GAME-THEORETIC SYNTHESIS OF OPTIMAL LINEAR SIGNAL-FILTERING SYSTEMS

Optimal linear filtering (OLF) of signals, which is widely employed in communications systems, enables the lowest mean square error to be ac hieved in cases where signals, interference, and communications channe ls take a Gaussian form. Optimal linear, Kolmogorov-Wiener filters mus t have complex frequency responses (CFR) proportional to the complex-c onjugate spectrum of the received signal and inversely proportional to the analogous interference spectrum to achieve such an error. However , the probability characteristics of the useful signal and interferenc e are not always known a priori to the designer of an optimal linear f ilter (LF), i.e., a priori uncertainty may exist. Moreover, in certain cases, a conflict situation may arise between operators of the inform ation transmission systems (ITS) and the radio jamming system (RJS). T he latter corresponds to the operation of an ITS under conditions of r adio countermeasures (radio masking). In this connection, it is intere sting to synthesize OLF systems based on a game-theoretic approach.