Accounting for correlated errors in inverse radiation transport problems

Inverse radiation transport focuses on identifying the configuration of an unknown radiation source given its observed radiation signatures. The inverse problem is solved by finding the set of transport model variables that minimizes a weighted sum of the squared differences by channel between the observed signature and the signature predicted by the hypothesized model parameters. The weights per channel are inversely proportional to the sum of the variances of the measurement and model errors at a given channel. In the current treatment, the implicit assumption is that the errors (differences between the modeled and observed radiation signatures) are independent across channels. In this paper, an alternative method that accounts for correlated errors between channels is described and illustrated for inverse problems based on gamma spectroscopy.