The constant false alarm rate (CFAR) detection algorithm considered by Chen and Reed is generalized to a test which is able to detect the presence of a known optical signal pattern which has nonnegligible unknown relative intensities in several signal-plus-noise bands or channels. This new test and its statistics are analytically evaluated and the signal-to-noise ratio (SNR) performance improvement is analyzed. Both theoretical and computer simulation results show that the SNR improvement factor of this new algorithm using multiple band scenes over the single scene of maximum SNR can be substantial. The SNR gain of this new detection algorithm and the one given by Chen and Reed are compared. It illustrates that the GSNR of the test using the full data array is always greater than that of using a partial data array. The data base used to simulate this new adaptive CFAR test is obtained from actual LANDS AT image scenes. The present results for optical detection are extendable to radar target detection and to other related detection problems. © 1990 IEEE
