Constant false alarm rate detection of point targets using distributed sensors

The problem of orthogonalization of multiple satellite images, focusing at the same field of view, is studied in this paper for constant false alarm rate (CFAR) point target detection. Information fusion techniques are incorporated. The Karhunen-Loeve (K-L) orthogonalization method offers the best CFAR detection performance. However, it requires central fusion. It is shown that a version of the Gram-Schmidt (G-S) orthogonalization method, which preprocesses data in a pipeline form, offers a comparable CFAR detection to that of the K-L method. Point target CFAR detection is carried out by employing various fusion approaches on the orthogonal data. Sensor level fusion with quality information is shown to be preferable when the proposed sequential G-S orthogonalization is applied. The proposed CFAR approach is applied to dissimilar sensors and avoids overloading the communication channel transmitting only in the case of target detection. Trade-off studies and experimental results on real and simulated data are presented. (C) 1998 Society of Photo-Optical Instrumentation Engineers.