Adaptive algorithm for detecting and evaluating the parameters of ultra-wideband signals against the background of interference in sub-bands based on a multidimensional biorthogonalizer filter

The problem of joint detection and estimation of parameters of ultra-wideband signals (UWB) in the presence of interference and noise is considered. The analysis of known adaptive algorithms for the formation of implemented signal estimation by the criterion of minimum root-mean-square error (RMS) has shown that in the case of receiving UWB signals, their main disadvantage is slow convergence, which prevents their use in location systems with UWB signals and large phased antenna arrays.

It is assumed that signals, interference and noise obey the Gaussian law of probability distribution. In the case of parametric a priori uncertainty, their covariance matrices are unknown and must be estimated, for example, by the method of direct inversion of the sample covariance matrix.