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Turbulence Awareness via Real-Time Data Mining

Award Information
Agency: National Aeronautics and Space Administration
Branch: N/A
Contract: 80NSSC18C0144
Agency Tracking Number: 174883
Amount: $750,000.00
Phase: Phase II
Program: SBIR
Solicitation Topic Code: A3
Solicitation Number: SBIR_17_P2
Solicitation Year: 2017
Award Year: 2018
Award Start Date (Proposal Award Date): 2018-04-25
Award End Date (Contract End Date): 2020-04-24
Small Business Information
2360 SW Chelmsford Avenue
Portland, OR 97201-2265
United States
DUNS: 802036496
HUBZone Owned: No
Woman Owned: Yes
Socially and Economically Disadvantaged: No
Principal Investigator
 Jimmy Krozel
 (503) 242-1761
Business Contact
 Michelle Camarda
Phone: (503) 242-1761
Research Institution

Automatic Dependent Surveillance - Broadcast (ADS-B) has been mandated by the FAA for all aircraft that fly in Class A airspace in year 2020 and beyond.  ADS-B will be the foundation of surveillance, and in this SBIR effort, we exploit the fact thta ADS-B data can also provide evidence of aircraft flying through known sources of aviation turbulence. Phase I R&D showed that moderate or greater levels of turbulence can be identified by analyzing in real-time certain key features observable from ADS-B data.  Mountain wave turbulence, clear air turbulence, and convective induced turbulence events can all be identified from the data mining approach that we have developed.  Analysis results can be performed in near real time and in an automated fashion, and can trigger safety alerts on AOC dispatcher displays or can be used to build better turbulence forecasts and nowcasts.

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

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