Abstract
The inverse problem in scatterometry which consists in determining the feature shape from an experimental ellipsometric signature is very difficult to solve. On one hand, the problem is ill-posed; on the other hand, due to equipment limitation and the presence of noise in the measurement, the number of experimental signature acquisition is limited to a few measurements. The efficient resolution of the inverse problem requires a more comprehensive signature. To deal with this problem, we use a new approach based on the Kriging interpolation method to enrich the number of usable data. This method is inherently providing the best linear unbiased optimal estimation.
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