Adaptive linear-quadratic array for detection

Results for an arbitrary linear-quadratic (LQ) array structure are presented. For this purpose, knowledge of the statistical properties of the noise up to the fourth order is needed. Unfortunately, in most situations of practical interest the latter information is not available a priori and must be estimated. Three adaptive algorithms which are extensions of the well-known sample matrix inversion (SMI), recursive matrix inversion (RMI), and Frost algorithms are then developed for the real-time computation of the optimal LQ array processor. The study of the numerical complexity of these algorithms is discussed