Title: Algorithm for Geodetic Positioning Based on Angle-of-Arrival of Automatic Dependent Surveillance-Broadcasts
Author(s): Richard A. Gross, Nicholas A. Baine
Published in: Proceedings of IEEE/ION PLANS 2018
April 23 - 26, 2018
Hyatt Regency Hotel
Monterey, CA
Pages: 990 - 1001
Cite this article: Gross, Richard A., Baine, Nicholas A., "Algorithm for Geodetic Positioning Based on Angle-of-Arrival of Automatic Dependent Surveillance-Broadcasts," Proceedings of IEEE/ION PLANS 2018, Monterey, CA, April 2018, pp. 990-1001.
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Abstract: This paper develops a non-precision geolocation algorithm for airborne vehicles that can serve as a redundant navigation system for use during locally limited Global Navigation Satellite Systems (GNSS) availability, that can be used to validate on-board satellite navigation systems to detect local spoofing attempts, and that can be used to validate Automatic Dependent Surveillance – Broadcast (ADS-B) position reports. The algorithm utilizes the proliferation of ADS-B equipped aircraft as airborne navigation aids in a radio frequency angle-of-arrival (AOA) based geodetic positioning algorithm. The navigation algorithm is loosely based on Simultaneous Localization and Mapping (SLAM) in that it tracks ADS-B capable aircraft to refine their ADS-B reported position estimates while simultaneously determining the geodetic position and velocity of the host vehicle. Unlike SLAM, where the absolute location – latitude/longitude – of the landmarks is unknown and must be estimated as the vehicle encounters them, the absolute position of the airborne navigation aids is reasonably well-known and periodically reported in the ADS-B data set. Because the absolute position of the navigation aids is known, the resulting host vehicle position will also be an absolute, rather than a relative position. Secondarily, the continuous tracking of the airborne navigation aids allows reported ADS-B positions to be validated against the estimated navigation aid position; thereby, concurrently accomplishing ADS-B validation and host vehicle geolocation. It has been demonstrated through simulation that the algorithm is capable of generating valid position estimates and a reliable estimate of its accuracy across a variety of anticipated input conditions. With multiple GNSS quality navigation aids available, mean position errors well below 500 meters were observed. As the quality of the navigation aids decreased, so too did the accuracy of the algorithm. Utilizing navigation aids with an accuracy of 4 nautical miles (95% containment) resulted in mean position errors on the order of 1.25 nautical miles. These results demonstrate that the method is feasible, and even under worst case conditions, the accuracy of the position estimate generated by the algorithm was sufficient to allow an aircraft to navigate to its destination.