Distributed Box Particle Filtering for Target Tracking in Sensor Networks
Distributed target tracking is a significant technique and is widely used in many applications. Combined with the interval analysis, box particle filtering (BPF) has been proposed to solve the problem of Bayesian filtering when the uncertainties in the measurements are intervals; that is, the measur...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Wiley
2015-07-01
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| Series: | International Journal of Distributed Sensor Networks |
| Online Access: | https://doi.org/10.1155/2015/829013 |
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| _version_ | 1832547793443487744 |
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| author | Ying Liu Hao Liu |
| author_facet | Ying Liu Hao Liu |
| author_sort | Ying Liu |
| collection | DOAJ |
| description | Distributed target tracking is a significant technique and is widely used in many applications. Combined with the interval analysis, box particle filtering (BPF) has been proposed to solve the problem of Bayesian filtering when the uncertainties in the measurements are intervals; that is, the measurements are interval-based vectors. This paper is targeted for extending the existing BPF based on a single sensor to a distributed sensor network. We propose a distributed BPF (d-BPF) that each sensor communicates with its direct neighbors to collaboratively estimate the states of the target. The feasibility of the proposed distributed BPF is justified, and some numerical simulations are presented to show its effectiveness in target tracking. |
| format | Article |
| id | doaj-art-9880a7cf6a5e4b1497c3c88545f31450 |
| institution | Kabale University |
| issn | 1550-1477 |
| language | English |
| publishDate | 2015-07-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Distributed Sensor Networks |
| spelling | doaj-art-9880a7cf6a5e4b1497c3c88545f314502025-02-03T06:43:17ZengWileyInternational Journal of Distributed Sensor Networks1550-14772015-07-011110.1155/2015/829013829013Distributed Box Particle Filtering for Target Tracking in Sensor NetworksYing LiuHao LiuDistributed target tracking is a significant technique and is widely used in many applications. Combined with the interval analysis, box particle filtering (BPF) has been proposed to solve the problem of Bayesian filtering when the uncertainties in the measurements are intervals; that is, the measurements are interval-based vectors. This paper is targeted for extending the existing BPF based on a single sensor to a distributed sensor network. We propose a distributed BPF (d-BPF) that each sensor communicates with its direct neighbors to collaboratively estimate the states of the target. The feasibility of the proposed distributed BPF is justified, and some numerical simulations are presented to show its effectiveness in target tracking.https://doi.org/10.1155/2015/829013 |
| spellingShingle | Ying Liu Hao Liu Distributed Box Particle Filtering for Target Tracking in Sensor Networks International Journal of Distributed Sensor Networks |
| title | Distributed Box Particle Filtering for Target Tracking in Sensor Networks |
| title_full | Distributed Box Particle Filtering for Target Tracking in Sensor Networks |
| title_fullStr | Distributed Box Particle Filtering for Target Tracking in Sensor Networks |
| title_full_unstemmed | Distributed Box Particle Filtering for Target Tracking in Sensor Networks |
| title_short | Distributed Box Particle Filtering for Target Tracking in Sensor Networks |
| title_sort | distributed box particle filtering for target tracking in sensor networks |
| url | https://doi.org/10.1155/2015/829013 |
| work_keys_str_mv | AT yingliu distributedboxparticlefilteringfortargettrackinginsensornetworks AT haoliu distributedboxparticlefilteringfortargettrackinginsensornetworks |