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Specifics of Matrix Masking in Digital Radar Images Transmitted Through Radar Channel

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Intelligent Decision Technologies

Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 309))

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Abstract

This paper presents research results, concerning systems of radar image masking in real-time mode when transmitting fast-changing data. A promising masking approach of visual data protection is employed here. This method entails utilization of a certain class of orthogonal two-level matrices, including the Hadamard matrices. The method is intended to convert radar images to a noise-like representation, while ensuring proper smoothing of pulse interference or deliberate distortions, arisen in the transmission channel, on a demasked image. This research is based on the consideration of special structural features of the images while masking and demasking, as well on the properties of the masking matrices. Evaluations of the demasked images are given, with pulse interference or deliberate distortions, introduced in the transmission channel. The evaluations are based on the values of some widely used metrics.

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Acknowledgements

The reported study was funded by RFBR project number â„– 19-29-06029.

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Authors and Affiliations

  1. Saint-Petersburg State University of Aerospace Instrumentation, 67 Bolshaya Morskaya street, Saint-Petersburg, 190000, Russian Federation

    Vadim Nenashev, Anton Sentsov & Alexander Sergeev

Authors
  1. Vadim Nenashev
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  2. Anton Sentsov
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  3. Alexander Sergeev
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Corresponding author

Correspondence to Vadim Nenashev .

Editor information

Editors and Affiliations

  1. Gdynia Maritime University, Gydnia, Poland

    Ireneusz Czarnowski

  2. ‘Aurel Vlaicu’ University of Arad, Arad, Romania

    Robert J. Howlett

  3. KES International, Selby, UK

    Lakhmi C. Jain

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Nenashev, V., Sentsov, A., Sergeev, A. (2022). Specifics of Matrix Masking in Digital Radar Images Transmitted Through Radar Channel. In: Czarnowski, I., Howlett, R.J., Jain, L.C. (eds) Intelligent Decision Technologies. Smart Innovation, Systems and Technologies, vol 309. Springer, Singapore. https://doi.org/10.1007/978-981-19-3444-5_20

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