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BRDF Analysis of LADAR-based Target Surface Characterization

Award Information
Agency: Department of Defense
Branch: Army
Contract: W911NF-11-C-0014
Agency Tracking Number: A10A-006-0064
Amount: $99,998.00
Phase: Phase I
Program: STTR
Solicitation Topic Code: A10A-T006
Solicitation Number: 2010.A
Solicitation Year: 2010
Award Year: 2010
Award Start Date (Proposal Award Date): 2010-10-15
Award End Date (Contract End Date): 2011-04-13
Small Business Information
4 Fourth Avenue
Burlington, MA 01803
United States
DUNS: 047627732
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Xuemin Jin
 Principal Scientist
 (781) 273-4770
Business Contact
 Fritz Bien
Title: President
Phone: (781) 273-4770
Research Institution
 University of California Irvine
 Alexei A Maradudin
Department of Physics
Irvine, CA 92697
United States

 (949) 824-5943
 Nonprofit College or University

LADAR light reflection from a target is highly dependent of the spectral reflectivity and texture properties of the surface. Such dependencies could be exploited for target recognition based on surface characterization with appropriate imaging conditions and processing algorithms. Target surface light reflection is characterized by the Bidirectional Reflectance Distribution Function (BRDF), which is embedded in LADAR reflected returns. We propose to develop an extended LADAR capability for characterizing and classifying surface material and texture by exploiting multispectral polarimetric LADAR signatures based on the BRDF. The key innovation in this proposal is the comprehensive unified application of waveband spectra, polarization, tomographic reconstruction, and material science to LADAR-based remote target classification. The proposed system incorporating these advances is called LADAR-based Surface Analysis by Reflectance (LASAR). Key features of LASAR include BRDF modeling, a database of target and ground materials, range profile simulation, and material inversion algorithms. The results from Phase I will be used to define real-time algorithms for remote target recognition applications in Phase II.

* Information listed above is at the time of submission. *

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