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Conference Papers Year : 2011

Multi-Sensor PHD: Construction and Implementation by Space Partitioning

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Emmanuel Delande
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  • PersonId : 873501
Emmanuel Duflos
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  • PersonId : 844358
Philippe Vanheeghe
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  • PersonId : 838038

Abstract

The Probability Hypothesis Density (PHD) is a well-known method for single-sensor multi-target tracking problems in a Bayesian framework, but the extension to the multi-sensor case seems to remain a challenge. In this paper, an extension of Mahler's work to the multi-sensor case provides an expression of the true PHD multi-sensor data update equation. Then, based on the configuration of the sensors' fields of view (FOVs), a joint partitioning of both the sensors and the state space provides an equivalent yet more practical expression of the data update equation, allowing a more effective implementation in specific FOV configurations.
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Dates and versions

hal-00639724 , version 1 (09-11-2011)

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Emmanuel Delande, Emmanuel Duflos, Philippe Vanheeghe, Dominique Heurguier. Multi-Sensor PHD: Construction and Implementation by Space Partitioning. International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2011, May 2011, Prague, Czech Republic. pp.3632 - 3635, ⟨10.1109/ICASSP.2011.5947137⟩. ⟨hal-00639724⟩
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