Asynchronous Network Signal Sensing and Classification Techniques

Award Information
Agency: Department of Defense
Branch: Army
Contract: W15P7T-11-C-H262
Agency Tracking Number: A111-028-1296
Amount: $149,979.00
Phase: Phase I
Program: SBIR
Awards Year: 2011
Solicitation Year: 2011
Solicitation Topic Code: A11-028
Solicitation Number: 2011.1
Small Business Information
ANDRO Computational Solutions, LLC
Beeches Technical Campus, 7902 Turin Road, Ste. 2-1, Rome, NY, -
DUNS: 883336190
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Andrew Drozd
 President and Chief Engineer
 (315) 334-1163
 adrozd@androcs.com
Business Contact
 Kristin Case
Title: Contracts Administrator
Phone: (315) 334-1163
Email: kcase@androcs.com
Research Institution
 Stub
Abstract
This SBIR project will develop a distributed sensor network framework capable of synchronous/asynchronous automatic modulation classification (AMC) in a non-cooperative communication environment where the received signal is unknown and weak. During the Phase I of this effort, we will focus our attention to synchronous/asynchronous AMC based on a distributed decision fusion network using parallel fusion architecture, because of the robustness, the scalability and the flexibility it offers. The developed distributed sensor network will include optimized local sensor decision rules as well as optimized fusion rules at the fusion center. The first goal of this project will be the generalization of the well-established distributed detection and data fusion results to the multiclass weak signal AMC problem which is not a trivial task. We will investigate both soft decision based multiclass classifiers along with multiclass fusion rules and binary decision tree classifiers. We will also address various other open research problems in distributed AMC including incorporation of the wireless channel uncertainties between local sensors and the fusion center, bandwidth management in a bandwidth constrained sensor network and security issues. We will perform feasibility studies in a number of operating conditions through computer simulations and theoretical analyses.

* information listed above is at the time of submission.

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