Probability Hypothesis Density Filter Based on Adaptive Target Birth Intensity

Authors

Jingjing Wu, 1. School of Mechanical Engineering, Jiangnan University, Wuxi 214122, China; ;2. Jiangsu Key Laboratory of Advanced Food Manufacturing Equipment and Technology, Wuxi 214122, China;
Lihua You, 1. School of Mechanical Engineering, Jiangnan University, Wuxi 214122, China; ;2. Jiangsu Key Laboratory of Advanced Food Manufacturing Equipment and Technology, Wuxi 214122, China;
Wang Yao, 1. School of Mechanical Engineering, Jiangnan University, Wuxi 214122, China; ;
Shujuan Song, 1. School of Mechanical Engineering, Jiangnan University, Wuxi 214122, China; ;

Abstract

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.

Recommended Citation

Wu, Jingjing; You, Lihua; Yao, Wang; and Song, Shujuan (2020) "Probability Hypothesis Density Filter Based on Adaptive Target Birth Intensity," Journal of System Simulation: Vol. 27: Iss. 11, Article 17.
Available at: https://dc-china-simulation.researchcommons.org/journal/vol27/iss11/17

First Page

2741

Revised Date

2014-12-20

DOI Link

https://doi.org/

Last Page

2747

CLC

TP391

Recommended Citation

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.