Open AccessCPHD Tracking Algorithm Based on BPF for Multiple Group Targets
Author(s) -
Yiduo Guo,
Jian Gong,
Qian Gao
Publication year - 2019
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1325/1/012145
Subject(s) - tracking (education) , clutter , algorithm , particle filter , group (periodic table) , computer science , filter (signal processing) , computer vision , radar , telecommunications , psychology , pedagogy , chemistry , organic chemistry
Aim to solve the tracking of multiple group targets in strong clutter environment, a rectangular box is used to deal with extension state of group targets. Combining the box particle filter algorithm and the cardinalized probability hypothesis density (CPHD) algorithm, a CPHD algorithm for multiple group targets tracking based on box particle filter (BPF), which is called BPF-CPHD, is proposed in this paper. Compared with the existed algorithm of multiple group targets tracking, the proposed algorithm can improve the tracking accuracy and efficiency greatly. Simulation results confirm the effectiveness of the BPF-CPHD.