Stability Analysis of Multi-Sensor Kalman Filtering over Lossy Networks
This paper studies the remote Kalman filtering problem for a distributed system setting with multiple sensors that are located at different physical locations. Each sensor encapsulates its own measurement data into one single packet and transmits the packet to the remote filter via a lossy distinct...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2016-04-01
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| Series: | Sensors |
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| Online Access: | http://www.mdpi.com/1424-8220/16/4/566 |
| _version_ | 1811262875654684672 |
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| author | Shouwan Gao Pengpeng Chen Dan Huang Qiang Niu |
| author_facet | Shouwan Gao Pengpeng Chen Dan Huang Qiang Niu |
| author_sort | Shouwan Gao |
| collection | DOAJ |
| description | This paper studies the remote Kalman filtering problem for a distributed system setting with multiple sensors that are located at different physical locations. Each sensor encapsulates its own measurement data into one single packet and transmits the packet to the remote filter via a lossy distinct channel. For each communication channel, a time-homogeneous Markov chain is used to model the normal operating condition of packet delivery and losses. Based on the Markov model, a necessary and sufficient condition is obtained, which can guarantee the stability of the mean estimation error covariance. Especially, the stability condition is explicitly expressed as a simple inequality whose parameters are the spectral radius of the system state matrix and transition probabilities of the Markov chains. In contrast to the existing related results, our method imposes less restrictive conditions on systems. Finally, the results are illustrated by simulation examples. |
| first_indexed | 2024-04-12T19:34:41Z |
| format | Article |
| id | doaj.art-dca0e2e5b60a400298a629c71f750e05 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-12T19:34:41Z |
| publishDate | 2016-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-dca0e2e5b60a400298a629c71f750e052022-12-22T03:19:15ZengMDPI AGSensors1424-82202016-04-0116456610.3390/s16040566s16040566Stability Analysis of Multi-Sensor Kalman Filtering over Lossy NetworksShouwan Gao0Pengpeng Chen1Dan Huang2Qiang Niu3Key Laboratory of Gas and Fire Control for Coal Mines, China University of Mining and Technology, Xuzhou 221116, ChinaSchool of Computer Science and Technology, China University of Mining and Technology, Xuzhou 221116, ChinaSchool of Computer Science and Technology, China University of Mining and Technology, Xuzhou 221116, ChinaSchool of Computer Science and Technology, China University of Mining and Technology, Xuzhou 221116, ChinaThis paper studies the remote Kalman filtering problem for a distributed system setting with multiple sensors that are located at different physical locations. Each sensor encapsulates its own measurement data into one single packet and transmits the packet to the remote filter via a lossy distinct channel. For each communication channel, a time-homogeneous Markov chain is used to model the normal operating condition of packet delivery and losses. Based on the Markov model, a necessary and sufficient condition is obtained, which can guarantee the stability of the mean estimation error covariance. Especially, the stability condition is explicitly expressed as a simple inequality whose parameters are the spectral radius of the system state matrix and transition probabilities of the Markov chains. In contrast to the existing related results, our method imposes less restrictive conditions on systems. Finally, the results are illustrated by simulation examples.http://www.mdpi.com/1424-8220/16/4/566Kalman filteringpacket lossesdistributed sensingstability analysisMarkov process |
| spellingShingle | Shouwan Gao Pengpeng Chen Dan Huang Qiang Niu Stability Analysis of Multi-Sensor Kalman Filtering over Lossy Networks Sensors Kalman filtering packet losses distributed sensing stability analysis Markov process |
| title | Stability Analysis of Multi-Sensor Kalman Filtering over Lossy Networks |
| title_full | Stability Analysis of Multi-Sensor Kalman Filtering over Lossy Networks |
| title_fullStr | Stability Analysis of Multi-Sensor Kalman Filtering over Lossy Networks |
| title_full_unstemmed | Stability Analysis of Multi-Sensor Kalman Filtering over Lossy Networks |
| title_short | Stability Analysis of Multi-Sensor Kalman Filtering over Lossy Networks |
| title_sort | stability analysis of multi sensor kalman filtering over lossy networks |
| topic | Kalman filtering packet losses distributed sensing stability analysis Markov process |
| url | http://www.mdpi.com/1424-8220/16/4/566 |
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