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• W2896724474 abstract "We consider the problem of Bayesian tracking of radar cross section. The adopted observation model employs the gamma family, which covers all Swerling cases in a unified framework. State dynamics are modeled using a nonstationary autoregressive gamma process. The principal component of the proposed solution is a nontrivial gamma approximation, applied during the time update recursion. The superior performance of the proposed approach is confirmed using simulations and a real-world dataset." @default.
• W2896724474 created "2018-10-26" @default.
• W2896724474 creator A5055766213 @default.
• W2896724474 date "2019-08-01" @default.
• W2896724474 modified "2023-09-26" @default.
• W2896724474 title "On Bayesian Tracking and Prediction of Radar Cross Section" @default.
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• W2896724474 doi "https://doi.org/10.1109/taes.2018.2875572" @default.
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