Resolvable Group State Estimation with Maneuver Movement Based on Labeled RFS

2018 ◽  
Author(s):  
Yudong Chi ◽  
Weifeng Liu
Keyword(s):  
State Estimation ◽  
Resolvable Group

scholarly journals Resolvable Group State Estimation with Maneuver Based on Labeled RFS and Graph Theory

Sensors ◽  
2019 ◽  
Vol 19 (6) ◽  
pp. 1307
Author(s):  
Weifeng Liu ◽  
Yudong Chi
Keyword(s):  
Graph Theory ◽  
State Estimation ◽  
Target Tracking ◽  
Finite Sets ◽  
Target Model ◽  
Group Members ◽  
Group Target ◽  
Random Finite Sets ◽  
Resolvable Group

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.

scholarly journals A Detection and Tracking Algorithm for Resolvable Group with Structural and Formation Changes Using the Gibbs-GLMB Filter

Sensors ◽  
2020 ◽  
Vol 20 (12) ◽  
pp. 3384 ◽  
Author(s):  
Xinfeng Ru ◽  
Yudong Chi ◽  
Weifeng Liu
Keyword(s):  
State Estimation ◽  
Target Tracking ◽  
Tracking Error ◽  
Relevant Information ◽  
The State ◽  
Tracking Algorithm ◽  
Detection And Tracking ◽  
Group Target ◽  
Resolvable Group

In the field of resolvable group target tracking, further study on the structure and formation of group targets is helpful to reduce the tracking error of group bluetargets. In this paper, we propose an algorithm to detect whether the structure or formation state of group targets changes. In this paper, a Gibbs Generalized Labeled Multi-Bernoulli (GLMB) filter is used to obtain the estimation of discernible group target bluestates. After obtaining the state estimation of the group target, we extract relevant information based on the estimation data to judge whether the structure or formation state has changed. Finally, several experiments are carried out to verify the algorithm.

Two-level state estimation for large power system. Part 1: Algorithms

1988 ◽  
Vol 135 (4) ◽  
pp. 299 ◽  
Author(s):  
K.L. Lo ◽  
M.M. Salem ◽  
R.D. McColl ◽  
A.M. Moffatt
Keyword(s):  
Power System ◽  
State Estimation ◽  
Large Power ◽  
System Part
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