Distributed Fusion for Multisensor Systems With Censored Measurements Under Round-Robin Protocol

In this paper, distributed fusion is investigated for a multisensor system affected by censored measurements and packet dropout. A Round-Robin protocol is proposed to alleviate communication burden and avoid packet collisions in communication networks with packet dropout. A local estimator with Round-Robin protocol is designed to acquire local estimates for the multisensor system under censored measurements and packet dropout. A distributed fusion algorithm is introduced to enhance estimation accuracy using a fast covariance intersection fusion (FCIF) method. Sufficient conditions on the designed local estimator are given to guarantee the boundedness of estimation error covariance matrix. A numerical example and an experiment are given to demonstrate effectiveness of the proposed algorithm.

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Publication Details

Journal
IEEE Sensors Journal
Published
2025-04-17
DOI
https://doi.org/10.1109/jsen.2025.3560117
Citations
3
Primary Topic
Target Tracking and Data Fusion in Sensor Networks
Type
article
Field-Weighted Citation Impact
7.44

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article

Distributed Fusion for Multisensor Systems With Censored Measurements Under Round-Robin Protocol

Ling Zhao, Guanyu Chen, Xinyue Cao, Li Li
3 citations
IEEE Sensors Journal
Target Tracking and Data Fusion in Sensor Networks
7.44
article

Distributed Fusion for Multisensor Systems With Censored Measurements Under Round-Robin Protocol

Ling Zhao, Guanyu Chen, Xinyue Cao, Li Li
article en
3 citations

Abstract

In this paper, distributed fusion is investigated for a multisensor system affected by censored measurements and packet dropout. A Round-Robin protocol is proposed to alleviate communication burden and avoid packet collisions in communication networks with packet dropout. A local estimator with Round-Robin protocol is designed to acquire local estimates for the multisensor system under censored measurements and packet dropout. A distributed fusion algorithm is introduced to enhance estimation accuracy using a fast covariance intersection fusion (FCIF) method. Sufficient conditions on the designed local estimator are given to guarantee the boundedness of estimation error covariance matrix. A numerical example and an experiment are given to demonstrate effectiveness of the proposed algorithm.

IEEE Sensors JournalVol. 25(11)
Tianjin University (CN), Yanshan University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 4%
Target Tracking and Data Fusion in Sensor Networks
7.44
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Distributed Fusion for Multisensor Systems With Censored Measurements Under Round-Robin Protocol — Ling Zhao, Guanyu Chen, et al. · IEEE Sensors Journal (2025) | TGRS Research Map | TGRS