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All sourcesNASA NTRSDOE OSTI
NASA NTRS2007

TRL-6 for JWST Wavefront Sensing and Control

NASA's Technology Readiness Level (TRL)-6 is documented for the James Webb Space Telescope (JWST) Wavefront Sensing and Control (WFSC) subsystem. The WFSC subsystem is needed to align the Optical Telescope Element (OTE) after all deployments have occurred, and achieves that requirement through a robust commissioning sequence consisting of unique commissioning algorithms, all of which are part of the WFSC algorithm suite. This paper identifies the technology need, algorithm heritage, describes the finished TRL-6 design platform, and summarizes the TRL-6 test results and compliance. Additionally, the performance requirements needed to satisfy JWST science goals as well as the criterion that relate to the TRL-6 Testbed Telescope (TBT) performance requirements are discussed

Feinberg, Lee↗
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 NTRS2011

Grazing Incidence Wavefront Sensing and Verification of X-Ray Optics Performance

Evaluation of interferometrically measured mirror metrology data and characterization of a telescope wavefront can be powerful tools in understanding of image characteristics of an x-ray optical system. In the development of soft x-ray telescope for the International X-Ray Observatory (IXO), we have developed new approaches to support the telescope development process. Interferometrically measuring the optical components over all relevant spatial frequencies can be used to evaluate and predict the performance of an x-ray telescope. Typically, the mirrors are measured using a mount that minimizes the mount and gravity induced errors. In the assembly and mounting process the shape of the mirror segments can dramatically change. We have developed wavefront sensing techniques suitable for the x-ray optical components to aid us in the characterization and evaluation of these changes. Hartmann sensing of a telescope and its components is a simple method that can be used to evaluate low order mirror surface errors and alignment errors. Phase retrieval techniques can also be used to assess and estimate the low order axial errors of the primary and secondary mirror segments. In this paper we describe the mathematical foundation of our Hartmann and phase retrieval sensing techniques. We show how these techniques can be used in the evaluation and performance prediction process of x-ray telescopes.

Saha, Timo T.↗
NASA NTRS2004

Wavefront Sensing using a Multi-Object Spectrograph (NIRSpec)

An analysis is presented that illustrates how the JWST fine-phasing process can be carried out using NIRSpec data collected at the science focal plane. The analysis is based on a multi-plane diffraction model which properly accounts for the microshutter diffractive element placed at the first relay position of the spectrograph. Wavefront sensing results are presented based on both simulated as well as real data collected from the NASA Goddard Microshutter Testbed.

Dean, Bruce↗
NASA NTRS2011

Hybrid architecture active wavefront sensing and control system, and method

According to various embodiments, provided herein is an optical system and method that can be configured to perform image analysis. The optical system can comprise a telescope assembly and one or more hybrid instruments. The one or more hybrid instruments can be configured to receive image data from the telescope assembly and perform a fine guidance operation and a wavefront sensing operation, simultaneously, on the image data received from the telescope assembly.

Feinberg, Lee D.↗
NASA NTRS2004

Wavefront Sensing Using a Multi-Object Spectrograph (NIRSpec)

An analysis is presented that illustrates how the James Webb Space Telescope (JWST) fine-phasing process can be carried out using the Near-Infrared Spectrograph (NIRSpec) data collected at the science focal plane. The analysis considers a multi-plane diffraction model which properly accounts for the microshutter diffractive element placed at the first relay position of the spectrograph. Wavefront sensing results are presented based on data collected from the NASA Goddard Microshutter Testbed.

Dean, Bruce H.↗
NASA NTRS2012

Common-Path Wavefront Sensing for Advanced Coronagraphs

Imaging of faint companions around nearby stars is not limited by either intrinsic resolution of a coronagraph/telescope system, nor is it strictly photon limited. Typically, it is both the magnitude and temporal variation of small phase and amplitude errors imparted to the electric field by elements in the optical system which will limit ultimate performance. Adaptive optics systems, particularly those with multiple deformable mirrors, can remove these errors, but they need to be sensed in the final image plane. If the sensing system is before the final image plane, which is typical for most systems, then the non-common path optics between the wavefront sensor and science image plane will lead to un-sensed errors. However, a new generation of high-performance coronagraphs naturally lend themselves to wavefront sensing in the final image plane. These coronagraphs and the wavefront sensing will be discussed, as well as plans for demonstrating this with a high-contrast system on the ground. Such a system will be a key system-level proof for a future space-based coronagraph mission, which will also be discussed.

