NASA SBIR 2015 Solicitation

FORM B - PROPOSAL SUMMARY


PROPOSAL NUMBER: 15-1 A3.02-9414
SUBTOPIC TITLE: Autonomy of the National Airspace System (NAS)
PROPOSAL TITLE: Anomaly Detection to Improve Airspace Safety and Efficiency

SMALL BUSINESS CONCERN (Firm Name, Mail Address, City/State/Zip, Phone)
Metron, Inc.
1818 Library Street
Reston, VA 20190 - 5602
(703) 787-8700

PRINCIPAL INVESTIGATOR/PROJECT MANAGER (Name, E-mail, Mail Address, City/State/Zip, Phone)
Dr. Gregory A Godfrey
godfrey@metsci.com
1818 Library Street
Reston, VA 20190 - 5602
(703) 787-8700 Extension :2897

CORPORATE/BUSINESS OFFICIAL (Name, E-mail, Mail Address, City/State/Zip, Phone)
Mr. Seth Blackwell
blackwell@metsci.com
1818 Library Street
Reston, VA 20190 - 5602
(703) 787-8700

Estimated Technology Readiness Level (TRL) at beginning and end of contract:
Begin: 3
End: 5

Technology Available (TAV) Subtopics
Autonomy of the National Airspace System (NAS) is a Technology Available (TAV) subtopic that includes NASA Intellectual Property (IP). Do you plan to use the NASA IP under the award?
No

TECHNICAL ABSTRACT (Limit 2000 characters, approximately 200 words)
As the air transportation system becomes increasingly autonomous over the next twenty years, there will be an increasing need for monitoring capabilities that operate in the background to identify anomalous behaviors consistent with either safety or efficiency deficiencies. Today, these behaviors are largely detected after an incident has occurred. In July 2013, an Asiana Boeing 777 flew too low approaching San Francisco International Airport (SFO), its tail hitting a seawall and crashing into the runway. Three people died and 180 were injured.
Since the weather was clear and visibility unimpeded, part of the instrument landing system (the glideslope transmitter) was offline for service, thus requiring pilots to land visually. The National Transportation Safety Board (NTSB) found that the Asiana pilots' reliance on the automated flight systems was a key factor in that crash. Further analysis by the Wall Street Journal revealed that foreign pilots required more "go-arounds" at SFO than U.S. pilots in the six weeks prior to the Asiana Airlines crash (i.e., when the glideslope transmitter was down), indicating a greater difficulty in executing the landing via visual approach.
This type of anomalous behavior could have been detected prior to the crash. All of the data was available, but no one was looking at it to see these consistent, yet anomalous behaviors. Metron proposes to develop a semi-autonomous background monitoring system to apply this type of data mining and data discovery to recent historical track repositories in order to identify opportunities for improvements to safety and efficiency in airspace operations. Metron proposes a statistical approach that uses historical flight data to develop models of normal behavior, and then apply statistical methods to identify outliers under one or more indicators. Metron has used similar approaches for anomaly detection systems developed and delivered to operational customers in the land and maritime domains.

POTENTIAL NASA COMMERCIAL APPLICATIONS (Limit 1500 characters, approximately 150 words)
The long-term goal of this A3 Airspace Operations and Safety work is facilitating the development of autonomy in the future National Airspace System (NAS) through the modeling of how human behavior influences the details of flight path selection. The short-term goal is to improve the current NAS by identifying flights deemed "anomalous" by a suite of indicators designed to assess flight efficiency and safety. The transition path for NASA priorities begins with ATAC's flight repository, the source of the data for this project. ATAC's mission is to consolidate, to cleanse, and to otherwise add value to NAS data—the indicators we propose to develop for this project are designed to aid that mission. In preparation for a Phase II, we will work with ATAC to transition our short-term technology to an FAA NextGen program (e.g., Collaborative Air Traffic Management Technologies (CATMT)), and leverage these in-roads to begin transitioning our deeper human-behavior modeling effort.

POTENTIAL NON-NASA COMMERCIAL APPLICATIONS (Limit 1500 characters, approximately 150 words)
For Non-NASA commercial applications, we plan to use the proposed work to extend our technical base of kinematic modeling and anomaly detection (which is land- and sea-oriented) to include air operations. This will allow us to break into new areas within agencies such as NGA that are already using our technology for land and sea. Much of our technical base was developed as a kinematic component of Maritime Domain Awareness (MDA) for the Navy, where it is important to understand the behavior of commercial shipping. We would use the extension of this work into the air domain to develop a similar capability for the Air Force, providing capabilities for them to interact more safely and effectively within the context of civilian airspace.

TECHNOLOGY TAXONOMY MAPPING (NASA's technology taxonomy has been developed by the SBIR-STTR program to disseminate awareness of proposed and awarded R/R&D in the agency. It is a listing of over 100 technologies, sorted into broad categories, of interest to NASA.)
Air Transportation & Safety
Algorithms/Control Software & Systems (see also Autonomous Systems)
Analytical Methods
Autonomous Control (see also Control & Monitoring)
Data Fusion
Data Processing
Intelligence
Process Monitoring & Control
Software Tools (Analysis, Design)

Form Generated on 04-23-15 15:37