Method of forming classified training sample with spatial signal processing under the impact of combined clutter and jamming

Abstract

Problems. In the conditions of combined clutter and jamming radar performance significantly deteriorates. This is due to the decorrelation of a point source of an active jamming by spatially distributed nature of passive clutter. The methods of forming a classified training sample to adjust the weight coefficients of spatial filters are introduced. Goal. Developing an effective method of formation of a classified training sample generated by an active masking jamming, for spatial processing of radar signals in a situation of simultaneous influence of clutter. Methods. The scientific novelty of this work is in developing a new method of forming the training sample based on the assessment 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 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. Results. The theoretical and practical aspects of the formation of a classified training sample are analyzed. A functional flow block diagram of the classifier of combined clutter components is developed. Conclusions. 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.