Fully Distributed Dynamic Adaptive Weighted Fusion Method For Sensors Network

This paper addresses an adaptive cooperative measurement problem for a class of multi-sensors systems. The main issue of this paper is to develop an optimal information weighted Kalman consensus filter, so that the states estimation can achieve convergence while ensuring the global optimal accuracy...

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Bibliographic Details
Published in2022 41st Chinese Control Conference (CCC) pp. 4819 - 4824
Main Authors Zilun, Hu, Jianying, Yang
Format Conference Proceeding
LanguageEnglish
Published Technical Committee on Control Theory, Chinese Association of Automation 25.07.2022
Subjects
Adaptive Information Fusion
Adaptive systems
Distributed Optimization
Filtering theory
Information filters
Kalman Filter
Real-time systems
Robustness
Sensor fusion
Sensor systems
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Summary:This paper addresses an adaptive cooperative measurement problem for a class of multi-sensors systems. The main issue of this paper is to develop an optimal information weighted Kalman consensus filter, so that the states estimation can achieve convergence while ensuring the global optimal accuracy for the multi-sensors system by using the distributed estimation scheme. According to the graph theory, it is proved that the proposed method can achieve a better estimation while optimizing the performance of the global system. Finally, a numerical example is provided to show the effectiveness of the proposed method.
ISSN:2161-2927
DOI:10.23919/CCC55666.2022.9902852