Aspheric Diffractive Surface Measurement Without Prior Estimates
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Solution Overview
Problem
Current surface measurement instruments face challenges in accurately characterizing aspheric diffractive structures, particularly in identifying step edges and heights without prior estimates of base radius or step height, and assuming equal step heights, which limits their applicability to diverse stepped structures.
Innovation Solution
A method and apparatus that receive measurement data from aspheric diffractive structures, fit an aspheric component, subtract known polynomial components, and use edge detection filters like Haar filters to enhance step edges, allowing for the identification of step locations and heights without initial estimates, and iteratively refine the characterization process to achieve accurate results.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional surface measurement instruments are used to characterize aspheric diffractive structures, then measurement capability is provided, but accuracy in identifying step edges and heights is compromised due to reliance on prior estimates and assumptions of equal step heights
Solution Approach 1:
The patent extracts and removes the aspheric component and known polynomial diffractive components from the measurement data through sequential subtraction. This isolation allows the stepped structure to be analyzed independently without interference from other surface features, enabling accurate step edge and height identification without requiring prior estimates or assumptions about equal step heights
Solution Approach 2:
The characterization process is segmented into distinct sequential steps: (1) fitting and removing the aspheric component, (2) fitting and removing known polynomial diffractive components, (3) analyzing the remaining stepped structure. This segmentation allows each component to be handled with appropriate methods and avoids the need for simultaneous complex analysis that would require prior estimates
2Loss of time
If initial estimates of base radius or step height are required for measurement, then characterization can proceed, but measurement time increases and accuracy is limited by the quality of these estimates
Solution Approach 1:
The patent performs preliminary actions by fitting and removing the aspheric component and known polynomial diffractive components before analyzing the stepped structure. This preliminary processing prepares the data in advance, isolating the stepped features and enabling their direct analysis without requiring time-consuming iterative estimation of base radius or step height parameters
Solution Approach 2:
The measurement system performs self-service by automatically identifying step edges and heights through edge detection filters applied to the residual data after component removal. The system does not require external prior estimates or manual input of expected values, as the processed data itself provides sufficient information for accurate characterization
3Measurement precision
If edge detection filters are applied to enhance step edges, then identification accuracy improves, but data processing complexity increases
Solution Approach 1:
Edge detection filters are applied as a preliminary action to the residual data after aspheric and polynomial component removal. This timing is critical because the filters work most effectively on isolated stepped structures rather than complex composite surfaces. The preliminary removal of other components simplifies the data structure, making the edge detection process more straightforward and less complex
Data Source
AI summary
A method of characterizing the surface of an aspheric diffractive structure includes using a metrological apparatus to perform a measurement on the surface of the structure so as to provide a measurement profile representing the z-direction deviations of the surface of the structure; determining parameters relating to the aspheric and diffractive components of the aspheric diffractive structure; producing data having the determined parameters; and comparing the produced data with the measurement profile to determine residual error data.