The fuzzy logic approach to the automatic classification of moving target detected by ground surveillance radar is presented in this paper. The real audio Doppler signatures of various targets are analyzed by spectrogram. As a result of analysis, input and output variables with corresponding membership function are defined. The set of fuzzy rules is established. The defuzzification of the output fuzzy set is performed by computing the "fuzzy centroid". The three target classes (walking man, running man and wheeled vehicle) are successfully classified.
In this paper we describe a database, noted as RadEch Database, containing radar echoes from various targets. The data has been collected in controlled test environments at the premises of Military Academy -Republic of Serbia. Our goal is to provide a balanced and comprehensive database to enable reproducible research results in the field of classification of ground moving targets (pattern recognition). A time-frequency analysis of radar echoes has been performed, in order to identify the main features of the various targets. The RadEch Database is freely available for download and we hope that our database provides researchers with a valuable tool to benchmark and improve the performance of classification algorithms.
Absir-mi -In this paper we consider the application of some adaptive algorithms for the antenna array beam steering. Three spatial channel models ( Lee's Model, Gaussian Angle of Arrival Model and Discrete Uniform Distribution Angle of Arrival Model) and 12 -element antenna array are simulated. The antenna array beam steering is performed by using the adaptive algorithms: Least Mean Sgziare -LMS, Least Mean Fourth -LMF, Recursive Least Square -RLS and Sample Matrix Inversion -SMZ. The output antenna array SNIR is analyzed and plotted relating to the angular width and the iteration number the adaptive algorithms.
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