SUMMARY

Brownout is a phenomenon in aviation which refers to high dust and sand levels stirred up by the rotor downwash of landing helicopters. The sand/dust levels reduce the pilot’s visibility to near zero and can lead to crashes, injuries, and even fatalities. This thesis explores one possible method of preventing brownout crashes by using the noise generated by the helicopter’s rotor as an altimeter. The height can be calculated by measuring the time it takes for noise from the rotor’s echo to reflect back from the ground. Distances to smaller obstacles, such as machinery, can be sensed by looking for echoes with smaller amplitudes. The velocity can be determined by measuring small amounts of Doppler distortion. To detect the height, a signal processing technique known as the cepstrum was employed. To measure the Doppler distortion, the Scale-Mellin Transform was used. Algorithms associated with these two methods were tested for robustness and accuracy. Once the algorithms were fully developed and optimized for this application, a microphone array was built to confirm the simulations. The array was tested in the hemianechoic chamber and outside in Georgia Tech’s Burger Bowl. It yielded very good results for the height detection algorithm but was not as effective in measuring velocity.