The performance of remotely-controlled (RC) vehicles in recreational activities, such as RC cars, boats, planes and drones, has increased dramatically with the increased energy density of lithium polymer and Nickel metal hydride battery technologies. As a result, RC cars capable of land speeds in excess of 100 mph are available in hobbyist-class vehicles. This work presents an experimental and analytical setup for measuring the land-, water-, and air-speed of such RC vehicles using passive signal processing of acoustic recordings of the vehicles in operation. The high-efficiency DC brushless motors used in these platforms emit strong harmonic structure that can be efficiently measured with Doppler-tracking. The harmonic structure of the recorded acoustic signals allow passive velocity estimation using quasi-periodic signal detection and period estimation techniques based on pitch detection methods in the time and frequency domain. Preliminary results yielded successful velocity recovery based on Doppler tracking using a pilot signal, and demonstrated the correlation between the speed profile of the vehicle and acoustic harmonics. Future work will include an analytical model and set of experiments for passive velocity measurement suitable for high school and undergraduate physics laboratory exercises.
In a previous talk, we presented the use of Doppler processing of an acoustic signal recorded from a moving RC car to estimate the speed of the RC car traveling to and away from an observer. In this work, a multi-harmonic dynamic model for the RC car motor is incorporated into the acoustic model and this multi-harmonic tracking algorithm is used to estimate the velocity of the RC car based on this improved model, implemented in Python.
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