This paper presents a wireless sensor system developed to use RC helicopter dynamics to measure wind turbulence. Wind turbulence is a safety concern for naval helicopter operations due to typical scarcity of landing/takeoff area on naval vessels. Wind turbulence affects the dynamics of helicopters by creating uneven thrust on the rotor blades. The proposed telemetry system, when retrofitted on an RC helicopter, extracts these external disturbances in the helicopter’s dynamics and maps the wind conditions. This study focuses on learning the helicopter’s dynamics in controlled wind conditions using machine learning algorithms. The presented telemetry system uses sensors such as an Inertial Measurement Unit (IMU), optical trackers, and GPS sensors to measure the dynamics of the flying RC helicopter. The system also measures the pilot’s radio inputs to account for pilot inputs in the helicopter’s dynamics. The telemetry system is trained and tested in a large indoor facility where turbulent wind conditions were created artificially using large wind circulation fans.

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