Adaptive detection of point-like targets in environment with orthogonal rejection

摘要: This paper deals with the problem of detecting point-like targets in presence Gaussian disturbance unknown covariance matrix. We consider a situation where environment is partially homogeneous, i.e., primary and secondary data share same structure matrix but different power level. Moreover, we assume that cell under test (CUT) contains fictitious signal orthogonal to nominal steering vector null hypothesis. Under above assumptions, devise an adaptive detector based on generalized likelihood ratio (GLRT). Interestingly, it shown proposed coincides well known coherence estimator (ACE). result provides alternative explanation good selectivity properties exhibited by ACE.