Hypersonic Target Detection Using Eoir-Emulated Synthetic Data: A Case Study of X-43A


DOI: https://doi.org/10.15308/Sinteza-2025-251-258
Authors:
Slobodan Pajić
Gerrit Viljoen
Marko Tanasković

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Keywords:
Synthetic Image Generation, EOIR, Hypersonic Targets, ANSYS STK, ATR


Abstract:
Detecting hypersonic vehicles is challenging due to their high flight velocity, unpredictable flight paths, and distinct thermal signatures. This study used the ANSYS Systems Tool Kit (STK) to generate high-fidelity synthetic datasets. These datasets were designed to simulate Electro-Optic Infrared (EOIR) scenarios tailored specifically for hypersonic targets. Inspired by the X-43A hypersonic flight tests, we created a simplified environment without terrain modeling to balance computational efficiency and physics-based simulation. Our approach tackles the critical lack of real-world data by offering a scalable and realistic foundation for advancing Automatic Target Recognition (ATR) systems. Our simulations demonstrated that a Modified HALO-II sensor achieved an 18% improvement in detection rates compared to the standard HALO-II sensor, even under challenging thermal conditions. We explain the experimental setup and ATR dataset generation. Future work will focus on integrating synthetic with experimental datasets to help AI-driven detection systems address the evolving challenges of hypersonic threats.

CITATION:

IEEE format

S. Pajić, G. Viljoen, M. Tanasković, “Hypersonic Target Detection Using Eoir-Emulated Synthetic Data: A Case Study of X-43A,” in Sinteza 2025 - International Scientific Conference on Information Technology, Computer Science, and Data Science, Belgrade, Singidunum University, Serbia, 2025, pp. 251-258. doi:10.15308/Sinteza-2025-251-258

APA format

Pajić, S., Viljoen, G., Tanasković, M. (2025). Hypersonic Target Detection Using Eoir-Emulated Synthetic Data: A Case Study of X-43A. Paper presented at Sinteza 2025 - International Scientific Conference on Information Technology, Computer Science, and Data Science. doi:10.15308/Sinteza-2025-251-258

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