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Multiple Deep Spectrum Usage Models (MUDSUM)

Award Information
Agency: Department of Defense
Branch: Navy
Contract: N68335-22-C-0379
Agency Tracking Number: N221-073-0622
Amount: $140,000.00
Phase: Phase I
Program: SBIR
Solicitation Topic Code: N221-073
Solicitation Number: 22.1
Solicitation Year: 2022
Award Year: 2022
Award Start Date (Proposal Award Date): 2022-06-06
Award End Date (Contract End Date): 2022-12-06
Small Business Information
3527 Beverly Glen Blvd.
Sherman Oaks, CA 91423-1111
United States
DUNS: 124668711
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Timur Chabuk
 (571) 235-5720
Business Contact
 Elan Freedy
Phone: (703) 200-4104
Research Institution

As the electromagnetic spectrum becomes increasingly crowded, it is critical that US ground force and tactical Signals Intelligence (SIGINT) and EW sensors are able to quickly and automatically scan large swaths of the RF spectrum and make sense of usage by private, commercial, civil and military entities operating a given area. Machine understanding of patterns of both routine and anomalous signal behavior would provide an indispensable advantage to operators monitoring and analyzing spectrum usage, allowing them to focus their efforts on only the most meaningful and actionable detections. The MUDSUM is an ML/AI system using a modular architecture which integrates deep signal detection, deep signal characterization, and a suite of pattern of life modeling methods, with domain relevant subject matter expertise. MUDSUM will be able to model dynamics in single emitters, multiple emitters of different classes, and additionally use context aware methods which model current behavior of the spectrum given the recent past. This multitiered and multiaspect method provides insight into typical and atypical behavior from multiple angles giving operators a large amount of visibility into the state and projected state of spectrum usage. MUDSUM’s Phase I development will culminate in a proof of concept demonstration, evaluating the suite of signal detection, characterization, and behavior modeling tools.

* Information listed above is at the time of submission. *

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