Distributed Fusion Receding Horizon Filtering in Linear Stochastic Systems
This paper presents a distributed receding horizon filtering algorithm for multisensor continuous-time linear stochastic systems. Distributed fusion with a weighted sum structure is applied to local receding horizon Kalman filters having different horizon lengths. The fusion estimate of the state of...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
SpringerOpen
2009-01-01
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| Series: | EURASIP Journal on Advances in Signal Processing |
| Online Access: | http://dx.doi.org/10.1155/2009/929535 |
| _version_ | 1811315031184244736 |
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| author | Il Young Song Du Yong Kim Yong Hoon Kim Suk Jae Lee Vladimir Shin |
| author_facet | Il Young Song Du Yong Kim Yong Hoon Kim Suk Jae Lee Vladimir Shin |
| author_sort | Il Young Song |
| collection | DOAJ |
| description | This paper presents a distributed receding horizon filtering algorithm for multisensor continuous-time linear stochastic systems. Distributed fusion with a weighted sum structure is applied to local receding horizon Kalman filters having different horizon lengths. The fusion estimate of the state of a dynamic system represents the optimal linear fusion by weighting matrices under the minimum mean square error criterion. The key contribution of this paper lies in the derivation of the differential equations for determining the error cross-covariances between the local receding horizon Kalman filters. The subsequent application of the proposed distributed filter to a linear dynamic system within a multisensor environment demonstrates its effectiveness. |
| first_indexed | 2024-04-13T11:22:58Z |
| format | Article |
| id | doaj.art-5a1d0c9757d5488b853362812a1634f6 |
| institution | Directory Open Access Journal |
| issn | 1687-6172 1687-6180 |
| language | English |
| last_indexed | 2024-04-13T11:22:58Z |
| publishDate | 2009-01-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | EURASIP Journal on Advances in Signal Processing |
| spelling | doaj.art-5a1d0c9757d5488b853362812a1634f62022-12-22T02:48:46ZengSpringerOpenEURASIP Journal on Advances in Signal Processing1687-61721687-61802009-01-01200910.1155/2009/929535Distributed Fusion Receding Horizon Filtering in Linear Stochastic SystemsIl Young SongDu Yong KimYong Hoon KimSuk Jae LeeVladimir ShinThis paper presents a distributed receding horizon filtering algorithm for multisensor continuous-time linear stochastic systems. Distributed fusion with a weighted sum structure is applied to local receding horizon Kalman filters having different horizon lengths. The fusion estimate of the state of a dynamic system represents the optimal linear fusion by weighting matrices under the minimum mean square error criterion. The key contribution of this paper lies in the derivation of the differential equations for determining the error cross-covariances between the local receding horizon Kalman filters. The subsequent application of the proposed distributed filter to a linear dynamic system within a multisensor environment demonstrates its effectiveness.http://dx.doi.org/10.1155/2009/929535 |
| spellingShingle | Il Young Song Du Yong Kim Yong Hoon Kim Suk Jae Lee Vladimir Shin Distributed Fusion Receding Horizon Filtering in Linear Stochastic Systems EURASIP Journal on Advances in Signal Processing |
| title | Distributed Fusion Receding Horizon Filtering in Linear Stochastic Systems |
| title_full | Distributed Fusion Receding Horizon Filtering in Linear Stochastic Systems |
| title_fullStr | Distributed Fusion Receding Horizon Filtering in Linear Stochastic Systems |
| title_full_unstemmed | Distributed Fusion Receding Horizon Filtering in Linear Stochastic Systems |
| title_short | Distributed Fusion Receding Horizon Filtering in Linear Stochastic Systems |
| title_sort | distributed fusion receding horizon filtering in linear stochastic systems |
| url | http://dx.doi.org/10.1155/2009/929535 |
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