JOURNAL ARTICLE

Active and dynamic multi-sensor information fusion method based on Dynamic Bayesian Networks

Abstract

In order to improve the dynamic optimization capability and fault-tolerant ability of the information fusion method for multi-sensor system, the theory of Dynamic Bayesian Networks was used to rebuild the conventional Federated Kalman Filter in this paper, and a new kind of active and dynamic information fusion and optimization method for multi-sensor systems under high-dynamic situation was proposed. The simulation results indicated the high dynamic flexibility and fault-tolerant ability of the proposed method.

Keywords:
Dynamic Bayesian network Kalman filter Computer science Flexibility (engineering) Sensor fusion Bayesian probability Fault tolerance Information fusion Fusion Fault (geology) Artificial intelligence Distributed computing Mathematics

Metrics

6
Cited By
0.76
FWCI (Field Weighted Citation Impact)
10
Refs
0.85
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Bayesian Modeling and Causal Inference
Physical Sciences →  Computer Science →  Artificial Intelligence
Target Tracking and Data Fusion in Sensor Networks
Physical Sciences →  Computer Science →  Artificial Intelligence
Fault Detection and Control Systems
Physical Sciences →  Engineering →  Control and Systems Engineering
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