Measurement-converted Kalman filter tracking with Gaussian intensity attenuation signal in wireless sensor networks
In this article, the target tracking problem in a wireless sensor network with nonlinear Gaussian signal intensity attenuation model is considered. A Bayesian filter tracking algorithm is presented to estimate the locations of moving source that has unknown central signal intensity. This approach ad...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2017-04-01
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| Series: | International Journal of Distributed Sensor Networks |
| Online Access: | https://doi.org/10.1177/1550147717700896 |
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| _version_ | 1849685353023143936 |
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| author | Sha Wen Liqiang Xing Xiaoqing Hu Hui Zhang |
| author_facet | Sha Wen Liqiang Xing Xiaoqing Hu Hui Zhang |
| author_sort | Sha Wen |
| collection | DOAJ |
| description | In this article, the target tracking problem in a wireless sensor network with nonlinear Gaussian signal intensity attenuation model is considered. A Bayesian filter tracking algorithm is presented to estimate the locations of moving source that has unknown central signal intensity. This approach adopts a measurement conversion method to remove the measurement nonlinearity by the maximum likelihood estimator, and a linear estimate of the target position and its associated noise statistics obtained by the Newton–Raphson iterative optimization steps are applied into the standard Kalman filter. The Monte Carlo simulations have been conducted in comparison with the commonly used extended Kalman filter with an augmented state that consists of both the original target state and the augmentative central signal intensity. It is observed that the proposed measurement-converted Kalman filter can yield higher accurate estimate and nicer convergence performance over existing methods. |
| format | Article |
| id | doaj-art-c3c3a1f89c4f4b85a70528ee5ec3d90a |
| institution | DOAJ |
| issn | 1550-1477 |
| language | English |
| publishDate | 2017-04-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Distributed Sensor Networks |
| spelling | doaj-art-c3c3a1f89c4f4b85a70528ee5ec3d90a2025-08-20T03:23:11ZengWileyInternational Journal of Distributed Sensor Networks1550-14772017-04-011310.1177/1550147717700896Measurement-converted Kalman filter tracking with Gaussian intensity attenuation signal in wireless sensor networksSha Wen0Liqiang Xing1Xiaoqing Hu2Hui Zhang3Electronic Technology Information Research Institute, Ministry of Industry and Information Technology of China, Beijing, ChinaChina National Institute of Standardization (CNIS), Beijing, ChinaInstitute of Acoustics, Chinese Academy of Sciences, Beijing, ChinaDepartment of Engineering Physics, Tsinghua University, Beijing, China Sha Wen, China National Institute of Standardization (CNIS), Beijing 100191, ChinaIn this article, the target tracking problem in a wireless sensor network with nonlinear Gaussian signal intensity attenuation model is considered. A Bayesian filter tracking algorithm is presented to estimate the locations of moving source that has unknown central signal intensity. This approach adopts a measurement conversion method to remove the measurement nonlinearity by the maximum likelihood estimator, and a linear estimate of the target position and its associated noise statistics obtained by the Newton–Raphson iterative optimization steps are applied into the standard Kalman filter. The Monte Carlo simulations have been conducted in comparison with the commonly used extended Kalman filter with an augmented state that consists of both the original target state and the augmentative central signal intensity. It is observed that the proposed measurement-converted Kalman filter can yield higher accurate estimate and nicer convergence performance over existing methods.https://doi.org/10.1177/1550147717700896 |
| spellingShingle | Sha Wen Liqiang Xing Xiaoqing Hu Hui Zhang Measurement-converted Kalman filter tracking with Gaussian intensity attenuation signal in wireless sensor networks International Journal of Distributed Sensor Networks |
| title | Measurement-converted Kalman filter tracking with Gaussian intensity attenuation signal in wireless sensor networks |
| title_full | Measurement-converted Kalman filter tracking with Gaussian intensity attenuation signal in wireless sensor networks |
| title_fullStr | Measurement-converted Kalman filter tracking with Gaussian intensity attenuation signal in wireless sensor networks |
| title_full_unstemmed | Measurement-converted Kalman filter tracking with Gaussian intensity attenuation signal in wireless sensor networks |
| title_short | Measurement-converted Kalman filter tracking with Gaussian intensity attenuation signal in wireless sensor networks |
| title_sort | measurement converted kalman filter tracking with gaussian intensity attenuation signal in wireless sensor networks |
| url | https://doi.org/10.1177/1550147717700896 |
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