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Solving Inverse Radiation Transport Problems with Multi-sensor Data in the Presence of Correlated Measurement and Modeling Errors.

机译:在相关测量和建模误差存在的情况下解决多传感器数据的逆辐射传输问题。

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Inverse radiation transport focuses on identifying the configuration of an unknown radiation source given its observed radiation signatures. The inverse problem is traditionally solved by finding the set of transport model parameter values 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 are inversely proportional to the sum of the variances of the measurement and model errors at a given channel. The traditional implicit (often inaccurate) assumption is that the errors (differences between the modeled and observed radiation signatures) are independent across channels. Here, an alternative method that accounts for correlated errors between channels is described and illustrated using an inverse problem based on the combination of gamma and neutron multiplicity counting measurements.

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