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.
On Bayesian Tracking and Prediction of Radar Cross Section
IEEE Transactions on Aerospace and Electronic Systems ; 55 , 4 ; 1756-1768
2019-08-01
1142957 byte
Article (Journal)
Electronic Resource
English
Radar cross-section: measurement, prediction and control
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