Visual cognitive control of space systems radiotechnical signals

The method of cognitive graphical information presentation is developed, allowing to classify radiotechnical signals and estimate the degree of noise. The method is based on the construction of a features set ordered by information significance. In turn, informativeness is determined by the formal contribution of the feature to the quality of signal type recognition. The construction of cognitive images is carried out in several stages: 1) determination of numerical characteristics of typical signals, 2) ranking and selection of the most informative characteristics, 3) construction of cognitive graphic images visualizing a multidimensional vector of signal features, 4) operator's interpretation of cognitive images. The method of integral contour representation polar scan is used to construct cognitive-graphic images of signals. A total of forty informative parameters of the signal (features) are calculated. To increase the polar scan selectivity, the features are ranked in informativeness descending order by the Add and Del methods. The operation of signals subtraction defined over their informative parameters is introduced. With the goal to improve the visual recognition quality, monochrome halftones have been added to cognitive images. To improve perception of the contour representation of difference images color components have been introduced. The sensitivity of the cognitive images to substantial noise signals is expressed through changes in polar scan forms, tones and colorful presentation. The comparison of signals recognition quality by using metrics and polar scan visual recognition is provided. The recommendations are given to the decision-making operator on the type and noise degree of the radio signal in the final part. © 2020 National Research Nuclear University. All rights reserved.

Authors
Emelyanova Yu.G.1 , Khachumov M.V. 2, 3
Publisher
National Research Nuclear University
Number of issue
2
Language
English
Pages
53-73
Status
Published
Volume
12
Year
2020
Organizations
  • 1 PSI RAS (Ailamazyan Program Systems Institute of RAS), Russian Federation
  • 2 FRC CSC RAS (Federal Research Center "Computer Science and Control" of Russian Academy of Sciences), Russian Federation
  • 3 RUDN University (Peoples Friendship University of Russia), Russian Federation
Keywords
Analysis of radiotechnical signals; Characteristics environment; Cognitive graphics; Cognitive image; Information importance; Interpretation of a cognitive image; Multidimensional data visualization; Radiotechnical signal; Recognition
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