adaptive optics↗
NASA NTRS2015

System and Method for Null-Lens Wavefront Sensing

A method of measuring aberrations in a null-lens including assembly and alignment aberrations. The null-lens may be used for measuring aberrations in an aspheric optic with the null-lens. Light propagates from the aspheric optic location through the null-lens, while sweeping a detector through the null-lens focal plane. Image data being is collected at locations about said focal plane. Light is simulated propagating to the collection locations for each collected image. Null-lens aberrations may extracted, e.g., applying image-based wavefront-sensing to collected images and simulation results. The null-lens aberrations improve accuracy in measuring aspheric optic aberrations.

Hill, Peter C.↗
NASA NTRS2010

Wavefront Sensing of X-Ray Telescopes

Phase Retrieval analysis of off-axis or defocused focal-plane data from telescope optics has been proven effective in understanding misalignments and optical aberrations in normal incidence telescopes. The approach is used, e.g., in commissioning of the James Webb Space Telescope (JWST) segmented primary mirror. There is a similar need for evaluating low-order figure errors of grazing incidence mirrors and nested telescope assemblies. When implemented in these systems, phase retrieval does not depend on normal incidence access to each mirror (shell) surface and, therefore, provides an effective means for evaluating nested x-ray telescopes during integration and test. We have applied a well-known phase retrieval algorithm to grazing incidence telescopes. The algorithm uses the Levenberg-Marquardt optimization procedure to perform a non-linear least-squares fit of the telescope Point Spread Function (PSF). The algorithm can also retrieve low order figure errors at visible wavelengths where optical diffraction is the dominant defect in the PSF. In this paper we will present the analytical approach and its implementation for grazing incidence mirrors of the International X-Ray Observatory (IXO). We analyze the effects of low order axial surface errors individually, and in combination on the system PSF at 633 nanometers. We demonstrate via modeling that the wavefront sensing algorithm can recover axial errors (of the grazing incidence mirrors) to a small fraction of the known axial figure errors using simulated PSFs as input data to the algorithm.

Saha, Timo↗
NASA NTRS2007

An Adaptive Cross-Correlation Algorithm for Extended-Scene Shack-Hartmann Wavefront Sensing

This viewgraph presentation reviews the Adaptive Cross-Correlation (ACC) Algorithm for extended scene-Shack Hartmann wavefront (WF) sensing. A Shack-Hartmann sensor places a lenslet array at a plane conjugate to the WF error source. Each sub-aperture lenslet samples the WF in the corresponding patch of the WF. A description of the ACC algorithm is included. The ACC has several benefits; amongst them are: ACC requires only about 4 image-shifting iterations to achieve 0.01 pixel accuracy and ACC is insensitive to both background light and noise much more robust than centroiding,

Terrestrial Planet Finder (TPF)↗
NASA NTRS2017

Wavefront sensing for a future HabEx space telescope.

HabEx is a concept study for a next generation space telescope having a 4 to 6.5 m primary mirror diameter. Primarily designed for exoplanet science, but also carrying general astrophysics instruments, it will have stability requirements orders of magnitude more stringent than any previously flown space-based observatory. Wavefront control, including active sensing/control of wavefront jitter and drift, will be essential to achieving and maintaining coronagraph performance. There are currently two complementary techniques that can be used to sense the wavefront drift. An attractive method is to use starlight rejected from the coronagraph to sense changes in the wavefront incident on the coronagraph mask. This method suffers from photon noise especially when imaging dim stars. It is also unavailable during slews between target stars. Laser metrology is a complementary system in which a laser “truss” enables rigid body displacements of the optics to be measured from changes in the separation of pairs of optical fiducials which can be separated by many meters. In closed loop with actuated optics, laser metrology actively maintains rigid body alignment of the front-end optics, thereby eliminating the dominant source of wavefront drift. This method can maintain rigid body stability of the telescope optics and thereby wavefront control, even during slews between targets.

Martin, Stefan↗