Source identification system based on the time-domain nearfield equivalence source imaging: Fundamental theory and implementation

A nearfield equivalence source imaging (NESI) technique is proposed to identify locations and strengths of noise sources. The NESI is based on the time-domain formulation that applies not only to stationary but also a transient noise. Multichannel inverse filters are designed using the least-square optimization. Tikhonov regularization is called for to mitigate the ill-posedness inherent in the underdetermined model-matching problem. The design parameters such as array aperture, microphone spacing, focal point spacing and distance of projection have profound impact on the resulting sound image resolution. The distance of reconstruction (DOR) is selected according to the condition number of the propagation matrix. A windowing design is also suggested to cope with boundary defocusing problem. Beam pattern is calculated for the inverse filters with window design. In addition, a modified approach based on focal point points is devised to avoid the singularity problem in reconstructing sound images. The multichannel inverse filters are implemented in light of a highly efficient state-space minimal realization technique. The NESI is applicable to one-dimensional (1D) linear array, two-dimensional (2D) rectangular array and even other arrays of irregular geometries. As indicated by the simulation results, the proposed NESI technique proves effective in the identification of noise sources.