Non-Ellipsoidal Infrared Group/Extended Target Tracking Based on Poisson Multi-Bernoulli Mixture Filter and B-Spline

被引:12
|
作者
Wang, Yi [1 ,2 ,3 ]
Chen, Xin [1 ,2 ]
Gong, Chao [1 ,2 ,3 ]
Rao, Peng [1 ,2 ]
机构
[1] Chinese Acad Sci, Shanghai Inst Tech Phys, Shanghai 200083, Peoples R China
[2] Chinese Acad Sci, Key Lab Intelligent Infrared Percept, Shanghai 200083, Peoples R China
[3] Univ Chinese Acad Sci, Beijing 100049, Peoples R China
基金
中国国家自然科学基金;
关键词
extended; group target tracking; B-spline; Poisson multi-Bernoulli mixture filter; amplitude; measurement partition; PROBABILITY HYPOTHESIS DENSITY; RANDOM FINITE SETS; EXTENDED OBJECT; PHD FILTER; DERIVATION; MODEL;
D O I
10.3390/rs15030606
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
This study provides a solution for multiple group/extended target tracking with an arbitrary shape. Many tracking approaches for extended/group targets have been proposed. However, these approaches make assumptions about the target shape, which have limitations in practical applications. To address this problem, in this work, an extended/group target tracking algorithm based on B-spline is proposed. Specifically, the extension of an extended or a group target was modeled as a spatial probability distribution characterized by the control points of a B-spline function that was then jointly propagated with the measurement rate model and kinematic component model over time using the Poisson multi-Bernoulli mixture (PMBM) filter framework. In addition, an amplitude-aided measurement partitioning approach is proposed to improve the accuracy caused by distance-based approaches. The simulation results demonstrate that the extension, shape and orientation of targets can be estimated better by the proposed algorithm, even if the shape changes. The tracking performance is also improved by about 10% and 13% compared to the other two algorithms.
引用
收藏
页数:22
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