@article{Piza_Bugrova_Lavrentiev_Semenov_2018, title={SELECTOR OF CLASSIFIED TRAINING SAMPLES FOR SPATIAL PROCESSING OF SIGNALS UNDER THE IMPACT OF COMBINED CLUTTER AND JAMMING}, url={http://ric.zntu.edu.ua/article/view/124623}, DOI={10.15588/1607-3274-2017-4-3}, abstractNote={<p>Context. In the conditions of combined clutter and jamming radar performance is significantly degraded. This is due to the decorrelation of a point source of an active jamming by spatially distributed passive clutter. The methods of forming classified training samples to adjust the weight coefficients of spatial filters are introduced.</p><p>Objective. The goal is developing an effective method of forming of classified training samples generated by an active masking jamming, for spatial processing of radar signals in a situation of the clutter influence.</p><p>Methods. The scientific novelty of this work is in developing a new method of forming the training samples based on the estimation of the width of the normalized autocorrelation function in each range resolution element. On-the-fly analysis of the components of combined clutter and jamming in each range resolution element improves the quality of the components classification and, as a result, minimizes the effect of passive clutter on a spatial filter adaptation process.</p><p>Results. The theoretical and practical aspects of the forming of the classified training samples are analyzed. A functional flow block diagram of the classifier of combined clutter components was developed.</p>Conclusions. Using of the on-the-fly analysis of the combined clutter and jamming components in each range resolution element improves the quality of the clutter classification, which is important in complex hydrometeorological conditions.}, number={4}, journal={Radio Electronics, Computer Science, Control}, author={Piza, D. M. and Bugrova, T. I. and Lavrentiev, V. M. and Semenov, D. S.}, year={2018}, month={Mar.}, pages={26–32} }