Multi-Bernoulli filter based sensor selection with limited sensing range for multi-target tracking
In this paper, we consider a sensor network with limited sensing range and present a sensor selection algorithm for multi-target tracking problem. The proposed algorithm is based on the multi-Bernoulli filtering and a collection of sub-selection problems for individual target. A sub-selection proble...
| Main Authors: | , , |
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| Format: | Conference Paper |
| Published: |
2015
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| Online Access: | http://hdl.handle.net/20.500.11937/14146 |
| Summary: | In this paper, we consider a sensor network with limited sensing range and present a sensor selection algorithm for multi-target tracking problem. The proposed algorithm is based on the multi-Bernoulli filtering and a collection of sub-selection problems for individual target. A sub-selection problem for each target is investigated under the framework of partially observed Markov decision process. Each sub-selection problem is solved using a combination of information theoretic method and limited sensing range. Numerical studies validate the effectiveness of our method for multi-target tracking scenario in a sensor network. |
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