scholarly journals Random Finite Set Based Bayesian Filtering with OpenCL in a Heterogeneous Platform

Sensors ◽  
2017 ◽  
Vol 17 (4) ◽  
pp. 843 ◽  
Author(s):  
Biao Hu ◽  
Uzair Sharif ◽  
Rajat Koner ◽  
Guang Chen ◽  
Kai Huang ◽  
...  
Keyword(s):  
Bayesian Filtering ◽  
Heterogeneous Platform ◽  
Random Finite Set ◽  
Finite Set

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.

scholarly journals Bayesian Filtering With Random Finite Set Observations

2008 ◽  
Vol 56 (4) ◽  
pp. 1313-1326 ◽  
Author(s):  
Ba-Tuong Vo ◽  
Ba-Ngu Vo ◽  
Antonio Cantoni
Keyword(s):  
Bayesian Filtering ◽  
Random Finite Set ◽  
Finite Set

scholarly journals Relating Random Vector and Random Finite Set Estimation in Navigation, Mapping, and Tracking

2017 ◽  
Vol 65 (17) ◽  
pp. 4609-4623 ◽  
Author(s):  
Keith Y. K. Leung ◽  
Felipe Inostroza ◽  
Martin Adams
Keyword(s):  
Random Vector ◽  
Random Finite Set ◽  
Set Estimation ◽  
Finite Set
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