Abstract:
The paper is concerned with design of systems for successive simultaneous detection and estimation of stochastic signals with a priori uncertainty. Under certain conditions processing of the in up data is reducible to obtaining an estimate of a likelihood relation averaged in terms of unknown informative parameters $\lambda$ and its comparison with two ariable threshold which depend on accuracy in estimating the parameters $\lambda$ and with estimates of hindering parameters. An adaptive algorithm is found for detection and estimation of a Gaussian signal of unknown duration in white Gaussian noise.