For many systems, accurately estimating multiple parameters or variables of interest from multiple sensor responses requires models that account for nonlinear system behavior. Such multivariate estimation is typically accomplished using iterative methods or local linearity assumptions in the vicinity of a nominal operating point. Here, an alternative approach is described in the context of nondestructive testing (NDT) where databases of precomputed sensor responses are used with error minimization methods to efficiently perform multiple unknown parameter estimations (Goldfine and Melcher, 1995; Goldfine and Melcher, 2002; Melcher, 1991).

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