A Track-oriented Approach to Target Tracking with Random Finite Set Observations

2019 ◽  
Author(s):  
Tiancheng Li ◽  
Xiaoxu Wang ◽  
Yan Liang ◽  
Junkun Yan ◽  
Hongqi Fan
Keyword(s):  
Target Tracking ◽  
Random Finite Set ◽  
Finite Set ◽  
Oriented Approach

scholarly journals Time-Matching Random Finite Set-Based Filter for Radar Multi-Target Tracking

Sensors ◽  
2018 ◽  
Vol 18 (12) ◽  
pp. 4416 ◽  
Author(s):  
Defu Jiang ◽  
Ming Liu ◽  
Yiyue Gao ◽  
Yang Gao ◽  
Wei Fu ◽  
...  
Keyword(s):  
Target Tracking ◽  
Gaussian Mixture ◽  
Bayesian Filtering ◽  
Probability Hypothesis Density ◽  
Random Finite Set ◽  
Bayesian Formulation ◽  
Multi Target Tracking ◽  
Finite Set ◽  
Density Filter ◽  
Bernoulli Filter

The random finite set (RFS) approach provides an elegant Bayesian formulation of the multi-target tracking (MTT) problem without the requirement of explicit data association. In order to improve the performance of the RFS-based filter in radar MTT applications, this paper proposes a time-matching Bayesian filtering framework to deal with the problem caused by the diversity of target sampling times. Based on this framework, we develop a time-matching joint generalized labeled multi-Bernoulli filter and a time-matching probability hypothesis density filter. Simulations are performed by their Gaussian mixture implementations. The results show that the proposed approach can improve the accuracy of target state estimation, as well as the robustness.

Passive target tracking with intermittent measurement based on random finite set

2014 ◽  
Vol 21 (6) ◽  
pp. 2282-2291 ◽  
Author(s):  
Xiao-bo Luo ◽  
Hong-qi Fan ◽  
Zhi-yong Song ◽  
Qiang Fu
Keyword(s):  
Target Tracking ◽  
Random Finite Set ◽  
Finite Set ◽  
Passive Target Tracking ◽  
Intermittent Measurement
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