Engineering Papers⌕ Search

Engineering topics

Sidick, Erkin

Publications and source records attributed to Sidick, Erkin.

At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS2012

HCIT Broadband Contrast Performance Sensitivity Studies

One of the important milestones of the TPF Coronagraph project is to demonstrate the ability to predict the performance sensitivities of the system at levels consistent with exo-planet detection requirement. We want to gain some general understanding about the potentials and the limitations of the current single-Deformable-Mirror (DM) High-contrast imaging testbed (HCIT) system through modeling and simulations. Specifically, we want to understand the effects of some common errors on the EFC-based control of e-field over a half dark-hole region and broadband contrast. Investigated errors include: (1) Absorbing particles on a flat-mirror (2) Defects on the Occulter surface (3) Dead actuators on the DM. We also investigated the effects of control bandwidth on the broadband contrast. We used a MACOS-based simulation algorithm which (1) combines a ray trace, diffraction model, & a broadband wavefront control algorithm (2) is capable of performing full three-dimensional near-field diffraction analysis

exoplanets↗
NASA NTRS2012

Method for Pre-Conditioning a Measured Surface Height Map for Model Validation

This software allows one to up-sample or down-sample a measured surface map for model validation, not only without introducing any re-sampling errors, but also eliminating the existing measurement noise and measurement errors. Because the re-sampling of a surface map is accomplished based on the analytical expressions of Zernike-polynomials and a power spectral density model, such re-sampling does not introduce any aliasing and interpolation errors as is done by the conventional interpolation and FFT-based (fast-Fourier-transform-based) spatial-filtering method. Also, this new method automatically eliminates the measurement noise and other measurement errors such as artificial discontinuity. The developmental cycle of an optical system, such as a space telescope, includes, but is not limited to, the following two steps: (1) deriving requirements or specs on the optical quality of individual optics before they are fabricated through optical modeling and simulations, and (2) validating the optical model using the measured surface height maps after all optics are fabricated. There are a number of computational issues related to model validation, one of which is the "pre-conditioning" or pre-processing of the measured surface maps before using them in a model validation software tool. This software addresses the following issues: (1) up- or down-sampling a measured surface map to match it with the gridded data format of a model validation tool, and (2) eliminating the surface measurement noise or measurement errors such that the resulted surface height map is continuous or smoothly-varying. So far, the preferred method used for re-sampling a surface map is two-dimensional interpolation. The main problem of this method is that the same pixel can take different values when the method of interpolation is changed among the different methods such as the "nearest," "linear," "cubic," and "spline" fitting in Matlab. The conventional, FFT-based spatial filtering method used to eliminate the surface measurement noise or measurement errors can also suffer from aliasing effects. During re-sampling of a surface map, this software preserves the low spatial-frequency characteristic of a given surface map through the use of Zernike-polynomial fit coefficients, and maintains mid- and high-spatial-frequency characteristics of the given surface map by the use of a PSD model derived from the two-dimensional PSD data of the mid- and high-spatial-frequency components of the original surface map. Because this new method creates the new surface map in the desired sampling format from analytical expressions only, it does not encounter any aliasing effects and does not cause any discontinuity in the resultant surface map.

Sidick, Erkin↗
NASA NTRS2012

Extended Scene SH Wavefront Sensor Algorithm: Minimization of Scene Content Dependent Shift Estimation Errors

Adaptive Periodic-Correlation (APC) algorithm was developed for use in extended-scene Shack-Hartmann wavefront sensors. It provides high-accuracy even when the sub-images in a frame captured by a Shack-Hartmann camera are not only shifted but also distorted relative to each other. Recently we found that the shift-estimate error of the APC algorithm has a component that depends on the content of extended-scene. In this paper we assess the amount of that error and propose a method to minimize it.

