Algorithms for Estimating Signal Information Parameters under the Action of Broadband Non-Gaussian Noise

Abstract

This paper describes the synthesis of algorithms for estimating signal information parameters with noninertial nonlinear transformation of the input mixture of the signal and broadband non-Gaussian noise. There is also the analysis of algorithms optimal in the domain of small mismatch and quasioptimal algorithms, which are capable of operating in arbitrary mismatches between measured parameters and their estimates in the case of random signal/noise ratio at the gauge input. This work also presents the obtained basic estimated relations that help one determine the form of optimal amplitude characteristics of the nonlinear transformation unit, the quality of suppression of additive noise in a given unit with optimal and arbitrary amplitude characteristic, the steepness of the discrimination characteristic, and the value of the phase characteristic in the domain of small mismatches. It is shown that, by specifying the type of action and the transfer function of a smoothing chain, it is possible to determine the steady-state dynamic and fluctuation errors in a closed servo-system.