A classification technique of group objects by artificial neural networks using estimation of entropy on synthetic aperture radar images

Anton V. Kvasnov, Vyacheslav P. Shkodyrev
2021 Journal of Sensors and Sensor Systems  
Abstract. The article discusses the method for the classification of non-moving group objects for information received from unmanned aerial vehicles (UAVs) by synthetic aperture radar (SAR). A theoretical approach to analysis of group objects can be estimated by cross-entropy using a naive Bayesian classifier. The entropy of target spots on SAR images revaluates depending on the altitude and aspect angle of a UAV. The paper shows that classification of the target for three classes able to
more » ... t with fair accuracy P=0,964 based on an artificial neural network. The study of results reveals an advantage compared with other radar recognition methods for a criterion of the constant false-alarm rate (PCFAR<0.01). The reliability was confirmed by checking the initial data using principal component analysis.
doi:10.5194/jsss-10-127-2021 fatcat:ko7shaf4sjbnlh2bt6agdcrfxm