Abstract
Cognitive radars are systems based on the percept-action cycle of cognition that sense the environment, extract relevant target and background information from it, and then adapt the radar sensor to optimally meet the needs of its mission according to the desired target. The aim of the study is to determine the options for using the cognitive approach to improve the performance of the radar system. The study results show the criteria by which a radar should be defined as cognitive. In addition, our task was to propose machine learning methods based on artificial neural networks for the problem of radar resource allocation.
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