MINIMIZATION OF BIAS ERROR DUE TO WINDOWS IN PLANAR ACOUSTIC HOLOGRAPHY USING A MINIMUM ERROR WINDOW

Abstract

Bias errors in the prediction of a sound field using planar acoustic holography are due to aliasing and window effects. It is noteworthy that aliasing is negligible in the forward predictions if the sampling space is less than a quarter wavelength. However, bias error induced by a window is the major concern for accurate holographic prediction because of the small number of measurement points in the planar acoustic holography. For the reduction of this error, a new class of window, the MEW, is proposed and compared with Ham, Gaussian, and Kaiser-Bessel windows. It is built by modifying the method that Papoulis proposed by minimizing the second-order moment of the window spectrum. The characteristics of the MEW vary with the number of weighting values and the number of higher-order moment terms to be eliminated. The applicability of the MEW on planar acoustic holography is demonstrated. (C) 1995 Acoustical Society of America.