Lung sound localization using array of acoustic sensors

This paper presents a localization algorithm to detect lung sounds using a circular array of microphones. We use the natural basis functions of propagation waves in height invariant wavefields to form a spatial minimum variance (MV) problem in eigen space. We also derive a Nyquist criteria for localizing sources within a circular region. This Nyquist criteria shows that the radius of the region where sources can be localized is inversely proportional to the frequency of sound. The modified Nyquist criteria can be used for determining the number of sensors required for a given frequency range and radius of region for which sources need to be localized. The results are corroborated by computer simulations.