Labeled particle unresolved target PHD filter for multiple group target tracking

Author(s):  
Yunxiang Li Yunxiang Li ◽  
Huaitie Xiao Huaitie Xiao ◽  
Hao Wu Hao Wu ◽  
Rui Hu Rui Hu ◽  
Qiang Fu Qiang Fu
Author(s):  
Louis Guerlin ◽  
Benjamin Pannetier ◽  
Michèle Rombaut ◽  
Maxime Derome
Keyword(s):  

2017 ◽  
Vol 2017 ◽  
pp. 1-9
Author(s):  
Linhai Gan ◽  
Gang Wang

The random matrix (RM) method is widely applied for group target tracking. The assumption that the group extension keeps invariant in conventional RM method is not yet valid, as the orientation of the group varies rapidly while it is maneuvering; thus, a new approach with group extension predicted is derived here. To match the group maneuvering, a best model augmentation (BMA) method is introduced. The existing BMA method uses a fixed basic model set, which may lead to a poor performance when it could not ensure basic coverage of true motion modes. Here, a maneuvering group target tracking algorithm is proposed, where the group extension prediction and the BMA adaption are exploited. The performance of the proposed algorithm will be illustrated by simulation.


Sensors ◽  
2019 ◽  
Vol 19 (6) ◽  
pp. 1307
Author(s):  
Weifeng Liu ◽  
Yudong Chi

In this paper, multiple resolvable group target tracking was considered in the frame of random finite sets. In particular, a group target model was introduced by combining graph theory with the labeled random finite sets (RFS). This accounted for dependence between group members. Simulations were presented to verify the proposed algorithm.


2017 ◽  
Author(s):  
Wen-dong Geng ◽  
Yuan-qin Wang ◽  
Zheng-hong Dong
Keyword(s):  

2001 ◽  
Author(s):  
Firooz A. Sadjadi ◽  
Wolfgang Kober

Sign in / Sign up

Export Citation Format

Share Document