particle filtering which could release the high computational burden caused by the increase in the number of extended targets and measurements. Simulation results show that the proposed multiple extended target particle filter has superior performance in shape estimation and improves the performance of the position estimation in the situation that there are spatially closed extended targets.

机译：为了跟踪非线性系统的多个扩展目标，本文采用粒子滤波的思想来跟踪运动状态和扩展目标的形状形成。首先，提出了针对多个扩展目标的贝叶斯框架，以共同估计多个扩展目标状态和关联假设。此外，为多个扩展目标状态和关联假设定义了联合提议分布。然后，通过粒子滤波实现多重扩展目标跟踪的贝叶斯框架，该框架可以释放由于扩展目标和测量数量的增加而导致的高计算负担。仿真结果表明，所提出的多重扩展目标粒子滤波器在形状估计方面具有优越的性能，并且在空间上封闭的扩展目标情况下提高了位置估计的性能。

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《Mathematical Problems in Engineering》 |2018年第6期|7424538.1-7424538.10|共10页
作者
Han Yulan; Han Chongzhao;
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Ningxia Univ, Sch Phys & Elect Elect Engn, Ningxia 750021, Peoples R China;

Xi An Jiao Tong Univ, Sch Elect & Informat Engn, Xian 710049, Shaanxi, Peoples R China;

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1. A Bayesian Approach to Track Multiple Extended Targets Using Particle Filter for Nonlinear System [J] . Yulan Han, Chongzhao Han Mathematical Problems in Engineering: Theory, Methods and Applications . 2018,第a期

机译：一种追踪使用非线性系统粒子滤波器的多个扩展目标的贝叶斯方法
2. Recursive update filtering-based variational Bayesian approach for extended target or group target tracking with nonlinear measurements [J] . Liang Zhibing, Liu Fuxian, Fan Chengli Journal of electronic imaging . 2019,第3期

机译：基于递归更新滤波的变分贝叶斯方法用于非线性测量的扩展目标或组目标跟踪
3. Recursive update filtering-based variational Bayesian approach for extended target or group target tracking with nonlinear measurements [J] . Liang Zhibing, Liu Fuxian, Fan Chengli Journal of electronic imaging . 2019,第3期

机译：基于递归更新过滤的变分贝叶斯方法，用于扩展目标或基于非线性测量的目标跟踪
4. Multiple signal classification algorithm compensated by Extended Kalman Particle Filtering for Wi-Fi through wall multi-target tracking [C] . Khaled E. Ahmed, Kareem M. Attiah, Ahmed S. Eltrass Proceedings of the 2016 IEEE-APS Topical Conference on Antennas and Propagationin Wireless Communications . 2016

机译：通过墙多目标跟踪，采用扩展卡尔曼粒子滤波补偿Wi-Fi的多信号分类算法
5. Nonlinear filtering for stochastic hybrid and nonlinear systems with applications to target tracking. [D] . West, Philip Davidson. 1994

机译：随机混合和非线性系统的非线性滤波及其在目标跟踪中的应用。
6. An Improved Unscented Particle Filter Approach for Multi-Sensor Fusion Target Tracking [O] . Junhai Luo, Zhiyan Wang, Yanping Chen, 2020

机译：一种改进的多传感器融合目标跟踪的无编织颗粒滤波器方法
7. A Bayesian Approach to Track Multiple Extended Targets Using Particle Filter for Nonlinear System [O] . Yulan Han, Chongzhao Han 2018

机译：一种追踪使用非线性系统粒子滤波器的多个扩展目标的贝叶斯方法
8. Multiple Model Particle Filtering For Multi-Target Tracking [R] . Hero, A. , Kreucher, C. , Kastella, K. 2004

机译：多目标跟踪的多模型粒子滤波

A Bayesian Approach to Track Multiple Extended Targets Using Particle Filter for Nonlinear System

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