Sidick, Erkin↗
NASA NTRS2012

Techniques for Down-Sampling a Measured Surface Height Map for Model Validation

This software allows one to down-sample a measured surface map for model validation, not only without introducing any re-sampling errors, but also eliminating the existing measurement noise and measurement errors. The software tool of the current two new techniques can be used in all optical model validation processes involving large space optical surfaces

Sidick, Erkin↗
NASA NTRS2011

Studies of the Effects of Optical System Errors on the HCIT Contrast Performance

The High Contrast Imaging Testbed (HCIT) at the Jet Propulsion Laboratory employs a broadband wavefront correction algorithm called Electric Field Conjugation (EFC) to obtain the required 10-10 contrast. This algorithm works with one deformable mirror (DM) to estimate the electric-field to be controlled, and with one or multiple DM's to create a "dark-hole" in a predefined region of the image plane where terrestrial planets would be found. We have investigated the effects of DM actuator errors and the optic position errors on the efficiency of the EFC algorithm in a Lyot coronagraph configuration. The structural design of the optical system as well as the parameters of various optical elements used in the analysis are drawn from those of the HCIT system that have been implemented with one DM. The simulation takes into account the surface errors of various optical elements. Results of some of these studies have been verified by actual measurements.

exoplanetsscopes↗
NASA NTRS2010

Advanced Wavefront Sensing and Control Testbed (AWCT)

The Advanced Wavefront Sensing and Control Testbed (AWCT) is built as a versatile facility for developing and demonstrating, in hardware, the future technologies of wave front sensing and control algorithms for active optical systems. The testbed includes a source projector for a broadband point-source and a suite of extended scene targets, a dispersed fringe sensor, a Shack-Hartmann camera, and an imaging camera capable of phase retrieval wavefront sensing. The testbed also provides two easily accessible conjugated pupil planes which can accommodate the active optical devices such as fast steering mirror, deformable mirror, and segmented mirrors. In this paper, we describe the testbed optical design, testbed configurations and capabilities, as well as the initial results from the testbed hardware integrations and tests.

active optics↗
NASA NTRS2010

Studies of the Effects of Actuator Errors on the HCIT/PIAA Contrast Performance

The High Contrast Imaging Testbed Phase Induced Amplitude Apodization (HCIT/PIAA) coronagraph system at JPL relies on an Electric-Field Conjugation (EFC) wavefront correction algorithm to obtain the required high contrast. This algorithm works with one deformable mirror (DM) to estimate the electric-field to be controlled, and with one or multiple DM's to create a "dark-hole" in the image plane. We have investigated the effects of DM actuator errors on the efficiency of the EFC algorithm. The structural design of the optical system as well as the parameters of various optical elements used in the analysis are drawn from those of the HCIT/PIAA system that have been and will be implemented with one or two DM's. The simulation takes into account the surface errors of various optical elements. In this paper, we report our findings in the case of narrowband wavelength light.

PIAA↗
NASA NTRS2010

New Variance-Reducing Methods for the PSD Analysis of Large Optical Surfaces

Edge data of a measured surface map of a circular optic result in large variance or "spectral leakage" behavior in the corresponding Power Spectral Density (PSD) data. In this paper we present two new, alternative methods for reducing such variance in the PSD data by replacing the zeros outside the circular area of a surface map by non-zero values either obtained from a PSD fit (method 1) or taken from the inside of the circular area (method 2).

Surface measurements-roughness↗
NASA NTRS2010

Performance Sensitivity Studies on the PIAA Implementation of the High-Contrast Imaging Testbed

This slide presentation reviews the sensitivity studies on the Phase-Induced Amplitude Apodization (PIAA), or pupil mapping using the High-Contrast Imaging Testbed (HCIT). PIAA is a promising technique in high-dynamic range stellar coronagraph. This presentation reports on the investigation of the effects of the phase and rigid-body errors of various optics on the narrowband contrast performance of the PIAA/HCIT hybrid system. The results have shown that the 2-step wavefront control method utilizing 2-DMs is quite effective in compensating the effects of realistic phase and rigid-body errors of various optics

Phase-Induced Amplitude Apodization (PIAA)↗
NASA NTRS2009

Performance Sensitivity Studies on the PIAA Implementation of the High-Contrast Imaging Testbed

We have investigated the dependence of the High Contrast Imaging Testbed (HCIT) Phase Induced Amplitude Apodization (PIAA) coronagraph system performance on the rigid-body perturbations of various optics. The structural design of the optical system as well as the parameters of various optical elements used in the analysis are drawn from those of the PIAA/HCIT system that have been and will be implemented, and the simulation takes into account the surface errors of various optics. In this paper, we report our findings when the input light is a narrowband beam.

