CBRN Sensor and Sensor Netting Algorithms

Award Information
Agency: Department of Defense
Branch: Office for Chemical and Biological Defense
Contract: W911SR-09-P-0039
Agency Tracking Number: C091-110-0141
Amount: $100,000.00
Phase: Phase I
Program: SBIR
Awards Year: 2009
Solicitation Year: 2009
Solicitation Topic Code: CBD09-110
Solicitation Number: 2009.1
Small Business Information
Torch Technologies, Inc.
4035 Chris Drive, Suite C, Huntsville, AL, 35802
DUNS: 122515708
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Jim Schwaiger
 Principal Investigator
 (256) 319-6000
 jim.schwaiger@torchtechnologies.com
Business Contact
 Kenneth Lones
Title: Director of Contracts
Phone: (256) 319-6019
Email: kenneth.lones@torchtechnologies.com
Research Institution
N/A
Abstract
This Phase I SBIR proposal presents the Torch Technologies approach for the development of advanced, innovative, robust real-time algorithms for the integration of passive and active electro-optical sensor detections and identification information. In our proposal, we detail our ideas regarding the optimal fusion of Chemical Warfare (CW) agent sensor data within the innovative data fusion architecture developed by Torch Technologies for the U.S. Army Dugway Proving Ground (DPG). The proposed approach merges the DPG data fusion architecture, called ACRES (Advanced Chemical Release Evaluation System) with a Fourier Transform (FT) Raman spectrometer model and Ballistic Missile Defense (BMD) sensor network modules, all developed by Torch personnel during the past 10 years, into a single framework. The framework will be designed to support feasibility assessments of enhanced multi-sensor CW data fusion concepts. The primary objective of the Torch Phase I SBIR will be to implement a distributed CW sensor network emulation in order to evaluate the feasibility of enhanced multi-sensor CW data fusion using an ACRES CW Agent identification (ID) feature augmented cloud measurement data fusion process. We will do this using a representative DTRA CW agent sensor track correlation/netting scenario using simulated CW agent sensor data communicated to the sensor data fusion node over an emulation of a Joint Sensor Network. The primary innovation in the Torch proposed effort is to apply our ACRES high-dimensionality CW Agent cloud state vector estimation process as a means to optimize the DTRA CW defense multi-sensor data fusion process.

* information listed above is at the time of submission.

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