Universal Signal Matching for RF Threat Classification

Award Information
Agency:
Department of Defense
Branch
Navy
Amount:
$149,890.00
Award Year:
2009
Program:
SBIR
Phase:
Phase I
Contract:
N68936-09-C-0109
Agency Tracking Number:
N092-113-0158
Solicitation Year:
2009
Solicitation Topic Code:
N092-113
Solicitation Number:
2009.2
Small Business Information
Michigan Aerospace Corporation
1777 Highland Drive, Suite B, Ann Arbor, MI, 48108
Hubzone Owned:
N
Socially and Economically Disadvantaged:
N
Woman Owned:
N
Duns:
969868298
Principal Investigator:
David Johnson
Senior Scientist
(734) 975-8777
djohnson@michaero.com
Business Contact:
Peter Tchoryk
Chief Executive Officer
(734) 975-8777
ptchoryk@michaero.com
Research Institution:
n/a
Abstract
In response to Navy SBIR Topic N092-113, “Universal Signal Matching for RF Threat Classification,” Michigan Aerospace Corporation proposes a robust method to identify emitter Electronic Intelligence Notation types from sensor data streams based on state-of-the-art techniques in estimation and detection for radar signatures developed in the arena of Signals Intelligence for Specific Emitter Identification. Our approach combines advanced time-frequency analysis to generate feature vectors for individual pulses, with cluster analysis for de-interleaving. This provides the basis for identifying the frequency agility of pulses as well as the PRI agility of the radars. These features are then compared to a library using Ensembles of Decision Trees, which provide robust classification as well as known/unknown detection. The feature vectors of newly discovered emitters are added to the library and additional examples of previously-known emitters are added to supplement description of the higher-order statistics of the clusters of these emitters in feature space. RF data streams from observational platforms often contain instances of several emitters, multi-path artifacts, and receiver coloration. It is possible to obtain concurrent streams from multiple platforms. In this situation, we employ a technique like Blind Equalization Source Recovery to recover undistorted transmitted pulses from the plurality of sensors.

* information listed above is at the time of submission.

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