Measurement Feedback Self-Tuning Weighted Measurement Fusion Kalman Filter for Systems with Correlated Noises
For the linear discrete stochastic systems with multiple sensors and unknown noise statistics, an online estimators of the noise variances and cross-covariances are designed by using measurement feedback, full-rank decomposition, and weighted least squares theory. Further, a self-tuning weighted me...
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| Format: | Article |
| Language: | English |
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Wiley
2012-01-01
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| Series: | Journal of Applied Mathematics |
| Online Access: | http://dx.doi.org/10.1155/2012/324296 |
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| _version_ | 1832555833168232448 |
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| author | Xin Wang Shu-Li Sun |
| author_facet | Xin Wang Shu-Li Sun |
| author_sort | Xin Wang |
| collection | DOAJ |
| description | For the linear discrete stochastic systems with multiple sensors and unknown noise statistics, an online estimators of the noise variances and cross-covariances are designed by using measurement feedback, full-rank decomposition, and weighted least squares theory. Further, a self-tuning weighted measurement fusion Kalman filter is presented. The Fadeeva formula is used to establish ARMA innovation model with unknown noise statistics. The sampling correlated function of the stationary and reversible ARMA innovation model is used to identify the noise statistics. It is proved that the presented self-tuning weighted measurement fusion Kalman filter converges to the optimal weighted measurement fusion Kalman filter, which means its asymptotic global optimality. The simulation result of radar-tracking system shows the effectiveness of the presented algorithm. |
| format | Article |
| id | doaj-art-a1df131a01cf481eb5860d656633244e |
| institution | Kabale University |
| issn | 1110-757X 1687-0042 |
| language | English |
| publishDate | 2012-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Applied Mathematics |
| spelling | doaj-art-a1df131a01cf481eb5860d656633244e2025-02-03T05:47:06ZengWileyJournal of Applied Mathematics1110-757X1687-00422012-01-01201210.1155/2012/324296324296Measurement Feedback Self-Tuning Weighted Measurement Fusion Kalman Filter for Systems with Correlated NoisesXin Wang0Shu-Li Sun1Department of Automation, Heilongjiang University, Harbin 150080, ChinaDepartment of Automation, Heilongjiang University, Harbin 150080, ChinaFor the linear discrete stochastic systems with multiple sensors and unknown noise statistics, an online estimators of the noise variances and cross-covariances are designed by using measurement feedback, full-rank decomposition, and weighted least squares theory. Further, a self-tuning weighted measurement fusion Kalman filter is presented. The Fadeeva formula is used to establish ARMA innovation model with unknown noise statistics. The sampling correlated function of the stationary and reversible ARMA innovation model is used to identify the noise statistics. It is proved that the presented self-tuning weighted measurement fusion Kalman filter converges to the optimal weighted measurement fusion Kalman filter, which means its asymptotic global optimality. The simulation result of radar-tracking system shows the effectiveness of the presented algorithm.http://dx.doi.org/10.1155/2012/324296 |
| spellingShingle | Xin Wang Shu-Li Sun Measurement Feedback Self-Tuning Weighted Measurement Fusion Kalman Filter for Systems with Correlated Noises Journal of Applied Mathematics |
| title | Measurement Feedback Self-Tuning Weighted Measurement Fusion Kalman Filter for Systems with Correlated Noises |
| title_full | Measurement Feedback Self-Tuning Weighted Measurement Fusion Kalman Filter for Systems with Correlated Noises |
| title_fullStr | Measurement Feedback Self-Tuning Weighted Measurement Fusion Kalman Filter for Systems with Correlated Noises |
| title_full_unstemmed | Measurement Feedback Self-Tuning Weighted Measurement Fusion Kalman Filter for Systems with Correlated Noises |
| title_short | Measurement Feedback Self-Tuning Weighted Measurement Fusion Kalman Filter for Systems with Correlated Noises |
| title_sort | measurement feedback self tuning weighted measurement fusion kalman filter for systems with correlated noises |
| url | http://dx.doi.org/10.1155/2012/324296 |
| work_keys_str_mv | AT xinwang measurementfeedbackselftuningweightedmeasurementfusionkalmanfilterforsystemswithcorrelatednoises AT shulisun measurementfeedbackselftuningweightedmeasurementfusionkalmanfilterforsystemswithcorrelatednoises |