Performance limits of the innovations-based detection algorithm

A theoretical evaluation of the performance limits of the innovations-based detection algorithm, which provides an adaptive algorithm for discriminating between two hypotheses parameterized as autoregressive (AR) models, is presented. Two particular cases are considered. One pertains to a situation in which the variance of the interference (modeled as an AR process) acting alone is known a priori. The other pertains to a situation in which no such knowledge is available. Detailed computer simulations are carried out to confirm the practical validity of the theory.<
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