On Bayesian Tracking and Prediction of Radar Cross Section

Michał Meller

doi:10.1109/taes.2018.2875572

On Bayesian Tracking and Prediction of Radar Cross Section

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 realworld dataset.

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Michał Meller dr hab. inż.

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Publication version: Accepted or Published Version
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Category:: Articles
Type:: artykuł w czasopiśmie wyróżnionym w JCR
Published in:: IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS no. 55, pages 1756 - 1768,
ISSN: 0018-9251
Language:: English
Publication year:: 2018
Bibliographic description:: Meller M.: On Bayesian Tracking and Prediction of Radar Cross Section// IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS. -Vol. 55, iss. 4 (2018), s.1756-1768
DOI:: Digital Object Identifier (open in new tab) 10.1109/taes.2018.2875572
Verified by:: Gdańsk University of Technology