Development of an Advanced Pilot Assistant System Based on Multiple Surveillance Sensor and Deep Learning for GA Class Aircraft Part I Algorithm Development and Validation

초록

In this study, the manufacturing process of multi-sensors and deep learning based pilot assistance system for manned/unmanned aircraft is described. It consists of a total of two parts, this Part 1 describes the development process and results of Software-in-the-loop Simulation (SILS) and Hardware-in-the-loop Simulation (HILS) used in the development process. Optical cameras, radio altimeters, GPS/INS, ADS-B, and Radar modeling were performed to define and use the Sense and Avoid (SAA) concept. The development of the deep learning-based algorithm and the algorithm verification process through the HILS system is described.

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