Artificial Ineligence for Synthetic Aperture Radar Image Processing

Authors

DOI:

https://doi.org/10.18372/1990-5548.80.18688

Keywords:

аrtificial intelligence, intelligent processing, intelligent system, machine learning, neural networks, synthetic aperture radar, unmanned aerial vehicle

Abstract

The object of this research is the processing of synthetic aperture radar (SAR) images using artificial intelligence. The subject of the study focuses on the utilization of artificial intelligence for the object detection on SAR images. The primary goal of this thesis is to investigate the principles of SAR operation, analyze various systems for detecting anomalous objects in soil, develop an intelligent system for processing SAR images, and evaluate the potential of the developed system for the classification of explosive objects. The research methods include the analysis of existing literature and programming in Python. The findings and materials from this thesis are recommended for use in the analysis of current underground anomaly detection systems, the potential application of artificial intelligence and machine learning in demining processes, and the examination of radar image processing methods.

Author Biographies

Victor Sineglazov , National Aviation University, Kyiv

Doctor of Engineering Science

Professor

Head of the Department Aviation Computer-Integrated Complexes

Faculty of Air Navigation Electronics and Telecommunications

Andriy Shvidchenko, National Aviation University, Kyiv

Student

Faculty of Air Navigation, Electronics and Telecommunications

References

https://tr.dsns.gov.ua/uk/news/ostanni-novini/iak-diiati-pri-viiavlenni-vibuxonebezpecnix-ta-pidozrilix-predmetiv

I. Trevoho, A. Horb, and O. Meleshko, “Zastosuvannya RLS iz syntezovanoyu aperturoyu dlya vysokotochnoho heoprostorovoho monitorynhu», Suchasni dosyahnennya heodezychnoyi nauky ta vyrobnytstva,” Vypusk I (33), 2017. [in Ukrainian]

P. Berens, “Introduction to Synthetic Aperture Radar (SAR),” Advanced Radar Signal and Data Processing, pp. 3-1-3-14, 2006.

https://www.findmine.org/gpsar

M. Bradley, T. Witten, M. Duncan, and B. McCunmmins, “Mine detection with a forward-looking ground-penetrating synthetic aperture radar,” vol. 5089, 2003.

M. Schartel, R. Burr, W. Mayer, and C. Waldschmidt, “Airborne Tripwire Detection using a Synthetic Aperture Radar,” Journal of Latex Class Files, vol. 14, no. 8, August 2015.

https://www.kaggle.com/datasets/kailaspsudheer/sar-scope-unveiling-the-maritime-landscape/code

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Published

2024-06-25

Issue

Vol. 2 No. 80 (2024)

Section

AUTOMATION AND COMPUTER-INTEGRATED TECHNOLOGIES

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