Innovative Sensing Techniques for Urban Operations

Award Information
Agency:
Department of Defense
Branch
Air Force
Amount:
$99,971.00
Award Year:
2007
Program:
SBIR
Phase:
Phase I
Contract:
FA8650-07-M-1178
Agency Tracking Number:
F071-249-0213
Solicitation Year:
2007
Solicitation Topic Code:
AF071-249
Solicitation Number:
2007.1
Small Business Information
BLACK RIVER SYSTEMS CO., INC.
162 Genesee Street, Utica, NY, 13502
Hubzone Owned:
N
Socially and Economically Disadvantaged:
N
Woman Owned:
N
Duns:
111305843
Principal Investigator:
Walter Szczepanski
Principal Investigator
(315) 732-7385
szczepanski@brsc.com
Business Contact:
Milissa Benincasa
Vice President
(315) 732-7385
benincasa@brsc.com
Research Institution:
n/a
Abstract
Black River Systems Co., Inc. and EnerLab, Inc. propose to investigate and develop advanced signal processing techniques necessary for radar detection, imaging and characterization of dismounts in urban environments. We will investigate the feasibility of developing, testing, and implementing a conceptually new signal processing technique, Spatial-Temporal Differential Analysis, which will reliably detect weak, slowly moving targets and to extract unique characteristics in extremely hostile urban environments. This technique provides significant additional sensitivity, flexibility in bandwidth and polarization, and time occupancy benefits for existing GMTI radar systems, as well as for future distributed radar architectures. The developed technique will provide a rapid insertion capability into existing, stand-alone radars, including coarse resolution monopulse radars, featuring computationally efficient, parallel digital signal processing. The technique does not require changes to existing radar designs, utilizes existing A/D digital outputs, is considered as a complementary technique to existing radar signal processing and can be implemented in parallel with existing signal processing. Based on preliminary results, the STDA technique promises to be fully robust to a wide variety of environments. We propose a comprehensive program to analyze and model dismounts and to apply STDA techniques to ensure detection and characterization of their signatures in urban environments.

* information listed above is at the time of submission.

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