An Improved Volume Information Particle Filtering Multi-targetTracking Algorithm

ZHAO  Yihuan; CHEN  Wei; LIU  Zhe; SHEN  Kang

doi:10.15892/j.cnki.djzdxb.2017.04.005

Journal of Projectiles, Rockets, Missiles and Guidance >

2017 , Vol. 37 >Issue 4: 19 - 22

DOI: https://doi.org/10.15892/j.cnki.djzdxb.2017.04.005

MISSILES AND GUIDANCE TECHNOLOGY

An Improved Volume Information Particle Filtering Multi-targetTracking Algorithm

ZHAO Yihuan ,
CHEN Wei ,
LIU Zhe ,
SHEN Kang

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1 China Airborn Missile Academy, Henan Luoyang 471009, China
2 Space Star Technology Co. Ltd, Beijing 100086, China
3 School of Electronics Information Engineering, BUAA, Beijing 100191, China

Received date: 2016-07-19

Online published: 2025-05-28

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Abstract

In order to solve the problem such as particle degeneration and poor tracking accuracy presented by traditional bootstrap particle filter adopting state transition density as importance sampling function, in this paper, the posterior probability was used as the importance sampling function and its estimation method was proposed. By means of volume information filtering and Gating technology, the mean and variance of importance sampling function were estimated, and the importance sampling function was designed. With the improved particle filter method, the states and numbers of targets were estimated in nonlinear scenario. The simulation results demonstrated that the proposed algorithm had the advantages of high tracking accuracy and good stability in the nonlinear multi-target tracking scenario.

Key words： bootstrap particle filtering; importance sampling function; volume information filtering; Gating technology

Cite this article

ZHAO Yihuan , CHEN Wei , LIU Zhe , SHEN Kang . An Improved Volume Information Particle Filtering Multi-targetTracking Algorithm[J]. Journal of Projectiles, Rockets, Missiles and Guidance, 2017 , 37(4) : 19 -22 . DOI: 10.15892/j.cnki.djzdxb.2017.04.005

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