A parametric multichannel detection algorithm for correlated non-Gaussian random processes

This paper addresses the problem of adaptive multichannel signal detection in additive correlated non-Gaussian noise using a parametric model-based approach. The adaptive signal detection problem has been addressed extensively for the case of additive Gaussian noise. However, the corresponding problem for the non-Gaussian case has received limited attention. The additive non-Gaussian noise is assumed to be modeled by a spherically invariant random process (SIRP). The innovations based detection algorithm for the case of constant signal with unknown complex amplitude is derived. The resulting receiver structure is shown to be equivalent to an adaptive matched filter compared to a data dependent threshold. Performance analysis of the derived receiver for the case of a K-distributed SIRV is presented.