Estimation and Prediction of Unmanned Aerial Vehicle Trajectories

Award Information
Agency:
National Aeronautics and Space Administration
Amount:
$599,754.00
Program:
SBIR
Contract:
NNX11CA33C
Solitcitation Year:
2009
Solicitation Number:
N/A
Branch:
N/A
Award Year:
2011
Phase:
Phase II
Agency Tracking Number:
095581
Solicitation Topic Code:
A3.01
Small Business Information
Numerica Corporation
CO, Suite 200, Loveland, CO, 80538-6010
Hubzone Owned:
N
Woman Owned:
N
Socially and Economically Disadvantaged:
N
Duns:
956324362
Principal Investigator
 Jason Adaska
 Principal Investigator
 (970) 612-2329
 jason.adaska@numerica.us
Business Contact
 Jeff Poore
Title: Business Official
Phone: (970) 461-2000
Email: jeff.poore@numerica.us
Research Institution
 Stub
Abstract
There is serious concern about the introduction of Unmanned Aerial Vehicles (UAV) in the National Air Space (NAS) because of their potential to increase the risk of collision between aircraft. At present, many UAV platforms lack a Sense and Avoid (SAA) capability to mitigate collision risk, and this has prevented both the government and private contractors from using these platforms in critically needed reconnaissance, surveillance, and security enforcement missions. To demonstrate a SAA capability that is applicable to a wide range of UAV platforms, advanced trajectory estimation and prediction algorithms are developed and used to exploit a small collision avoidance radar currently under development for UAV operation. Collision prediction algorithms will assess potential risk in probabilistic terms using adaptive techniques that permit accurate predictions across long time horizons. Techniques to ensure these predictions are robust to modeling uncertainty increase the utility the developed SAA capability for realistic scenarios.

* information listed above is at the time of submission.

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