NASA SBIR 2019-I Solicitation

Proposal Summary

 19-1- A3.03-3040
 Future Aviation Systems Safety
 Smart UAS Information Network
SMALL BUSINESS CONCERN (Firm Name, Mail Address, City/State/Zip, Phone)
Mosaic ATM, Inc.
540 Fort Evans Road Northeast, Suite 300
Leesburg, VA 20176- 3379
(800) 405-8576

Principal Investigator (Name, E-mail, Mail Address, City/State/Zip, Phone)

Mr. Tim Bagnall
540 Fort Evans Road NE, Suite 300 Leesburg, VA 20176 - 3379
(571) 423-9429

Business Official (Name, E-mail, Mail Address, City/State/Zip, Phone)

Chris Stevenson
540 Fort Evans Road NE, Suite 300 Leesburg, VA 20176 - 3379
(540) 454-7458
Estimated Technology Readiness Level (TRL) :
Begin: 2
End: 3
Technical Abstract (Limit 2000 characters, approximately 200 words)

Over the past decade, hobbyist and commercial small Unmanned Aircraft System (sUAS) operations in the United States have greatly expanded, and forecasts predict that the trend will continue into the foreseeable future. With this expansion has come conflict with traditional manned aircraft. Already, and within the last five years, there have been several mid-air collisions, near-miss incidents, and other accidents involving sUASs. This proliferation of unmanned aircraft operations raises serious safety concerns for manned aircraft. To confront this present and growing danger, pilots need a robust, system-wide alerting system to increase situational awareness (SA) of nearby sUAS activity.

In this proposal, Mosaic ATM and Drone Traffic outline a plan for a software product that increases pilot SA by warning them of actual and potential sUAS activity in their area. The proposed innovation, the Smart UAS information Network (SUN), will integrate and fuse a wide array of disparate surveillance data, including airborne and terrestrial sensors and crowd-sourced sUAS activity reports, to present timely and user-tailored sUAS safety alerts to pilots. The ultimate vision for the proposed innovation – a Waze for aviation – is as a stand-alone flight application, or as a supplement to existing applications such as ForeFlight, living within a pilot’s electronic flight bag (EFB). At the heart of the innovation is a combination of deep learning techniques for classifying and identifying sUASs and generating their likely trajectories. A rich graphical user interface will provide current flight status, future trajectory information, and SUN’s safety-focused sUAS warning information embedded within 2D and 3D mapping displays.

Potential NASA Applications (Limit 1500 characters, approximately 150 words)
  • The proposed solution has applications in projects falling under the Airspace Operation and Safety program, especially those oriented towards future aviation systems like UAM and ATM-X.
  • The proposed solution could be adapted to include other aircraft besides sUASs, including thin-haul vehicles, urban air taxis, and other new vehicles.
Potential Non-NASA Applications (Limit 1500 characters, approximately 150 words)
  • General and commercial aviation customers, as well as UAS operators. The most immediate marketable product will be in the form of an application on an Electronic Flight Bag.
  • Government agencies interested in public safety like the Department of Homeland Security, Federal Aviation Administration, and local police forces and fire departments.
Duration: 6

Form Generated on 06/16/2019 23:35:17