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IR/RF SPARK - IR/RF fusion using Stochastic Programming And Robust Kinematic…

Award Information

Agency:
Department of Defense
Branch:
Missile Defense Agency
Award ID:
Program Year/Program:
2013 / STTR
Agency Tracking Number:
B12A-002-0036
Solicitation Year:
2012
Solicitation Topic Code:
MDA12-T002
Solicitation Number:
2012.A
Small Business Information
Scientific Systems Company, Inc
500 West Cummings Park - Ste 3000 Woburn, MA -
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Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No
 
Phase 1
Fiscal Year: 2013
Title: IR/RF SPARK - IR/RF fusion using Stochastic Programming And Robust Kinematic features
Agency / Branch: DOD / MDA
Contract: HQ0147-13-C-7189
Award Amount: $99,999.00
 

Abstract:

SSCI and MIT team will approach a problem of fusing target data from sensor of different phenomenology using Probabilistic programming technology, Stochastic inference techniques based on Markov chain simulation, and Robust kinematic features. These methods will allow us to estimate the extend of information on metric, material, and kinematic properties of the observed low resolution targets available through infra-red and radar sensors. Any collaborating information available through both sensors would help their association and tracking between sensors of different phenomenology. Stochastic inference techniques based on Markov chain simulation will be employed to rapidly identify accurate interpretations of the data. Probabilistic programs go beyond classical pattern recognition techniques, statistical learning methods and Bayesian networks. These programs simulate hypothetical worlds according to the prior assumptions. Each possible execution path of the probabilistic program constitutes a distinct hypothesis over which Bayesian inference can be performed. In this framework, it becomes natural to capture detailed physical prior knowledge, even if the distributions involved are highly non-Gaussian and their time evolution is highly non-linear, making analytical representations intractable. The programs will also help the team assess the best wavebands to provide the richest set of potentially useful features for target characterization.

Principal Investigator:

Ranga Narayanaswami
Sr Grp Leader: Signal Exploitation
(781) 933-5355
rangan@ssci.com

Business Contact:

Jay Miselis
Corporate Controller
(781) 933-5355
contracts@ssci.com
Small Business Information at Submission:

Scientific Systems Company, Inc
500 West Cummings Park - Ste 3000 Woburn, MA -

EIN/Tax ID: 043053085
DUNS: N/A
Number of Employees:
Woman-Owned: No
Minority-Owned: Yes
HUBZone-Owned: No
Research Institution Information:
MIT
77 Massachusetts Avenue
Cambridge, MA 02139-4307
Contact: Josh Tenebaum
Contact Phone: (617) 452-2010