Evaluation of CFAR and texture based target detection statistics on SAR imagery

In this work, we evaluated the effectiveness of synthetic aperture radar (SAR) target detection algorithms that consist of any number of combinations of three statistics which include two-parameter CFAR, variance, and extended fractal features. The performance of these algorithms were tested at various threshold settings over the public domain MSTAR database. This database contains one foot resolution X-band SAR imagery. Receiver-operating-characteristic (ROC) curves were generated for the seven resulting algorithms. The results indicate that the CFAR statistic is the least effective detection statistic