Clustering inverse beamforming for vehicles NVH

Clustering Inverse Beamforming is an array-based acoustic imaging technique to solve inverse problems formulated by discretizing the source region into elementary equivalent sources. It is based on a statistical processing of multiple realizations of the acoustic image, related to the investigated source region, iteratively obtained solving the corresponding inverse problem on different clusters of microphones, taken from the same microphones array. The result of such statistical processing is stored in the so-called "clustering mask matrix". This function is defined, in the source region, where it is interpretable as the confidence level of finding a physical source in each location within the domain. The inner statistical nature of such approach prevents the occurrence of numerical issues related to the solution of the inverse problem. It allows accurate localization and optimal quantification by enabling to focus on those sub-regions most likely to be the location of physical sources. Moreover, if combined with Principal Component Analysis, the method provides a robust criterion for uncorrelated noise source separation with no need of reference sensors in the proximity of the investigated object. Clustering Inverse Beamforming is applicable to exterior as well as to interior acoustic imaging problems. It does not require any special geometrical configuration of the microphones array. The technique is presented both on numerical simulations and on experiments related to vehicles NVH applications.