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Descripción
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| The fully adaptive radar framework aims to use the available information from the scenario in which a system is deployed to adaptively change its configuration with the intention of achieving a performance improvement. The use of this strategy relies on an optimization procedure, usually based on the minimization of the predicted conditional Crame?r-Rao lower bound, which in some difficult scenarios can result in misperformance of the system due to a lack of robustness. In this paper, we present a novel approach based on a linear-Gaussian approximation, to carry out the optimization procedure inherent in the fully adaptive radar framework that successfully avoids these robustness issues. This method can be easily implemented using sigma-point integration methods. We demonstrate the performance of the proposed approach through simulations in a single target tracking scenario using a sensor network. | |
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Internacional
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Si |
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Nombre congreso
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2018 IEEE Radar Conference (RadarConf18). |
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Tipo de participación
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960 |
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Lugar del congreso
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Oklahoma, USA. |
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Revisores
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Si |
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ISBN o ISSN
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2375-5318 |
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DOI
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10.1109/RADAR.2018.8378568 |
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Fecha inicio congreso
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23/04/2018 |
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Fecha fin congreso
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27/04/2018 |
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Desde la página
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1 |
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Hasta la página
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6 |
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Título de las actas
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Proceedings 2018 IEEE Radar Conference (RadarConf18). |