Tracking moving targets in wireless sensor networks using extended diffusion strategies of distributed Kalman filter
Using wireless sensor networks to track the position of a moving object in a 3-D spatial model requires precise information of location and speed of the object, which in turn demands for accuracy in state estimation of distributed Kalman filter. In view of reducing the impacts of noise in the dynami...
| Main Authors: | , , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
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IEEE
2013
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| Online Access: | http://psasir.upm.edu.my/id/eprint/44810/ http://psasir.upm.edu.my/id/eprint/44810/1/Tracking%20moving%20targets%20in%20wireless%20sensor%20networks%20using%20extended%20diffusion%20strategies%20of%20distributed%20Kalman%20filter.pdf |
| _version_ | 1848850460669116416 |
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| author | Solouk, Vahid Taghizadeh, Hamid Moghanjoughi, Ayyoub Akbari Razm, S. K. |
| author_facet | Solouk, Vahid Taghizadeh, Hamid Moghanjoughi, Ayyoub Akbari Razm, S. K. |
| author_sort | Solouk, Vahid |
| building | UPM Institutional Repository |
| collection | Online Access |
| description | Using wireless sensor networks to track the position of a moving object in a 3-D spatial model requires precise information of location and speed of the object, which in turn demands for accuracy in state estimation of distributed Kalman filter. In view of reducing the impacts of noise in the dynamic linear system and achieve optimized state estimate, the current study proposes extended strategies of Kalman filter diffusion based on distributed Kalman filter. Through the proposed strategies, each node communicates merely with its neighbor nodes. The data aggregation is done in a set of neighborhood using instructions of recursive Kalman filter iterations with specific weights. The proposed algorithms provide precise state estimates in a moment as global state estimates using various updates at each step. As a simulation study, we applied the algorithms in a network to track the position and speed of a projectile and compared the results with real world circumstances, using the concept of transient mean square deviations of network as a cost function. The results report improvements over the conventional methods in terms of mean square errors. |
| first_indexed | 2025-11-15T10:06:39Z |
| format | Conference or Workshop Item |
| id | upm-44810 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T10:06:39Z |
| publishDate | 2013 |
| publisher | IEEE |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-448102020-08-04T02:32:18Z http://psasir.upm.edu.my/id/eprint/44810/ Tracking moving targets in wireless sensor networks using extended diffusion strategies of distributed Kalman filter Solouk, Vahid Taghizadeh, Hamid Moghanjoughi, Ayyoub Akbari Razm, S. K. Using wireless sensor networks to track the position of a moving object in a 3-D spatial model requires precise information of location and speed of the object, which in turn demands for accuracy in state estimation of distributed Kalman filter. In view of reducing the impacts of noise in the dynamic linear system and achieve optimized state estimate, the current study proposes extended strategies of Kalman filter diffusion based on distributed Kalman filter. Through the proposed strategies, each node communicates merely with its neighbor nodes. The data aggregation is done in a set of neighborhood using instructions of recursive Kalman filter iterations with specific weights. The proposed algorithms provide precise state estimates in a moment as global state estimates using various updates at each step. As a simulation study, we applied the algorithms in a network to track the position and speed of a projectile and compared the results with real world circumstances, using the concept of transient mean square deviations of network as a cost function. The results report improvements over the conventional methods in terms of mean square errors. IEEE 2013 Conference or Workshop Item PeerReviewed text en http://psasir.upm.edu.my/id/eprint/44810/1/Tracking%20moving%20targets%20in%20wireless%20sensor%20networks%20using%20extended%20diffusion%20strategies%20of%20distributed%20Kalman%20filter.pdf Solouk, Vahid and Taghizadeh, Hamid and Moghanjoughi, Ayyoub Akbari and Razm, S. K. (2013) Tracking moving targets in wireless sensor networks using extended diffusion strategies of distributed Kalman filter. In: 2013 IEEE 11th Malaysia International Conference on Communications (MICC), 26-28 Nov. 2013, Kuala Lumpur, Malaysia. (pp. 213-216). 10.1109/MICC.2013.6805827 |
| spellingShingle | Solouk, Vahid Taghizadeh, Hamid Moghanjoughi, Ayyoub Akbari Razm, S. K. Tracking moving targets in wireless sensor networks using extended diffusion strategies of distributed Kalman filter |
| title | Tracking moving targets in wireless sensor networks using extended diffusion strategies of distributed Kalman filter |
| title_full | Tracking moving targets in wireless sensor networks using extended diffusion strategies of distributed Kalman filter |
| title_fullStr | Tracking moving targets in wireless sensor networks using extended diffusion strategies of distributed Kalman filter |
| title_full_unstemmed | Tracking moving targets in wireless sensor networks using extended diffusion strategies of distributed Kalman filter |
| title_short | Tracking moving targets in wireless sensor networks using extended diffusion strategies of distributed Kalman filter |
| title_sort | tracking moving targets in wireless sensor networks using extended diffusion strategies of distributed kalman filter |
| url | http://psasir.upm.edu.my/id/eprint/44810/ http://psasir.upm.edu.my/id/eprint/44810/ http://psasir.upm.edu.my/id/eprint/44810/1/Tracking%20moving%20targets%20in%20wireless%20sensor%20networks%20using%20extended%20diffusion%20strategies%20of%20distributed%20Kalman%20filter.pdf |