Model-Based Classification for Laser Radar

Award Information
Agency: Department of Defense
Branch: Missile Defense Agency
Contract: HQ0006-02-C-0021
Agency Tracking Number: 02-0342
Amount: $70,000.00
Phase: Phase I
Program: SBIR
Awards Year: 2002
Solicitation Year: N/A
Solicitation Topic Code: N/A
Solicitation Number: N/A
Small Business Information
Alphatech, Inc.
50 Mall Road, Burlington, MA, 01803
DUNS: 094841665
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 William Snyder
 Senior Research Engineer
 (781) 273-3388
 william.snyder@alphatech.com
Business Contact
 Andrew Mullin
Title: Gen. Cnsl. & Dir. of Cont
Phone: (781) 273-3388
Email: andy.mullin@alphatech.com
Research Institution
N/A
Abstract
"Laser Radar (ladar) sensors are under consideration for BMD ground and interceptor platforms. An advantage of ladar over other modalities, such as SAR, is that it has very high range and Doppler (range rate) resolution. Therefore, ladar has the potentialto separate, characterize, and classify closely spaced objects, which is a critical part of the BMD problem. To realize this potential for complex threat clouds requires advanced scene understanding methods. We propose to apply the model-based approach,where features extracted from the collected data are matched with those predicted from a physical model of the scene. In this SBIR, we develop and evaluate a model-based approach suitable for ladar data analysis that results in a probabilistic physicaldescription of closely-spaced objects in the scene. For BMD, the model parameters of interest include the number of objects, and object shapes, locations, and kinematics. This work will combine the expertise of two companies: ALPHATECH, Inc. willdevelop the model-based scene understanding system, based on our experience as lead algorithm developers in the MSTAR SAR ATR program. The sub-contractor, SPARTA, Inc. provides expertise on ladar phenomenology and in simulating realistic ladar signaturesfor feature prediction, as well as for test and evaluation. The technology developed under this program will contribute directly to the BMDO objective of improving threat object classification

* information listed above is at the time of submission.

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