Imaging with two-axis micromirrors

We demonstrate a means of creating a digital image by using a two axis tilt micromirror to scan a scene. For each different orientation we extract a single grayscale value from the mirror and combine them to form a single composite image. This allows one to choose the distribution of the samples, and so in principle a variable resolution image could be created. We demonstrate this ability to control resolution by constructing a voltage table that compensates for the non-linear response of the mirrors to the applied voltage.Comment: 8 pages, 5 figures, preprin

Optical Propagation Methods for System-Level Modeling of Optical MEM Systems

In this thesis, we determine and implement an optical propagation technique suitable for system-level simulation of optical micro-systems. The Rayleigh-Sommerfeld formulation is selected as the optical propagation modeling technique because it satisfies the requirements of a system-level CAD tool and supports accurate modeling at propagation distances on the order of the wavelength of light. We present an efficient solution to the Rayleigh-Sommerfeld formulation using the angular spectrum technique which uses the fast Fourier transform to decompose the complex optical wavefront into plane waves propagating from the aperture to the observation plane. This technique reduces the computational order of solving the Rayleigh-Sommerfeld formulation from a brute force direct integration technique of O(N4) to a computational order of O(N2logN).For use in a design environment, we present an error analysis of our technique. Errors are caused by the discrete sampling of the optical wavefront over a finite range to approximate the infinite continuous Fourier transform. Methods for reducing both aliasing and truncation errors are presented, along with techniques to estimate the remaining errors of the angular spectrum technique. We perform a rigorous error estimate on several common optical wavefronts and provide techniques to perform an error analysis on a general wavefront. The utility of this method is shown by implementing the work into a mixed-signal, multi-domain CAD tool, in which we perform system-level simulations and analyses of several optical MEM systems

Model-based optoelectronic packaging automation

IEEE Journal of Selected Topics in Quantum Electronics, 10(3): pp. 445-454. http:dx.doi.org/10.1109/JSTQE.2004.828476In this paper, we present an automation technique that yields high-performance, low-cost optoelectronic alignment and packaging through the use of intelligent control theory and system-level modeling. The control loop design is based on model-based control, previously popularized in process and other control industries. The approach is to build an a priori knowledge model, specific to the assembled package’s optical power propagation characteristics, and use this to set the initial “feed-forward” conditions of the automation system. In addition to this feed-forward model, the controller is designed with feedback components, along with the inclusion of a built in optical power sensor. The optical modeling is performed with the rigorous scalar Rayleigh–Sommerfeld formulation, efficiently solved online using an angular spectrum technique. One of the benefits of using a knowledge-based control technique is that the efficiency of the automation process can be increased, as the number of alignment steps can be greatly reduced. An additional benefit of this technique is that it can reduce the possibility that attachment between optical components will occur at local power maximums, instead of the global maximum of the power distribution. Therefore, the technique improves system performance, while reducing the overall cost of the automation process

Learning identification control for model-based optoelectronic packaging

IEEE Journal Of Selected Topics In Quantum Electronics, 12(5): 945-951.In this paper, we present a learning control algorithm for the packaging automation of optoelectronic systems. This automation provides high performance, low-cost alignment and packaging through the use of a model-based control theory and systemlevel modeling. The approach is to build an a priori model, specific to the assembled package’s optical power propagation characteristics. From this model, an inverse model is created and used in the “feedforward” loop. In addition to this feedforward model, the controller is designed with feedback components, along with the inclusion of a built-in optical power sensor. We introduce a learning technique, which is activated at a lower sampling frequency for specific and appropriate tasks, to improve the model used in the model-based control. Initial results are presented from an experimental test bed that is used to verify the control and learning algorithms

Advanced packaging automation for opto-electronic systems

Virology, 351(2), 271-279. http://dx.doi.org/10.1016/j.virol.2006.01.051In this paper, we present a learning control algorithm used in our research of advanced opto-electronic automation, which yields high performance, low cost optoelectronic alignment and packaging through the use of intelligent control theory and system-level modeling. The learning loop technique is activated at a lower sampling frequency for specific and appropriate tasks, to improve the knowledge based control model. Our automation technique is based on constructing an a priori knowledge based model, specific to the assembled package’s optical power propagation characteristics. From this model, a piece-wise linear inverse model is created and used in the “feedforward” loop. This model can be updated for increased accuracy through the learning loop

College of Arts and Sciences Drexel E-Repository and Archive (iDEA)

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