Array processing estimation of sound velocity for non-linearly superimposed acoustic waves

Acoustic pressure waves are non-linearly superimposed when a periodic gas flow is perturbing the propagating medium, as it arises in exhaust systems. In such an environment, to estimate a certain set of source parameters from the pressure measures taken by an array of sensors is non-trivial. In this paper two possible linearization methods for the wave superposition are given. Moreover, a new problem formulation including the noise corruption of the source data is presented. Based on this linear approach, three different sound speed estimates are compared for a numerical experiment generated by thermodynamics modeling software. Results have shown that good performance of sound speed estimates mainly depends on the limited array aperture imposed by the linear model feasibility, being ML-like estimates more robust than those based in subspace decomposition methods.