NASA SBIR 2019-I Solicitation

Proposal Summary


PROPOSAL NUMBER:
 19-1- A3.03-2960
SUBTOPIC TITLE:
 Future Aviation Systems Safety
PROPOSAL TITLE:
 Data Fusion for Anomaly and Degradation Detection
SMALL BUSINESS CONCERN (Firm Name, Mail Address, City/State/Zip, Phone)
CAL Analytics
4031 Colonel Glenn Highway, Suite 300
Beavercreek, OH 43214- 2700
(937) 458-7777

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

Name:
Chris Crowder
E-mail:
c.crowder@calanalytics.com
Address:
4031 Colonel Glenn Hwy, Suite 300 Beavercreek, OH 43214 - 2700
Phone:
(315) 935-7716

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

Name:
Ryan Pleskach
E-mail:
ryan.pleskach@calanalytics.com
Address:
235 Harrison St, Mail Drop #5 Syracuse, NY 13202 - 3023
Phone:
(315) 216-5310
Estimated Technology Readiness Level (TRL) :
Begin: 1
End: 3
Technical Abstract (Limit 2000 characters, approximately 200 words)

Sources of sensor error leave a UTM (UAS Traffic Management) system vulnerable. The impact of anomalous sensor behavior can be devastating to a UTM system. Degraded sensor accuracy can lead to broken tracks or split tracks within a UTM system. Degraded sensor sensitivity may result in a Mid-Air Collision with an aircraft not detected by UTM sensors. It may also result in more Loss of Well-Clear violations and more frequent Near Mid-Air Collisions.  

This proposal recommends research and development in the area of monitoring a diverse set of UTM sensor outputs for detection and identification of anomalous sensor behavior as a technique to enable In-Time System-wide Safety Assurance (ISSA). In addition, research will be performed to develop an in-time methodology for translating out-of-spec sensor data to overall UTM system safety.  

CAL Analytics has teamed with Hidden Level to accomplish the following Phase 1 research tasks: 

  • Perform market study of UTM Sensors 

  • Perform study to determine minimum required sensor data elements to enable ISSA 

  • Develop a framework for comparing sensor outputs 

  • Perform study to assess separability of anomalous sensor behavior 

  • Develop requirements and performance metrics for guiding Phase II algorithm development 

  • Perform study exploring methods to assess system safety given degraded sensor performance 

  • Document results of studies in final report with recommendations for Phase II. 

The results of this research will form the basis of a UTM ISSA technique that will: 

  • Enable detection and reporting of anomalous sensor behavior through data mining  

  • Identify impacts to UTM system safety using anomalous sensor behavior to assess the impact to overall UTM system safety. 

Potential NASA Applications (Limit 1500 characters, approximately 150 words)

Monitoring anomalous sensor performance within a UTM ecosystem will help NASA research as UTM is transitioned from a research project to productization and commercialization. As NASA shifts gears to UAM, a mechanism to identify, report, and assess the impact of anomalous sensor behavior must exist. This research will also assist with standards development through RTCA and ASTM, by providing insight into standardizing interfaces and reactions to common off-nominal scenarios. 

Potential Non-NASA Applications (Limit 1500 characters, approximately 150 words)

The Non-NASA applications for this project include incorporating the anomalous sensor behavior detection and safety algorithms into a Software as a Service platform that monitors the health and integrity of a UTM ecosystem. This software will automate contingency management to improve UTM system fault tolerance, and ensure safety is maintained, and help automate failure root cause analysis. 

Duration: 6

Form Generated on 06/16/2019 23:22:19