Abstract
Constant false alarm rate (CFAR) detection techniques have been of much interest in radar and sonar applications. In this paper we consider CFAR detection in a decentralized, multisensor context and show some interesting characteristics of cell averaging (CA) in this setting. We investigate cases with observations which are dependent from sensor to sensor, for which results have been lacking. The in-phase and quadrature components of the received narrowband observation at each sensor consist of a weak random signal in additive clutter and noise. Each sensor transmits a single binary decision to a fusion center which uses either an AND or an OR fusion rule to develop a final decision. The forms of the best sensor detector rules are found and a set of necessary conditions are given for their thresholds. Solutions are obtained for some representative cases and their detection probability performance is studied. Their ability to maintain constant false alarm probability in the face of clutter edges is also studied. We show that solutions which use different fusion rules may excel for each of these different criteria.
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