SELECTOR OF CLASSIFIED TRAINING SAMPLES FOR SPATIAL PROCESSING OF SIGNALS UNDER THE IMPACT OF COMBINED CLUTTER AND JAMMING

Authors

  • D. M. Piza Zaporizhzhye National Technical University, Ukraine
  • T. I. Bugrova Zaporizhzhye National Technical University, Ukraine
  • V. M. Lavrentiev State Enterprise “Scientific and production complex “Iskra”, Zaporizhzhya, Ukraine
  • D. S. Semenov State Enterprise “Scientific and production complex “Iskra”, Zaporizhzhya, Ukraine

DOI:

https://doi.org/10.15588/1607-3274-2017-4-3

Keywords:

Radar signals processing, adaptive spatial filtering, combined clutter and jamming, classified training samples, normalized autocorrelation function, functional flow block diagram.

Abstract

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.

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.

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.

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.

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.

Author Biographies

D. M. Piza, Zaporizhzhye National Technical University

Doctor of Technical Sciences, Professor, Pro-rector on scientific and pedagogical work and questions of prospects for the development of the university

T. I. Bugrova, Zaporizhzhye National Technical University

Ph.D, Associate Professor of Radioengineering and Telecommunication Department

V. M. Lavrentiev, State Enterprise “Scientific and production complex “Iskra”, Zaporizhzhya

Ph.D, Head of the department

D. S. Semenov, State Enterprise “Scientific and production complex “Iskra”, Zaporizhzhya

Head of the division

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How to Cite

Piza, D. M., Bugrova, T. I., Lavrentiev, V. M., & Semenov, D. S. (2018). SELECTOR OF CLASSIFIED TRAINING SAMPLES FOR SPATIAL PROCESSING OF SIGNALS UNDER THE IMPACT OF COMBINED CLUTTER AND JAMMING. Radio Electronics, Computer Science, Control, (4), 26–32. https://doi.org/10.15588/1607-3274-2017-4-3

Issue

No. 4 (2017): Radio Electronics, Computer Science, Control

Section

Radio electronics and telecommunications

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Copyright (c) 2017 D. M. Piza, T. I. Bugrova, V. M. Lavrentiev, D. S. Semenov

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