Optimal Detection and Classification in a Centralized Network of Asynchronous Sensors

Award Information
Agency:
Department of Defense
Branch
n/a
Amount:
$99,952.00
Award Year:
2011
Program:
SBIR
Phase:
Phase I
Contract:
W15P7T-11-C-H261
Agency Tracking Number:
A111-028-0418
Solicitation Year:
2011
Solicitation Topic Code:
A11-028
Solicitation Number:
2011.1
Small Business Information
Ivysys Technologies, LLC
4501 N. Fairfax Drive, Suite 920, Arlington, VA, 22203
Hubzone Owned:
N
Minority Owned:
Y
Woman Owned:
N
Duns:
608730714
Principal Investigator:
Wil Myrick
Chief Scientist
(703) 414-5665
wil@ivysys.com
Business Contact:
Anthony Hayter
Director of Business Development
(703) 414-5665
ahayter@ivysys.com
Research Institution:
Stub




Abstract
IvySys proposes novel asynchronous signal sensing and automatic modulation classification (AMC) approaches that leverage a centralized network of low-cost asynchronous sensors to enable weak signal detection and classification. These innovative approaches will provide detection performance within 3 to 5 dB Signal-to-Interference-plus-Noise Ratio (SINR) of a centralized network of synchronous sensors. This asynchronous signal sensing processing architecture combines weak signal Cross Ambiguity Function (CAF) detection with Maximal Ratio Combining (MRC) to improve probability of detection, while minimizing the probability of false alarm. We plan to extend the CAF mathematical algorithm framework to address asynchronous signal correlations and build upon existing MRC techniques, which are inherently robust to signal fading. We will investigate both traditional and cyclic CAF processing algorithms. The cyclic CAF is inherently robust to channel distortion allowing for increased SINR for a given Signal of Interest (SOI), thereby enhancing weak signal detection. We will also leverage a sensor network simulation tool (LPIsimNET) to provide both planning and prediction capability for sensor placement based on maximizing SINR for single input multiple-output (SIMO) configurations.

* information listed above is at the time of submission.

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