Centralised Fusion of Cooperative Sensors With Limited Field of View for Multiple Resolvable Group Targets Tracking

ABSTRACT The coordinated deployment of multi‐sensor systems significantly enhances group target detection capabilities, yet persistent tracking remains challenging due to inherent limitations in single‐sensor field of view (FoV) coverage. This paper proposes a novel labelled multi‐Bernoulli (LMB) filter for resolvable group target (RGT) tracking under the centralised fusion (CF) framework, abbreviated as the CF‐LMB‐RGT filter. The proposed method introduces the virtual leader kinematic model to capture intra‐group motion constraints and incorporates group structure undirected graph into the LMB recursion for interaction prediction. A key innovation lies in the Kullback–Leibler divergence minimised fusion rule that optimally integrates local posteriors within joint FoV regions while explicitly modelling common FoV overlaps, enabling complementary information fusion across nonoverlapping sensor FoVs. Simulation results demonstrate that our method achieves impressive tracking accuracy for RGTs by integrating information from all sensors.

Authors

Institutions

Publication Details

Journal
IET Radar Sonar & Navigation
Published
2025-01-01
DOI
https://doi.org/10.1049/rsn2.70032
Primary Topic
Target Tracking and Data Fusion in Sensor Networks
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Centralised Fusion of Cooperative Sensors With Limited Field of View for Multiple Resolvable Group Targets Tracking

Jikun Ye, Daozhi Wei, Ruining Luo, Changxin Luo et al.
IET Radar Sonar & Navigation
Target Tracking and Data Fusion in Sensor Networks
article

Centralised Fusion of Cooperative Sensors With Limited Field of View for Multiple Resolvable Group Targets Tracking

Jikun Ye, Daozhi Wei, Ruining Luo, Changxin Luo, Xirui Xue, Shucai Huang, Ning Li
article en

Abstract

ABSTRACT The coordinated deployment of multi‐sensor systems significantly enhances group target detection capabilities, yet persistent tracking remains challenging due to inherent limitations in single‐sensor field of view (FoV) coverage. This paper proposes a novel labelled multi‐Bernoulli (LMB) filter for resolvable group target (RGT) tracking under the centralised fusion (CF) framework, abbreviated as the CF‐LMB‐RGT filter. The proposed method introduces the virtual leader kinematic model to capture intra‐group motion constraints and incorporates group structure undirected graph into the LMB recursion for interaction prediction. A key innovation lies in the Kullback–Leibler divergence minimised fusion rule that optimally integrates local posteriors within joint FoV regions while explicitly modelling common FoV overlaps, enabling complementary information fusion across nonoverlapping sensor FoVs. Simulation results demonstrate that our method achieves impressive tracking accuracy for RGTs by integrating information from all sensors.

IET Radar Sonar & NavigationVol. 19(1)
Air Force Engineering University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 95%
Target Tracking and Data Fusion in Sensor Networks
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.