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Robust Autonomous Detection of the Faulty Sensors of a Sensor Array
Ghosh, S.   Freitas, A.   Marshall, I.  
Comput. Lab., Univ. of Kent Canterbury, Canterbury;

This paper appears in: Computational Advances in Multi-Sensor Adaptive Processing, 2007. CAMPSAP 2007. 2nd IEEE International Workshop on
Publication Date: 12-14 Dec. 2007
On page(s): 233-236
Location: St. Thomas, VI,
ISBN: 978-1-4244-1713-1
INSPEC Accession Number: 9967751
Digital Object Identifier: 10.1109/CAMSAP.2007.4498008
Current Version Published: 2008-04-25

Abstract
We propose a technique for the autonomous detection of the faulty sensors of a sensor array that are aberrant relative to the rest. Our approach is based on probabilistically modeling the distribution of the differences between the sensor measurements as a mixture of Gaussians and then classifying further instances of the sensor differences using a naive Bayes classifier. We demonstrate the applicability of this technique to the diagnosis of the sensors/photosites of a CCD array, using sensor array data comprising of randomly selected images. Our technique performs well for different combinations of parameter settings at the detection of the faulty photosites of a CCD array.

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