Review of the mathematical foundations of data fusion techniques in surface metrology

TLDR

Engineered surfaces such as freeform and structured types challenge existing metrology, prompting the use of multiple sensors to extend spatial frequency bandwidth, which necessitates data fusion. This paper reviews current data fusion methods and applications, focusing on their mathematical foundations. The authors conduct a literature review of data fusion techniques applied to surface metrology, analyzing the mathematical frameworks that support them. The review identifies key research questions and discusses potential fusion algorithms for surface metrology.

Abstract

The recent proliferation of engineered surfaces, including freeform and structured surfaces, is challenging current metrology techniques. Measurement using multiple sensors has been proposed to achieve enhanced benefits, mainly in terms of spatial frequency bandwidth, which a single sensor cannot provide. When using data from different sensors, a process of data fusion is required and there is much active research in this area. In this paper, current data fusion methods and applications are reviewed, with a focus on the mathematical foundations of the subject. Common research questions in the fusion of surface metrology data are raised and potential fusion algorithms are discussed.