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• W2312911457 abstract "In this paper, we propose a new tractable Bernoulli filter based on the random matrix framework to track an extended target in an ultra-wideband (UWB) sensor network. The resulting filter jointly tracks the kinematic and shape parameters of the target and is called the extended target Gaussian inverse Wishart Bernoulli (ET-GIW-Ber) filter. Closed form expressions for the ET-GIW-Ber filter recursions are presented. A clustering step is inserted into the measurement update stage in order to have a computationally tractable filter. In addition, a new method that is consistent with the applied clustering method is embedded into the filter recursions in order to adaptively estimate the time-varying number of measurements of the extended target. The simulation results demonstrate the robust and effective performance of the proposed filter. Furthermore, real data collected from a UWB sensor network are used to assess the performance of the proposed filter. It is shown that the proposed filter yields a very promising performance in estimation of the kinematic and shape parameters of the target." @default.
• W2312911457 created "2016-06-24" @default.
• W2312911457 creator A5028365375 @default.
• W2312911457 creator A5051895263 @default.
• W2312911457 date "2016-06-01" @default.
• W2312911457 modified "2023-09-27" @default.
• W2312911457 title "A Bernoulli Filter for Extended Target Tracking Using Random Matrices in a UWB Sensor Network" @default.
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• W2312911457 doi "https://doi.org/10.1109/jsen.2016.2544807" @default.
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