SBIR-STTR Award

We will develop new computational techniques to extend the reach of large ground-based optical systems, enabling high resolution imaging of satellites under daylight conditions. Current state-of-the-art systems, such as the 3.6 m AEOS telescope, dramatically underperform in such conditions because of strong turbulence generated by solar heating. Our approach will exploit a priori physical constraints on the imaging process that have hitherto not been incorporated or not fully exploited in MFBD algorithms. The new algorithm, which may be used with seeing-limited data or as an adjunct to partial compensation with adaptive optics, will restore imaging to the diffraction limit even under the extreme conditions of daylight observing. We will develop a numerical simulation to explore the added value of the following constraints: * Exploitation of temporal coherence in high-cadence images through an extension to a multi-layer frozen flow turbulence model. * Inclusion of simultaneous wave-front sensor information. * Constraints imposed by ratios of image spectra and by observed “zeros” in the moduli of spectra of the object and point-spread functions. * Constraints imposed through polarization and wavelength diversity imaging, and the use of multiple telescopes. In addition, we will where possible assess the performance of each constraint by evaluating the Cramér-Rao lower bounds on the variance of estimated parameters.

Benefit:
Benefits to the government are the ability to make high resolution images of satellites from ground-based optical surveillance facilities even in daylight conditions. This dramatically reduces the typical wait time to acquire an observation of a particular satellite since it relieves the requirement to wait for a particular geometrical configuration with respect to the sun. Commercial applications include: * Extending the sensitivity and range of airborne EO/IR ISR systems. * Post-processing of astronomical images taken with partial compensation using adaptive optics, thus allowing higher resolution observations at shorter wavelengths. * Image sharpening in the movie and TV industry.

Keywords:
Multi-Frame Blind Deconvolution, High-Resolution Imaging, Adaptive Optics, Telescopes, Space Situational Awareness, Intelligence Surveillance And Reconnaissance

A new algorithm, the Daylight Object Restoration Algorithm (DORA), has been developed. DORA includes a novel implementation of the multi-frame blind deconvolution image restoration concept which recovers high-quality object estimates from sequences of degraded images. DORA removes the effects of atmospheric aberration in images recorded at ground-based telescopes, and is designed to operate under seeing conditions much more severe than any previous approach can address. We have demonstrated that DORA restores high quality object estimates in seeing as bad as D/r0=70 (D is the telescope diameter and r0 is the Fried parameter). This is more than three times worse than the seeing at which conventional techniques begin to fail. We will implement DORA as a parallel code on a supercomputing platform at the MHPCC. We will begin with an integrated version of DORA for a single processor, and continue to the parallel version. Both will be tested with simulated and real data, to include data from the Maui Space Surveillance System. We will develop the parallel code in a manner that will facilitate its deployment on a variety of computing platforms. This will support the range of commercialization targets that have been identified, which will have unique hardware requirements.

Benefit:
Benefits to the government are the ability to make high resolution images of satellites from ground-based optical surveillance facilities even in daylight conditions. This dramatically reduces the typical wait time to acquire an observation of a particular satellite since it relieves the requirement to wait for a particular geometrical configuration with respect to the sun. Commercial applications include long-path horizontal imaging; post-processing of astronomical observations recorded with partial adaptive optics correction, thus allowing sharper images at shorter wavelengths; image sharpening in the movie industry.

Keywords:
Multi-Frame Blind Deconvolution, High-Resolution Imaging, Image Sharpening, Telescopes, Space Situational Awareness, Intelligence Surveillance And Reconnaissance