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Full-Text Articles in Engineering
Deep Visual Gravity Vector Detection For Unmanned Aircraft Attitude Estimation, Gary J. Ellingson, David Wingate, Tim Mclain
Deep Visual Gravity Vector Detection For Unmanned Aircraft Attitude Estimation, Gary J. Ellingson, David Wingate, Tim Mclain
Faculty Publications
This paper demonstrates a feasible method for using a deep neural network as a sensor to estimate the attitude of a flying vehicle using only flight video. A dataset of still images and associated gravity vectors was collected and used to perform supervised learning. The network builds on a previously trained network and was trained to be able to approximate the attitude of the camera with an average error of about 8 degrees. Flight test video was recorded and processed with a relatively simple visual odometry method. The aircraft attitude is then estimated with the visual odometry as the state …
Minimum Required Detection Range For Detect And Avoid Of Unmanned Aircraft Systems, Jared Kevin Wikle, Tim Mclain, Randal W. Beard, Laith Rasmi Sahawneh
Minimum Required Detection Range For Detect And Avoid Of Unmanned Aircraft Systems, Jared Kevin Wikle, Tim Mclain, Randal W. Beard, Laith Rasmi Sahawneh
Faculty Publications
For unmanned aircraft systems to gain full access to the National Airspace System, they must have the capability to detect and avoid other aircraft. To safely avoid an- other aircraft, an unmanned aircraft must detect the intruder aircraft with ample time and distance to allow the ownship to track the intruder, perform risk assessment, plan an avoidance path, and execute the maneuver. This paper describes two analytical methods for finding the minimum detection range to ensure that these detection and avoidance steps can be carried out. The first method, time-based geometric velocity vectors, includes the bank-angle dynamics of the ownship; …
A Well Clear Recommendation For Small Uas In High-Density, Ads-B-Enabled Airspace, Timothy Mclain, Matthew O. Duffield
A Well Clear Recommendation For Small Uas In High-Density, Ads-B-Enabled Airspace, Timothy Mclain, Matthew O. Duffield
Faculty Publications
With the growing popularity of small unmanned aircraft systems (UAS), there is a significant need to enable small UAS to detect and avoid collisions with both manned and unmanned aircraft. The capabilities of ADS-B make it an attractive sensor for detect and avoid (DAA), but it is susceptible to frequency congestion. This paper quantitatively analyzes the frequency limitations of 978 MHz ADS-B. It then uses these limitations to make a recommendation for well clear in ADS-B-equipped airspace that has a high density of small UAS operations.