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

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.