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UAS Research, Development, and Design Projects
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). 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 Imageryby 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 DesignThe 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 AvoidThe 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 Development for Flight by Unmanned Aerial VehiclesScientific 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 SensingDuring 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 Observational Camera (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 EffectsLow 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 PayloadsThe 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
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John D. Odegard School of Aerospace Sciences - Center for Unmanned Aircraft Systems
