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Adaptive Fusion Design Using Multiscale Unscented Kalman Filter Approach for Multisensor Data Fusion
Joint Authors
Source
Mathematical Problems in Engineering
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-11-23
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
In order to improve the reliability of measurement data, the multisensor data fusion technology has progressed greatly in improving the accuracy of measurement data.
This paper utilizes the real-time, recursive, and optimal estimation characteristics of unscented Kalman filter (UKF), as well as the unique advantages of multiscale wavelet transform decomposition in data analysis to effectively integrate observational data from multiple sensors.
A new multiscale UKF-based multisensor data fusion algorithm is proposed by combining the UKF with multiscale signal analysis.
Firstly, model-based UKF is introduced into the multiple sensors, and then the model is decomposed at multiple scales onto the coarse scale with wavelets.
Next, signals decomposed from fine to coarse scales are adjusted using the denoised observational data from corresponding sensors and reconstructed with wavelets to obtain the fused signals.
Finally, the processed data are fused using adaptive weighted fusion algorithm.
Comparison of simulation and experimental results shows that the proposed method can effectively improve the antijamming capability of the measurement system and ensure the reliability and accuracy of sensor measurement system compared to the use of data fusion algorithm alone.
American Psychological Association (APA)
Wang, Huadong& Dong, Shi. 2015. Adaptive Fusion Design Using Multiscale Unscented Kalman Filter Approach for Multisensor Data Fusion. Mathematical Problems in Engineering،Vol. 2015, no. 2015, pp.1-10.
https://search.emarefa.net/detail/BIM-1074899
Modern Language Association (MLA)
Wang, Huadong& Dong, Shi. Adaptive Fusion Design Using Multiscale Unscented Kalman Filter Approach for Multisensor Data Fusion. Mathematical Problems in Engineering No. 2015 (2015), pp.1-10.
https://search.emarefa.net/detail/BIM-1074899
American Medical Association (AMA)
Wang, Huadong& Dong, Shi. Adaptive Fusion Design Using Multiscale Unscented Kalman Filter Approach for Multisensor Data Fusion. Mathematical Problems in Engineering. 2015. Vol. 2015, no. 2015, pp.1-10.
https://search.emarefa.net/detail/BIM-1074899
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1074899