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Intelligent CFAR processor based on data variability

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2 Author(s)
M. E. Smith ; Sensis Corp., DeWitt, NY, USA ; P. K. Varshney

An intelligent constant false alarm rate (CFAR) processor to perform adaptive threshold target detection is presented. It employs a composite approach based on the well-known cell averaging CFAR (CA-CFAR), smallest of CFAR (SO-CFAR), and greatest of CFAR (GO-CFAR) processors. Data in the reference window is used to compute a second-order statistic called the variability index (VI) and the ratio of the means of the leading and lagging windows. Based on these statistics, the VI-CFAR dynamically tailors the background estimation algorithm. The VI-CFAR processor provides low loss CFAR performance in a homogeneous environment and also performs robustly in nonhomogeneous environments including multiple targets and extended clutter edges

Published in:

IEEE Transactions on Aerospace and Electronic Systems  (Volume:36 ,  Issue: 3 )