On the multichannel innovations based detection algorithm for correlated non-Gaussian random processes

The paper addresses the problem of multichannel signal detection in additive correlated non-Gaussian noise using the innovations approach. Spherically invariant random processes (SIRP) are used for modeling the additive non-Gaussian noise phenomena. The resulting innovations based detector is shown to be canonical for SIRPs. An autoregressive process of order two [AR(2)] is used to approximate the SIRPs. The effect of estimated AR parameters on the performance of the innovations based detector is presented.<<ETX>>