Application of the local Markov approximation method for the analysis of information processes processing algorithms with unknown discontinuous parameters under violation of the consistency property of their estimates

Abstract

We considered the local Markov approximation method for the definition of the precision characteristics of statistical analysis algorithms of information processes 6268 O. V. Chernoyarov et al. under inconsistent estimate of their unknown discontinuous parameters and in the presence of Gaussian distortions. By two visual examples we illustrated the use of the stated approach in practical applications for the analysis of operating efficiency of detectors and measurers of the quasi-deterministic and random signals.

Adaptive detection and time and power parameters estimation of the low-frequency random pulse with inexactly known duration against white and correlated hindrances

“…For the determination of applicability borders of found asymptotically exact formulas for detection and estimation characteristics the statistical computer modeling of quasi-likelihood receivers action was carried out. During modeling, following a technique stated in [7]…”

“…Let us suppose that the value δ is such that expressions (17) can be approximated by dominant terms of asymptotic decompositions with required accuracy. Then, on the basis of results [7], it is possible to write down the approximate expressions for conditional (under fixed…”

“…(19), that characteristics of the normalized QLE (9) adapted to the unknown value are conditional bias and variance of the anomalous estimate. According to [6,7], if condition (21) is satisfied, then…”