Advanced Algorithms for Data Fusion with 3-D Image Reconstruction from

Award Information
Agency:
Department of Defense
Branch
Missile Defense Agency
Amount:
$99,531.00
Award Year:
2009
Program:
SBIR
Phase:
Phase I
Contract:
HQ0006-09-C-7162
Agency Tracking Number:
B083-039-0281
Solicitation Year:
n/a
Solicitation Topic Code:
n/a
Solicitation Number:
n/a
Small Business Information
INTELLIGENT SYSTEMS RESEARCH, INC.
3390 Auto Mall Drive, Thousand Oaks, CA, 91362
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
N
Duns:
068577175
Principal Investigator:
Phillip Dennis
Senior Scientist
(805) 409-0429
Phillip.Dennis@isrweb.com
Business Contact:
William Cook
President
(805) 409-0429
William.Cook@isrweb.com
Research Institution:
n/a
Abstract
Creating a real-time single integrated missile picture for defense against enemy missile attacks presents technical challenges due to both sensor measurement errors and discrimination uncertainties that arise from the nature of missile object characteristics and signatures. Successful intercept of lethal objects is critically degraded if uncertainties preclude the effective discrimination of lethal vs. non-lethal objects. A promising approach to reduce the effects of these uncertainties and enhance threat object discrimination is the use of 3-D object imaging techniques using all of the features and signature data provided from the network of distributed sensors. An integrated robust fusion process can enhance discrimination by considering the "cross correlations" that exist between data from multiple, geographically diverse networked sensors. To achieve this, the fusion process must be capable of fusing dissimilar data including radar feature data and thermal imagery from sources such as on-board IR sensors and SBIRS. An effective fusion approach that includes 3-D imaging must fit within processor throughput and network communication bandwidth constraints. Thus, a key consideration in multi-sensor fusion using distributed data is the Value of Information (VOI) of reported data and cost in terms of processor and network resources required to collect and disseminate the data.

* information listed above is at the time of submission.

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