Optical Model Calibration Test Pattern Selection
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Solution Overview
Problem
Current methods for selecting calibration patterns for simulating the imaging performance of optical imaging systems are inefficient, requiring a large number of patterns for robustness but consuming significant time, and often rely on designer experience rather than systematic approaches.
Innovation Solution
A method is developed to determine optimal calibration test patterns by generating a cross-correlation transform function and selecting test structures that contribute to all terms in this function, ensuring comprehensive calibration while minimizing the number of patterns needed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a large number of calibration patterns are used to ensure robustness of the simulation model, then the reliability of the model is improved, but the time required for calibration increases significantly
Solution Approach 1:
The patent extracts and identifies only the essential calibration patterns needed for model calibration by analyzing the imaging model's mathematical representation. Instead of using a large number of patterns, the method identifies a minimal set of test patterns that specifically target the critical parameters of the imaging model, thereby reducing calibration time while maintaining model robustness
Solution Approach 2:
The patent transforms the calibration approach by changing from a brute-force method (using many patterns) to a parameter-based method. It analyzes the mathematical parameters of the imaging model (such as optical transfer function parameters, resist model parameters) and selects calibration patterns that specifically test these parameters, enabling efficient calibration with fewer patterns
2Ease of operation
If calibration patterns are selected based on designer experience rather than systematic methods, then the ease of operation is improved, but the manufacturing precision of the calibration process deteriorates
Solution Approach 1:
The calibration process becomes self-directed through automated pattern selection. The system automatically identifies and selects optimal calibration patterns based on the imaging model's mathematical representation, eliminating the need for designer intervention while ensuring high calibration accuracy through systematic, objective criteria
Solution Approach 2:
The patent replaces the subjective, experience-based mechanical process of pattern selection with an automated computational system. The system uses mathematical analysis of the imaging model to objectively determine optimal calibration patterns, substituting human designer judgment with algorithmic precision
Data Source
AI summary
A method of determining calibration test patterns to be utilized to calibrate a model for simulating the imaging performance of an optical imaging system. The method includes the steps of defining a model equation representing the imaging performance of the optical imaging system; transforming the model equation into a plurality of discrete functions; identifying a calibration pattern for each of the plurality of discrete functions, where each calibration pattern corresponding to one of the plurality of discrete functions being operative for manipulating the one of the plurality of discrete functions during a calibration process; and storing the calibration test patterns identified as corresponding to the plurality of discrete functions. The calibration test patterns are then utilized to calibrate the model for simulating the imaging performance of an optical imaging system.