Statistical optimization and analyses of the method of forming radar images in the time and frequency domains

Authors

  • S.S. Zhyla Національний аерокосмічний університет «Харківський авіаційний інститут», Ukraine https://orcid.org/0000-0003-2989-8988
  • O.V. Odokiienko Національний аерокосмічний університет «Харківський авіаційний інститут», Ukraine https://orcid.org/0000-0002-5227-1000
  • D.I. Kovaljchuk Національний аерокосмічний університет «Харківський авіаційний інститут», Ukraine https://orcid.org/0009-0007-6847-6610
  • K.O. Shcherbyna Національний аерокосмічний університет «Харківський авіаційний інститут», Ukraine https://orcid.org/0009-0005-7870-3675
  • Y.D. Sydorov Національний аерокосмічний університет «Харківський авіаційний інститут», Ukraine https://orcid.org/0009-0002-4088-2127

DOI:

https://doi.org/10.30837/rt.2025.3.222.11

Keywords:

decorrelation, radar image, optimization, reflectivity, scatterometry, signal detection, statistical estimation, stochastic model, time domain, frequency domain

Abstract

The article presents a statistically grounded approach to the formation of scatterometric radar images based on stochastic signal processing. The developed mathematical model takes into account the spatial structure of the reflecting surface, as well as the physical and statistical characteristics of radar signals. The proposed optimal algorithm combines detection, Fourier transformation, decorrelation filtering, and estimation of surface reflectivity coefficients. It is shown that such an approach ensures high resolution and increased noise immunity of the radar system. The statistical optimization is carried out according to the maximum likelihood criterion with minimization of mean square error, using the Cramér–Rao lower bound. The analysis covers both time and frequency domains, with an emphasis on practical implementation of whitening filters and decorrelation procedures in real signal conditions. Simulation examples confirm the theoretical efficiency of the algorithm and justify its application in airborne radar systems using linear frequency modulated signals for high-precision imaging.

References

Wang Z., Bovik A. C., Sheikh H. R., & Simoncelli E. P. Image Quality Assessment: From Error Visibility to Structural Similarity // IEEE Transactions on Image Processing. 2004. Vol. 13, No. 4.

Damera-Venkata N., Kite T. D., Geisler W. S., Evans B. L., & Bovik A. C. Image Quality Assessment Based on a Degradation Model // IEEE Transactions on Image Processing. 2000. Vol. 9, No. 4.

Wang Z. et al. Image Quality Assessment: From Error Visibility to Structural Similarity // IEEE Transactions on Image Processing. 2004.

Eskicioglu A. M., & Fisher P. S. Image Quality Measures and Their Performance // IEEE Transactions on Communications. 1995.

Shnayderman A., Gusev A., & Eskicioglu A. M. An SVD-Based Grayscale Image Quality Measure for Local and Global Assessment // IEEE Transactions on Image Processing. 2006. Vol. 15, No. 2.

Sheikh H. R., & Bovik A. C. Image Information and Visual Quality // IEEE Transactions on Image Processing. 2006

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Published

2025-09-18

How to Cite

Zhyla, S., Odokiienko, O., Kovaljchuk, D., Shcherbyna, K., & Sydorov, Y. (2025). Statistical optimization and analyses of the method of forming radar images in the time and frequency domains. Radiotekhnika, (222), 120–135. https://doi.org/10.30837/rt.2025.3.222.11

Issue

No. 222 (2025): Radiotekhnika

Section

Articles

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