Method for dealing with non-stationary natural and simulating interference in intellectual surveillance radars

The article discusses a method for dealing with non-stationary natural and simulating interference in intelligent surveillance radars. When creating simulating marks, the introduction of amplitude modulation into the relayed radar sounding signal is used. As a result of the analysis, it was possible to find out that in the imitating noise, in this case, the so-called "intelligent" fluctuations of the burst structure of false marks appear, which differ from the fluctuations of the packs of real marks and can be easily detected by a human operator. The method is based on the definition of semantic components at the stage of formation and analysis of a symbolic model of amplitude fluctuations of a burst of signals from non-stationary natural and simulating interference and from real moving objects. In this case, the semantic features of amplitude fluctuations are determined by solving predicate equations for transforming these fluctuations into symbolic images of noise marks and real mobile aircraft. As a result of semantic analysis of the amplitude fluctuations of the burst in the time domain, classification distinctive features of fluctuations in the burst of signals from natural imitating noise and air objects were obtained. The semantic components of the decision-making algorithm are investigated, which are similar to the decision-making algorithms by a human operator. Process knowledge of transforming radar signals into symbolic images of amplitude fluctuations of a burst in the time domain is formalized. The formalization of the processing of symbolic images includes a system of predicate equations, by solving which the types of amplitude fluctuations of the burst are identified. Based on the results of experimental data, the transformations of real radar signals into symbolic images of burst fluctuations were carried out on the basis of the algebra of finite predicates. The authors also managed to propose these transformations to be used as the basis of an effective toolkit for obtaining classification distinctive features of packet fluctuations from interference and from aircraft.