Locally optimum detection of discrete-time stochastic signals in non-Gaussian noise

Two basic models are considered for the problem of detecting small, zero-mean stochastic signals in non-Gaussian noise processes. Appying the theory of local tests, a general detector structure is derived for each of these models. A third (suboptimal) scheme based on null-zone detection is also proposed and a technique for optimizing its parameters is discussed. Using the criterion of asymptotic relative efficiency, the performance of these three detectors and of a power detector are compared under each of the proposed models.