Имитационная Модель Радиолокационного Сопровождения Распределенных Объектов

Abstract

The subject of research is radar tracking of distributed objects like groups of small drones. The peculiarity of these objects is in their complex composition and an unusual for most classic aircrafts movement character.The research method is simulation modeling. It allows evaluating the effectiveness of radar tracking algorithms and classification in selected terms.The article presents the process organization of simulation modeling of integrated radar system functioning in the detection, measurement, tracking and classification modes. It also presents the description of analytical models and their interaction, as well as simulation results, which are received using traditional experiment processing methods. The methods take into account a required number of tests to provide probability values in confidence interval no more than 0,01 of the obtained value with a confidence probability no more than 0.8. The authors evaluated performance of the most popular tracking and classification algorithms. Tracking algorithms include α-β-γ algorithm, Kalman filter, Unscented Kalman filter, partial filter. Classification algorithms include optimal Bayes algorithm, parting algorithm, Viterbi algorithm, Savrasov algorithm. The model, unlike the known ones, takes into account the influence of all reflections and re-reflections of the probing signal from the sophisticated object elements.According to the simulation results, the authors make a conclusion that among the tracking algorithms, the most efficient are algorithms based on the partial filter and Unscented Kalman filter; among the classification algorithms, the most efficient is Savrasov algorithm. However, based on the requirements for a radar performance, none of the considered algorithms provides the required quality under the described conditions. This indicates the need to improve the scientific and methodological apparatus of radar trajectory processing.