pupil mapping↗
NASA NTRS2009

Power Spectral Density Specification and Analysis of Large Optical Surfaces

The 2-dimensional Power Spectral Density (PSD) can be used to characterize the mid- and the high-spatial frequency components of the surface height errors of an optical surface. We found it necessary to have a complete, easy-to-use approach for specifying and evaluating the PSD characteristics of large optical surfaces, an approach that allows one to specify the surface quality of a large optical surface based on simulated results using a PSD function and to evaluate the measured surface profile data of the same optic in comparison with those predicted by the simulations during the specification-derivation process. This paper provides a complete mathematical description of PSD error, and proposes a new approach in which a 2-dimentional (2D) PSD is converted into a 1-dimentional (1D) one by azimuthally averaging the 2D-PSD. The 1D-PSD calculated this way has the same unit and the same profile as the original PSD function, thus allows one to compare the two with each other directly.

wavefront↗
NASA NTRS2008

Algorithm for Wavefront Sensing Using an Extended Scene

A recently conceived algorithm for processing image data acquired by a Shack-Hartmann (SH) wavefront sensor is not subject to the restriction, previously applicable in SH wavefront sensing, that the image be formed from a distant star or other equivalent of a point light source. That is to say, the image could be of an extended scene. (One still has the option of using a point source.) The algorithm can be implemented in commercially available software on ordinary computers. The steps of the algorithm are the following: 1. Suppose that the image comprises M sub-images. Determine the x,y Cartesian coordinates of the centers of these sub-images and store them in a 2xM matrix. 2. Within each sub-image, choose an NxN-pixel cell centered at the coordinates determined in step 1. For the ith sub-image, let this cell be denoted as si(x,y). Let the cell of another subimage (preferably near the center of the whole extended-scene image) be designated a reference cell, denoted r(x,y). 3. Calculate the fast Fourier transforms of the sub-sub-images in the central NxN portions (where N < N and both are preferably powers of 2) of r(x,y) and si(x,y). 4. Multiply the two transforms to obtain a cross-correlation function Ci(u,v), in the Fourier domain. Then let the phase of Ci(u, v) constitute a phase function, phi(u,v). 5. Fit u and v slopes to phi (u,v) over a small u,v subdomain. 6. Compute the fast Fourier transform, Si(u,v) of the full NxN cell si(x,y). Multiply this transform by the u and phase slopes obtained in step 4. Then compute the inverse fast Fourier transform of the product. 7. Repeat steps 4 through 6 in an iteration loop, cumulating the u and slopes, until a maximum iteration number is reached or the change in image shift becomes smaller than a predetermined tolerance. 8. Repeat steps 4 through 7 for the cells of all other sub-images.

Sidick, Erkin↗
NASA NTRS2008

Dependence of Adaptive Cross-correlation Algorithm Performance on the Extended Scene Image Quality

Recently, we reported an adaptive cross-correlation (ACC) algorithm to estimate with high accuracy the shift as large as several pixels between two extended-scene sub-images captured by a Shack-Hartmann wavefront sensor. It determines the positions of all extended-scene image cells relative to a reference cell in the same frame using an FFT-based iterative image-shifting algorithm. It works with both point-source spot images as well as extended scene images. We have demonstrated previously based on some measured images that the ACC algorithm can determine image shifts with as high an accuracy as 0.01 pixel for shifts as large 3 pixels, and yield similar results for both point source spot images and extended scene images. The shift estimate accuracy of the ACC algorithm depends on illumination level, background, and scene content in addition to the amount of the shift between two image cells. In this paper we investigate how the performance of the ACC algorithm depends on the quality and the frequency content of extended scene images captured by a Shack-Hatmann camera. We also compare the performance of the ACC algorithm with those of several other approaches, and introduce a failsafe criterion for the ACC algorithm-based extended scene Shack-Hatmann sensors.

wave-front sensing and control↗
NASA NTRS2008

An Improved Wavefront Control Algorithm for Large Space Telescopes

Wavefront sensing and control is required throughout the mission lifecycle of large space telescopes such as James Webb Space Telescope (JWST). When an optic of such a telescope is controlled with both surface-deforming and rigid-body actuators, the sensitivity-matrix obtained from the exit pupil wavefront vector divided by the corresponding actuator command value can sometimes become singular due to difference in actuator types and in actuator command values. In this paper, we propose a simple approach for preventing a sensitivity-matrix from singularity. We also introduce a new "minimum-wavefront and optimal control compensator". It uses an optimal control gain matrix obtained by feeding back the actuator commands along with the measured or estimated wavefront phase information to the estimator, thus eliminating the actuator modes that are not observable in the wavefront sensing process.

adaptive optics↗