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Proceedings Paper

Physical-model-aided antenna pattern calibration for flight inspection
Author(s): Matthew Gilliam; Yan (Rockee) Zhang; John Dyer
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Paper Abstract

The calibration and inspection of various antennas related to navigation, aviation and flight operations has been a big challenge for agencies such as FAA and DoD. These antennas include both ground and airborne components. Antenna systems at ground infrastructure include navigational aide systems such as VOR/LOC, TACAN/DME, and Glide Slope, and include the ground-based surveillance radars. The antennas mounted on the aircraft include various aviation probe antennas and airborne radars. The flight inspection mission requires precise measurement of signal power at locations around any facility. Calibration of airborne radar antenna mounted on aircraft is also needed for precise radar functions. The difficulties, however, lie in the fact that the aircraft body and the environment have significant impacts on the signal measurement quality, which is usually difficult to characterize. This work focuses on how the airframe affects the typical aviation antenna measurements, and a possible way to “normalize” such impacts to gain the desired “effective” radiation patterns. We mainly reply on computational electromagnetic (CEM) tools to establish the physical scattering model of the aircraft with respect to different simplified antenna models, and then validate the radiation patterns through actual flight test data collections. Initial comparisons between the simulations and flight measurements reveal some interesting behaviors of radiation patterns on the aircraft installations, further issue of electromagnetic compatibility in the complex aircraft operations, and the potential of using unmanned aerial systems (UAS) to automate the measurement procedure in the future.

Paper Details

Date Published: 3 May 2019
PDF: 12 pages
Proc. SPIE 11003, Radar Sensor Technology XXIII, 1100309 (3 May 2019); doi: 10.1117/12.2518434
Show Author Affiliations
Matthew Gilliam, The Univ. of Oklahoma (United States)
Yan (Rockee) Zhang, The Univ. of Oklahoma (United States)
John Dyer, The Univ. of Oklahoma (United States)

Published in SPIE Proceedings Vol. 11003:
Radar Sensor Technology XXIII
Kenneth I. Ranney; Armin Doerry, Editor(s)

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