Evaluation of radar image processing efficiency based on intelligent analysis of processes

Abstract

The paper presents results of development of the method and experimental studies of the system for automatic detection of radar signals of aerial objects and their recognition with the processing of real records in surveillance radars. The relevance of this work consists in creation of algorithms for automatic information processing to ensure effective detection of useful signals due to accumulation of signal (energy) and semantic information. The method is based on the definition of semantic components at the stage of formation and analysis of the symbolic model of signals from point and extended air objects. Signal information is described by the predicate function of process knowledge of the formation and analysis of a symbolic model of a burst of impulse signals from point-like mobile aircraft such as an airplane, a helicopter, a UAV, and from extended atmospheric formations such as angel-echoes, clouds. As a result of semantic analysis of symbolic images of signal marks, classification distinctive features of air objects were obtained. The semantic components of the decision-making algorithm, similar to the decision-making algorithms used by the operator, have been investigated. In the developed algorithm, signal information is described by a predicate function on the set of signal mark pulse amplitudes that have exceeded a certain threshold value. Recognizing of aerial objects is carried out by solving the developed equations of predicate operations. The verification of the developed method was carried out on real data obtained on a survey radar of the centimeter range (pulse duration was 1 μs, probing frequency wass 365 Hz, survey period was 10 s). Based on these data, the types of characteristic marks of radar signals are modeled. According to the results of the experiments, they were all correctly identified.