Multi-Bernoulli filtering with unknown clutter intensity and sensor field-of-view
In Bayesian multi-target filtering knowledge of parameters such as clutter intensity and sensor field-of-view are of critical importance. Significant mismatches in clutter and sensor field of view model parameters results in biased estimates. In this paper we propose a multi-target filtering solutio...
| Main Authors: | , , , |
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| Format: | Conference Paper |
| Published: |
2011
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| Online Access: | http://hdl.handle.net/20.500.11937/55205 |
| Summary: | In Bayesian multi-target filtering knowledge of parameters such as clutter intensity and sensor field-of-view are of critical importance. Significant mismatches in clutter and sensor field of view model parameters results in biased estimates. In this paper we propose a multi-target filtering solution that can accommodate non-linear target model and unknown non-homogeneous clutter intensity and sensor field-of-view. Our solution is based on the multi-target multi-Bernoulli filter that adaptively learns non-homogeneous clutter intensity and sensor field-of-view while filtering. © 2011 IEEE. |
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