Temperature-parameter CRB-guided wavelength selection for multispectral radiation thermometry.

Multispectral radiation thermometry (MRT) estimates temperature from several spectral-radiance measurements while compensating for unknown emissivity, but the inversion stability is strongly determined by the wavelength configuration chosen before the inversion. We propose a temperature-parameter Cramér-Rao bound (CRB) guided wavelength-selection method that treats emissivity-model parameters as nuisance parameters and minimizes the CRB component associated with the target temperature. For a power-law emissivity model, an analytical Jacobian is derived for the Fisher information matrix, enabling deterministic evaluation of candidate wavelength sets. Numerical simulations in the 1.1-2.5 μm band show that the predicted temperature CRB agrees with the empirical Monte Carlo temperature-error standard deviation over 27 temperature-emissivity scenarios. Compared with uniform spacing, the proposed CRB-Opt design reduces the average CRB from 3.82% to 2.60%, the RMSE from 3.82% to 2.60%, and the 95th-percentile ARE from 7.59% to 5.23%. Experiments on a pre-oxidized GH4169 nickel-based superalloy further indicate that, under the same calibration and inversion procedure, the CRB-Opt wavelengths reduce the median ARE from 9.85% to 2.50% and suppress the high-error tail relative to uniform spacing. The method provides a temperature-prioritized, physically interpretable, and computationally feasible front-end channel-design criterion for MRT.