Multi-target Tracking Based on AI-AP-PHD Filter

TAN Shuncheng; HAN Fanglin; YU Hongbo

doi:10.15892/j.cnki.djzdxb.2021.04.020

Journal of Projectiles, Rockets, Missiles and Guidance >

2021 , Vol. 41 >Issue 4: 90 - 94

DOI: https://doi.org/10.15892/j.cnki.djzdxb.2021.04.020

Multi-target Tracking Based on AI-AP-PHD Filter

TAN Shuncheng ¹^,² ,
HAN Fanglin ¹ ,
YU Hongbo ¹

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¹ Institute of Information Fusion Technology, Naval Aeronautical University, Shandong Yantai 264001, China
² Nanjing Research Institute of Electronic Technology, Nanjing 210039, China

Received date: 2020-11-04

Online published: 2025-02-13

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Abstract

The amplitude information of target can provide more accurate target and false-alarm likelihoods, which can be used to improve the performance of multi-target detection and tracking. In this paper, a practical and feasible auxiliary particle probability hypothesis density filter combined with target amplitude information (AI-AP-PHD) is proposed. Firstly, the target state vector and measurement vector are expanded, and then the extended dynamic equation and measurement equation are used to realize the prediction and update of system, the number and state estimation of multi-target are given simultaneously in the end. The simulation results show that the proposed method is very suitable for the situation of unknown target SNR, and perform well than the traditional PHD filter method.

Key words： auxiliary particle filter; probability hypothesis density filter; amplitude information

Cite this article

TAN Shuncheng , HAN Fanglin , YU Hongbo . Multi-target Tracking Based on AI-AP-PHD Filter[J]. Journal of Projectiles, Rockets, Missiles and Guidance, 2021 , 41(4) : 90 -94 . DOI: 10.15892/j.cnki.djzdxb.2021.04.020

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