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2 results on '"Persymmetric disturbance"'

1. On the Maximal Invariant Statistic for Adaptive Radar Detection in Partially Homogeneous Disturbance With Persymmetric Covariance.

Author

Ciuonzo, D., Orlando, D., and Pallotta, L.

Subjects
ADAPTIVE signal detection, GAUSSIAN processes, COVARIANCE matrices
Abstract

This letter deals with the problem of adaptive signal detection in partially homogeneous and persymmetric Gaussian disturbance within the framework of invariance theory. First, a suitable group of transformations leaving the problem invariant is introduced and the maximal invariant statistic (MIS) is derived. Then, it is shown that the (two-step) generalized-likelihood ratio test, Rao, and Wald tests can be all expressed in terms of the MIS, thus proving that they all ensure a constant false-alarm rate. [ABSTRACT FROM PUBLISHER]

Published
2016
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2. On the maximal invariant statistic for adaptive radar detection in partially homogeneous disturbance with persymmetric covariance

Author

Luca Pallotta, Domenico Ciuonzo, Danilo Orlando, Ciuonzo, D., Orlando, D., and Pallotta, L.

Subjects
FOS: Computer and information sciences, Computer Science - Information Theory, Gaussian, 02 engineering and technology, symbols.namesake, 0203 mechanical engineering, Constant false-alarm rate (CFAR), 0202 electrical engineering, electronic engineering, information engineering, Applied mathematics, Symmetric matrix, Detection theory, Maximal invariant, Electrical and Electronic Engineering, Statistic, Mathematics, 020301 aerospace & aeronautics, Information Theory (cs.IT), Applied Mathematics, Ratio test, Persymmetric disturbance, 020206 networking & telecommunications, Adaptive radar detection, Covariance, Invariant (physics), Invariance theory, Signal Processing, symbols, Partially homogeneous disturbance, Constant (mathematics)
Abstract

This letter deals with the problem of adaptive signal detection in partially-homogeneous and persymmetric Gaussian disturbance within the framework of invariance theory. First, a suitable group of transformations leaving the problem invariant is introduced and the Maximal Invariant Statistic (MIS) is derived. Then, it is shown that the (Two-step) Generalized-Likelihood Ratio test, Rao and Wald tests can be all expressed in terms of the MIS, thus proving that they all ensure a Constant False-Alarm Rate (CFAR)., Comment: submitted for journal publication

Published
2016

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