An Adaptive Spatial Target Tracking Method Based on Unscented Kalman Filter
The spatial target motion model exhibits a high degree of nonlinearity. This leads to the fact that it is easy to diverge when the conventional Kalman filter is used to track the spatial target. The Unscented Kalman filter can be a good solution to this problem. This is because it conveys the statis...
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MDPI AG
2024-09-01
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| author | Dandi Rong Yi Wang |
| author_facet | Dandi Rong Yi Wang |
| author_sort | Dandi Rong |
| collection | DOAJ |
| description | The spatial target motion model exhibits a high degree of nonlinearity. This leads to the fact that it is easy to diverge when the conventional Kalman filter is used to track the spatial target. The Unscented Kalman filter can be a good solution to this problem. This is because it conveys the statistical properties of the state vector by selecting sampling points to be mapped through the nonlinear model. In practice, however, the measurement noise is often time-varying or unknown. In this case, the filtering accuracy of the Unscented Kalman filter will be reduced. In order to reduce the influence of time-varying measurement noise on the spatial target tracking, while accurately representing the a posteriori mean and covariance of the spatial target state vector, this paper proposes an adaptive noise factor method based on the Unscented Kalman filter to adaptively adjust the covariance matrix of the measurement noise. In this paper, numerical simulations are performed using measurement models from a space-based infrared satellite and a ground-based radar. It is experimentally demonstrated that the adaptive noise factor method can adapt to time-varying measurement noise and thus improve the accuracy of spatial target tracking compared to the Unscented Kalman filter. |
| format | Article |
| id | doaj-art-e22c6c0ef2be45719c26f91ee34c0210 |
| institution | OA Journals |
| issn | 1424-8220 |
| language | English |
| publishDate | 2024-09-01 |
| publisher | MDPI AG |
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| series | Sensors |
| spelling | doaj-art-e22c6c0ef2be45719c26f91ee34c02102025-08-20T01:55:51ZengMDPI AGSensors1424-82202024-09-012418609410.3390/s24186094An Adaptive Spatial Target Tracking Method Based on Unscented Kalman FilterDandi Rong0Yi Wang1Nanjing Research Institute of Electronics Technology, Nanjing 210039, ChinaNanjing Research Institute of Electronics Technology, Nanjing 210039, ChinaThe spatial target motion model exhibits a high degree of nonlinearity. This leads to the fact that it is easy to diverge when the conventional Kalman filter is used to track the spatial target. The Unscented Kalman filter can be a good solution to this problem. This is because it conveys the statistical properties of the state vector by selecting sampling points to be mapped through the nonlinear model. In practice, however, the measurement noise is often time-varying or unknown. In this case, the filtering accuracy of the Unscented Kalman filter will be reduced. In order to reduce the influence of time-varying measurement noise on the spatial target tracking, while accurately representing the a posteriori mean and covariance of the spatial target state vector, this paper proposes an adaptive noise factor method based on the Unscented Kalman filter to adaptively adjust the covariance matrix of the measurement noise. In this paper, numerical simulations are performed using measurement models from a space-based infrared satellite and a ground-based radar. It is experimentally demonstrated that the adaptive noise factor method can adapt to time-varying measurement noise and thus improve the accuracy of spatial target tracking compared to the Unscented Kalman filter.https://www.mdpi.com/1424-8220/24/18/6094spatial target trackingUnscented Kalman filteradaptive noise factorcooperation of the space-based infrared satellite and ground-based radar |
| spellingShingle | Dandi Rong Yi Wang An Adaptive Spatial Target Tracking Method Based on Unscented Kalman Filter Sensors spatial target tracking Unscented Kalman filter adaptive noise factor cooperation of the space-based infrared satellite and ground-based radar |
| title | An Adaptive Spatial Target Tracking Method Based on Unscented Kalman Filter |
| title_full | An Adaptive Spatial Target Tracking Method Based on Unscented Kalman Filter |
| title_fullStr | An Adaptive Spatial Target Tracking Method Based on Unscented Kalman Filter |
| title_full_unstemmed | An Adaptive Spatial Target Tracking Method Based on Unscented Kalman Filter |
| title_short | An Adaptive Spatial Target Tracking Method Based on Unscented Kalman Filter |
| title_sort | adaptive spatial target tracking method based on unscented kalman filter |
| topic | spatial target tracking Unscented Kalman filter adaptive noise factor cooperation of the space-based infrared satellite and ground-based radar |
| url | https://www.mdpi.com/1424-8220/24/18/6094 |
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