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Distributed Fusion of Labeled Multi-Bernoulli Filters Based on Arithmetic Average
- Source :
- IEEE Signal Processing Letters; 2024, Vol. 31 Issue: 1 p656-660, 5p
- Publication Year :
- 2024
-
Abstract
- This letter considers the distributed fusion for Labeled Multi-Bernoulli (LMB) filters under the multi-sensor multi-target tracking scenario. In practice, a novel fusion method that combines the label-free strategy with the fusion method based on the Arithmetic Average (AA) is proposed. Firstly, the label-free version of the LMB posterior is obtained. Then, the corresponding Probability Hypothesis Density (PHD) is acquired and fused by the merging-based PHD-AA fusion method. Finally, the labels of the fused distributions are reassigned. The simulation shows that the distributed LMB filter using the proposed fusion method can achieve more accurate multi-target state estimates with relatively low computational burden under clutter and missed detection environment compared to other existing methods.
Details
- Language :
- English
- ISSN :
- 10709908 and 15582361
- Volume :
- 31
- Issue :
- 1
- Database :
- Supplemental Index
- Journal :
- IEEE Signal Processing Letters
- Publication Type :
- Periodical
- Accession number :
- ejs65705207
- Full Text :
- https://doi.org/10.1109/LSP.2024.3364506