Distributed Multi-Sensor Fusion for Multi-Group/Extended Target Tracking with Different Limited Fields of View

The identification of sensing group targets and extended targets is of paramount importance in the context of vehicle tracking and early warning detection. As the scope of target monitoring and tracking extends, conventional single-sensor-based tracking techniques are proving to be inadequate in mee...

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Bibliographic Details
Published inApplied sciences Vol. 14; no. 21; p. 9627
Main Authors Xiong, Chao, Hu, Moufa, Lu, Huanzhang, Zhao, Fei
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 01.11.2024
Subjects
Algorithms
distributed fusion
Distributed processing
group/extended target
Hypotheses
Information processing
Kinematics
limited FOV
Methods
PMBM
Sensors
Simulation methods
WAA
WGA
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Summary:The identification of sensing group targets and extended targets is of paramount importance in the context of vehicle tracking and early warning detection. As the scope of target monitoring and tracking extends, conventional single-sensor-based tracking techniques are proving to be inadequate in meeting the practical demands of the field. Consequently, multi-sensor fusion tracking technology has emerged as a viable alternative. However, the use of multiple sensors is constrained by their limited fields of view (FOVs), which leads to issues such as the loss of target detection and the introduction of false targets after fusion. Hence, this study proposes a combination of weighted geometric averaging (WGA) and weighted arithmetic averaging (WAA) methods to solve distributed multi-group/extended target tracking with different fields of view. Specifically, a local Poisson multi-Bernoulli mixture (PMBM) filter was first used on individual sensors. Subsequently, we combined a sequential fusion technique and the proposed fusion approach to fuse the PMBM filter densities. The efficacy and superiority of this approach were demonstrated through simulations.
ISSN:2076-3417
2076-3417
DOI:10.3390/app14219627