Feasibility Study of Flight Inspection Aided by UAS-Based Sensing and Calibration

PROJECT ID AND TITLE: Feasibility Study of Flight Inspection Aided by UAS-Based Sensing and Calibration

Project completed Sep. 2019

Collaborators:

PI: Dr. Yan Zhang, Associate Professor, School of Electrical and Computer Engineering, University of Oklahoma
Co-PI: Dr. John Dyer, Research Assistant Professor, University of Oklahoma
Students: Nepal Ramesh, Yih-Ru Huang
FAA Sponsor: Floyd Badsky, Flight Program Operations (AJW-3)
FAA Technical Monitor: Brad Snelling

Abstract:

The Intelligent Aerospace Radar Team at the University of Oklahoma will support the flight inspection operations of FAA AJW-3, through development and application of a novel approach to improve the existing solutions for signal strength (SS) measurement during flight inspection and calibration of the navigational aid signals from VHF to L bands. The approach combines electromagnetic simulations, software-defined radios, usage of unmanned aerial system (UAS) platforms and extension of free-space VSWR (voltage standing wave ratio, a measure of signal uncertainty) processing algorithms.

Expected Project Outcomes:

Aircraft and antenna modeling for FAA’s flight inspection systems.
Computational Electromagnetics (CEM) analysis of antenna patterns (for antennas mounted on FAA inspection A/C).
Proof-of-Concept Studies of the Software-Defined Radio (SDR) Option as probe receiver of signal strength.

Value of Research:

Multiple computational electromagnetic solving tools including MLFMM, MoM, FDTD and Ray Tracing are used together for accurate and efficient prediction of radiation patterns of antennas on large aircraft, with the environment and propagation effects taken into account;
Low-cost, flexibility and mobility based on open-source, software-reconfigurable RF transceivers and customized antenna designs;
Usage of small UAS as probe carrier platform for signal probes, which can achieve automatic SS measurements and precise location tracking based on improved GNSS truth sensor;
Multi-element probe antenna covering the required signal bandwidth while also having the capability for detecting RF interference;
Advanced signal processing to achieve requirement accuracies through the noise and interference control for improved measurement precision. Algorithms can also separate and isolate the impacts on SS measurements from different sources such as environment reflections/multipath, transceiver noise, and possible signal modulation from platform propellers.