FINANCIAL ASSISTANCE FUNDING OPPORTUNITY ANNOUNCEMENT Small Business Innovation Research (SBIR) Small Business Technology Transfer (STTR
- 27: REMOTE SENSING
- Description: The Office of Defense Nuclear Nonproliferation Research and Development (NA-22) has a research objective to develop remote sensing technology to support detection and characterization of signatures or activities related nuclear proliferation.
- b: Development and Validation of a Polarized 3D Atmospheric Radiation Model
- Description: Increasing signature contrast in both the solar and thermal spectral regions, obtained from the Stokes vector data, provides advanced avenues for improving material identification. Analysis of these data requires polarization signature models that incorporate the effects of absorption, emission and scattering in the 3D atmospheric and terrain environment. Although high fidelity, scalar, 1D atmospheric radiative transfer models are readily available [Berk et al. 2006], few 1D polarization models [MODTRAN-P, vector-6S] have been developed. These 1D polarized models have significant limitations in spectral coverage, computational speed, optical polarization databases, and-or physics fidelity. There are currently no available models that treat all the polarized spectral signatures of key 3D scene elements such as clouds, plumes, topographic backgrounds, and man-made objects in a self-consistent, unified approach. Research is sought to develop a validated 3D polarized atmospheric radiation transport model. The Phase I effort should focus (1) on assessing current 1D capabilities and available polarization databases, (2) on formulating approaches for upgrades to the 1D models for a fully polarized implementation in Phase II, (3) on designing a 3D polarization model, and (4) on planning validation field measurements in collaboration with a DOE lab. A validated 3D polarized radiance model that incorporates the effects of water clouds, plumes, natural terrain and turbid water backgrounds, and both man-made and natural materials will be developed in Phase II. The new model will be tested against the existing 1D models and validated against DOE field measurements.
- c: Information-Theoretic Compressive Sensing for Efficient Standoff Monitoring
- Description: Modern remote sensing systems are characterized by collection of a massive quantity of data, particularly for long-term monitoring. For example, hyperspectral sensors involve measurement of possibly hundreds of wavelengths. In addition, one may be interested in measuring hyperspectral video, potentially at multiple focal points. Research is sought for a new framework that will be constituted for compressive measurements, in which the complexity (bandwidth and energy) is taken into account within the sensor. Application areas include compressive hyperspectral imagers, compressive video, compressive multi-focus, and compressive mass spectrometry, among many others. The emphasis is not just on systems that may be characterized by Gaussian noise, but also by sensors and data types better characterized with Poisson noise (count measurements). In addition to developing the theory for such compressive measurements, laboratory experiments will be performed, for demonstration of proof of concept. In Phase II, the final system will be applicable to remote sensing, will substantially reduce the quantity of data collected relative to a conventional sensor, and the sensor complexity will be no greater than that of conventional sensing systems.
- d: Other
- Description: In addition to the specific subtopics listed above, the Department invites grant applications in other areas relevant to this Topic.