Automatic Design: Precision Optimization for Peak Imaging System Performance

Design for any imaging system starts with a set of requirements such as focal length, field of view, image size and resolution. Selecting the appropriate first-order layout from the design library or sample lenses, closest to the specification is beneficial, yet it is often the simplest aspect of the design process. The initial design is plagued with various spherical and chromatic aberrations that degrade image quality and fails to account for any physical limitations or manufacturing tolerances. It is necessary to find a balance between meeting performance requirements and staying within budget. The primary challenge is to overcome the inherent trade-offs between these goals to achieve an optimal design that can be effectively implemented when coupled with physical constraints and manufacturing cost.

The anatomy of a lens is defined by how precisely the design is rectified to eliminate its intrinsic imperfections. The traditional method of correcting these flaws, a manual process of trial and error is extremely time consuming. Manipulation of several variables simultaneously, such as the curvature, thickness, or material of the lens, leads to the realization that correcting one aberration worsens another. This necessitates an endless cycle of design iterations which ultimately stagnates the product development cycle.

Leveraging CODE V’s powerful optimization tool helps automate the task of finding the best design. This computational process combines image error data into a single value called the error function, that we attempt to make as small as possible. This thorough, iterative approach yields an imaging system that generates clear and distortion-free images. In addition to enhancing performance, it also improves overall efficiency and robustness.

Optimization: Paradigm Shift Towards Automation and Precision

CODE V’s optimization feature called Automatic Design (AUT) uses damped least square algorithm (DLS) to generate changes in variables that improve the system. Constraints defined based on physical dimension, material availability and manufacturing conditions act as boundaries when identifying the ideal solution.

Optimization Workflow in CODE V

1. Define as variables all radii of curvatures, thickness values, and fictitious glasses in lens data manager (LDM).
2. Make sure all glass elements are thick enough and glass index is not too high to ensure design is cost effective.
3. Set specific constraints on parameters that shouldn’t be varied by the optimization process like, effective focal length (EFL), FOV, dimension or glass materials.
4. Specify user defined error function or use the default spot size error function in CODE V.
5. Draw the lens on each optimization cycle and analyze its modulation transfer function (MTF), point spread function (PSF) and various field aberration curves.
6. Additionally, cost analysis evaluates the glass cost and blocking factors which helps compare relative costs of various design.
7. Ghost and Narcissus image analysis (GHO, NAR) are paraxially based options for evaluating unwanted secondary images.

Optimization tool is a necessity for modern optical design. It significantly reduces the time it takes to produce a manufacturable design thus enhancing efficiency. Drastically improves device performance and image quality due to its capability of simultaneously varying multiple parameters which is never possible manually. It helps ensure higher yield and lower costs by accounting for design sensitivity towards manufacturing.

In essence, optimization transforms the design process from a labor-intensive, trial-and-error approach into a data-driven, systematic search for the best possible solution.