SBIR/STTR Research Award
Multi-Object Spectrometer for Space Object Identification
Award amount
$98,779Program and phase
SBIR · Phase IAward year
2010Award details
- Awarding agency
- Department of Defense
- Branch
- Air Force
- Recipient company
- ASE OPTICS
- Proposal award date
- 2010-03-26
- Contract end date
- 2011-03-28
- UEI
- Not reported
- Solicitation number
- 2009.3
- Topic code
- AF093-056
Research abstract
Approximately 19,000 resident space objects (RSOs) larger than 10 cm are known to be orbiting Earth.[1] These objects range from active payloads, such as satellites, to "space junk."[2] Currently these objects are tracked using Ground-Based Electro-Optical Deep Space Surveillance (GEODSS). There is a growing need for hyperspectral Space Situational Awareness (SSA) to detect and classify RSOs. Such capabilities would enable the identification of new satellites and the observation of distant, spatially unresolved targets. The purpose of this project is to advance the design of a digital micromirror device multi-object spectrometer (DMDMOS-II). ASE Optics has previously partnered with the Rochester Institute of Technology (RIT) and Geospatial Systems, Inc. (formerly Pixel Physics) to develop a DMD-based Multi-Object Spectrometer (DMDMOS). This technology has been proven for use in the MK spectral classification of individual stars within a star cluster. ASE Optics proposes to reconfigure the existing DMDMOS technology into a new sensor, DMDMOS-II, which will enable the sensor to cover the spectral range of 450-1800 nm with a lager field-of-view and a higher collection efficiency to meet the specific needs of spectrally classifying RSOs for improved SSA. BENEFIT: The advanced Digital Micromirror Device Multi-object Spectrometer (DMDMOS-II) that will be developed during Phase I of this project will enable improved Space Situational Awareness of resident space objects (RSOs). We also expect significant applications for the DMDMOS-II in the areas of perimeter surveillance, and homeland defense. The instrument enables rapid, high-resolution classification of objects in the field of view, and can adapt to a changing scene in real-time. Over the past 10 years, hyperspectral technology has also been adopted for many commercial applications such as food inspection and safety, quality control of flat-panel screens and increasing pharmaceutical production yields. The next wave of adoption is currently under way in biotechnology, life sciences and medicine.
Technology keywords
Not reported
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