Civil UAS Operating Environment Without TFRs
The University of North Dakota, in cooperation with the Federal Aviation Administration , is identifying airspace within the state of North Dakota where organizations interested in developing UASs can test/operate their systems without the need for an on-board sense and avoid system. Taking advantage of a relatively low population density, UND and the state of North Dakota are working to provide more than 13,000 square miles of airspace suitable for all manner of UAS operations without the need for implementation of temporary flight restrictions (TFRs).
The JDO School of Aerospace Sciences, with funding from the United States Air Force UAV Battle Lab, is developing a ground-based radar system capable of detecting low observable aircraft such as sailplanes and hot-air balloons while developing the software to optimally display the information to operators of UASs.Where previously available ground-based radar systems have not been sufficient for the Federal Aviation Administration to approve their use for sense and avoid mitigation, this system will employ new technology that will enable UAS operators to see potential conflicts before they become a problem and safely maneuver their craft away from non-cooperative aircraft. Sophisticated algorithms are being developed to determine optimum scan patterns, rates and data assimilation to provide the most comprehensive "picture" of the operating environment.
Initial funding of the program will allow UND to develop a comprehensive system that incorporates all available data into the big picture. Ultimately, UND hopes to provide an interim mitigation strategy to allow UAS research and development outside restricted airspace thus aiding the Federal Aviation Administration in its efforts to develop appropriate regulations relating to UAS operations and certification.
For further information, contact Ben Trapnell
A University-Designed UAV Imaging Payload From the Ground Up
By Richard R. Schultz, Ph.D and William
H. Semke, Ph.D from the School of Engineering & Mines
Real-Time Super-Resolution Automatic Target Recognition of UAV-Based Reconnaissance and Surveillance Imagery
by Richard R. Schultz, Ph.D
This DEPSCoR award to the University of North Dakota will investigate feature-domain super- resolution image reconstruction with model-based constraints as a robust and real-time automatic target recognition algorithm for reconnaissance and surveillance imagery captured by airborne sensors flown by Unmanned Aerial Vehicles. Pixel-domain super-resolution is capable of extracting additional visual details from electro-optical (EO) and infrared (IR) video feeds that are not observable in any one frame through the integration of several frames registered with respect to a target-of-interest. However, super-resolution algorithms that rely on pixel-domain constraints are generally unsuitable for ATR because they are severely limited in magnification power, highly computational, and extremely sensitive to clutter, occlusions, noise, and registration errors. To overcome these limitations, model-based constraints will be generated by projecting CAD models and digital images of known military targets under surveillance, such as aircraft, armored personnel carriers, and combat vehicles, into a much lower-dimensional “target-space” using principal components analysis. By utilizing these “eigentargets,” super-resolution carried out in this low-dimensional feature-domain will be capable of quickly detecting and identifying a target that appears in only a small fraction of pixels within several video frames, as well as magnifying the visual data by much greater than 10x.
Regulation Study on Commercial UAS Vehicle Design
The Federal Aviation Administration (FAA)established this agreement with the Center of Excellence for General Aviation Research (CGAR) to organize, conduct research, and report the results and recommendations for a set of regulatory guidelines to be used with UAS (Unmanned Aircraft System) vehicle design and certification to allow for the safe and efficient operation of UAS in the NAS (National Airspace System).
Detect Sense and Avoid
The Federal Aviation Administration (FAA) has established an agreement with the Centers of Excellence for General Aviation Research (CGAR) to organize, conduct research and report the results and recommendations regarding the concept of Detect Sense and Avoid relating to UAS operations.
Environmental Payload and Sensor Developmentfor Flight by Unmanned Aerial Vehicles
Scientific payload development for environmental remote sensing applications and the design of an in-air collision avoidance sensor, to be flown by an experimental UAV developed by Lockheed Martin Corporation and provided to the Odegard School of Aerospace Sciences. (download )
Unmanned Aerial Vehicle Platform for Scientific Remote Sensing
During the summer of 2004, undergraduate engineering students and K- 12 science teachers built a quarter-scale, radio-controlled airplane kit capable of flying payloads in excess of 4-kg. (download )
Airborne Environmental Research ObservationalCamera (AEROCam)
Multispectral digital camera designed for flight on UND Aviation fleet aircraft, to be used for precision farming and ranching operations and high-resolution mapping. (download )
Development of Unmanned Aerial Vehicle Instrumentation with Fault Tolerant Electronics to Minimize High Altitude Radiation Effects
Low Earth orbit (LEO) satellites are subjected to severe radiation effects beyond the Earth’s atmosphere. Satellite engineers have learned to design radiation-hardened and fault tolerant electronics to minimize the problems faced by communication, navigation, and control systems. High altitude aircraft such as Unmanned Aerial Vehicles also experience electronic malfunctions due to radiation effects, particularly over polar flight paths. This research activity will extend fault tolerant electronic design techniques from the satellite industry to UAVs and their payloads.
Cold Weather Testing of Unmanned Aerial Vehicle Platforms and Payloads
The Northern Border of the United States provides a perfect test-bed for evaluating both Unmanned Aerial Vehicle platforms (i.e., aircraft) and payloads (e.g., military intelligence, surveillance, and communication sensors and civilian sensors for environmental remote sensing and commercial use) under cold weather stress conditions. The U.S. Border Patrol, the Department of Defense, and companies such as FedEx that currently ship cargo using manned aircraft will benefit from this research activity.
Human Factors Projects
- Predictors of UAS Pilot Training Success
- The Impact of Circadian Variations and Nutritional Intake on
- Decision Making in UAS operations
- Executive Function and Weather-Related Risk
- Detection of Weather-Related Thread Words Presented at Different Orientations
- Texting Dependence, Information Processing, and Psychological Health