STATISTICAL PROPERTIES OF RANDOM SPARSE ARRAYS

Theoretical models that can be used to predict the range of mainlobe widths and the probability distribution of the peak sidelobe levels of two-dimensionally sparse arrays are presented here. The arrays are considered to comprise microphones that are randomly positioned on a segmented grid of a given size. First, approximate expressions for the mean and variance of the squared magnitude of the aperture smoothing function are formulated for the random arrays considered in the present study. By using the variance function, the mean value and the lower end of the range i.e., the first 1 per cent of the mainlobe width distribution, can be predicted with reasonable accuracy. To predict the probability distribution of the peak sidelobe levels, distributions of levels were modelled by using a Weibull distribution at each peak in the sidelobe region of the mean squared magnitude of the aperture smoothing function. The two parameters of the Weibull distribution were estimated from the means and variances of the levels at the corresponding locations. Next, the probability distribution of the peak sidelobe levels were identified by following a procedure in which the peak sideload level was determined as the maximum among a finite number of independent random sidelobe levels. It was found that the model obtained from that approach predicts the probability density function of the peak sidelobe level distribution reasonably well for the various combinations of the two different numbers of microphones and the various grid sizes tested in the present study. The application of these models to the design of random, sparse arrays having specified performance levels is discussed.