Title :
Distributed cell-averaging CFAR detection in dependent sensors
Author :
Blum, Rick S. ; Kassam, Saleem A.
Author_Institution :
Dept. of Comput. Sci. & Electr. Eng., Lehigh Univ., Bethlehem, PA, USA
fDate :
3/1/1995 12:00:00 AM
Abstract :
Constant false alarm rate detection is considered in a decentralized, two-sensor context. Cases with observations which are dependent from sensor to sensor are investigated, for which results have been lacking. The in-phase and quadrature components of the received narrowband observation at each sensor consist of a common weak random signal in additive Gaussian combined clutter and noise. The sensors use cell-averaging CFAR tests to each generate binary decisions which are sent to a fusion center. Optimal sensor thresholds are found and the performance of the best schemes using AND and OR fusion rules are compared. The ability of these schemes to maintain constant false alarm probability in the presence of clutter edges is also studied
Keywords :
Gaussian noise; clutter; sensor fusion; signal detection; AND fusion rules; OR fusion rules; additive Gaussian clutter; additive Gaussian noise; binary decisions; clutter edges; constant false alarm rate detection; decentralized two-sensor context; dependent sensors; distributed cell-averaging CFAR detection; in-phase component; optimal sensor thresholds; quadrature components; received narrowband observation; weak random signal; Additive noise; Detectors; Fusion power generation; Gaussian noise; Matched filters; Narrowband; Sensor fusion; Signal detection; Signal to noise ratio; Testing;
Journal_Title :
Information Theory, IEEE Transactions on