Helicopter noise is composed of several sources of sound that vary in importance, dependent on the emission angle and operating condition. It can generally be sub-divided in noise generated by the main rotor and tail rotor, engine noise and interior noise. An approach to capturing this complex noise pattern is the measurement of noise hemispheres from flight tests. Trials were held with an Apache AH-64 in order to measure its free space acoustic directivity. The measurement setup consisted of a 100m vertical array containing 93 microphones and a horizontal ground array consisting of 13 microphones. Beamforming was applied to filter out ground reflections for the vertical array microphones by focussing on the helicopter position. A processing algorithm was developed that relies on regression analysis to obtain a model for the acoustic directivity. Directivity functions based on two variable Taylor series and Fourier series were considered. Both approaches yield good results. If a low order approximation is desired, the polynomial fit is better able to capture the measured trend. For a high order approximation, however, the Fourier series fit is better capable to follow rapid changes in directivity.
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