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ABORT-like detectors: a Bayesian approach

Bandiera, Francesco and Besson, Olivier and Coluccia, Angelo and Ricci, Giuseppe ABORT-like detectors: a Bayesian approach. (2015) IEEE Transactions on Signal Processing, 36 (19). 5274-5284. ISSN 1053-587X

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Official URL: http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=7140829&tag=1

Abstract

In this paper, we deal with the problem of adaptive radar detection of point-like targets in presence of noise with unknown spectral properties. As customary, we assume that a set of data sharing the same properties of the noise in the cell under test is available. To cope with a limited number of training data, a Bayesian framework is adopted at the design stage. In order to come up with detectors with good rejection capabilities, the possible presence of a fictitious signal under the null hypothesis is modeled probabilistically, as opposite to the conventional ABORT-like approach. Several detectors are devised for the problem at hand, with different complexities. The performance assessment, conducted by means of Monte Carlo simulations, reveals that a good trade-off between detection power and selectivity can be achieved, even assuming a limited number of training data.

Item Type:Article
Additional Information:Thanks to IEEE Xplore editor. The definitive version is available at http://ieeexplore.ieee.org/Xplore/home.jsp The original PDF of the article can be found at Signal Processing, IEEE Transactions on website : http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=7140829&tag=1
HAL Id:hal-01925407
Audience (journal):International peer-reviewed journal
Uncontrolled Keywords:
Institution:Université de Toulouse > Institut Supérieur de l'Aéronautique et de l'Espace - ISAE-SUPAERO (FRANCE)
Other partners > Università del Salento (ITALY)
Laboratory name:
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Deposited By: Olivier Besson
Deposited On:08 Sep 2015 15:20

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