Gauss Hermite <italic>H</italic>_&#x221E; Filter for UAV Tracking Using LEO Satellites TDOA/FDOA Measurement&#x2014;Part I

• Main Authors: Abulasad Elgamoudi, Hamza Benzerrouk, G. Arul Elango, Rene Landry
• Format: Article
• Language: English
• Published: IEEE 2020-01-01
• Series: IEEE Access
• Subjects: Geolocation; TDOA; FDOA; <italic xmlns:ali="http://www.niso.org/schemas/ali/1.0/" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">H</italic>∞; GHKF; observability
• Online Access: https://ieeexplore.ieee.org/document/9234403/

The precision geolocation and target tracking problem has been addressed in this paper using High-Degree Non-linear Filtering based on hybrid Time Difference of Arrival (TDOA), Frequency Difference of Arrival (FDOA) measurements using Low Earth Orbit (LEO) satellite with slant range. In order to update the noise covariance and estimation process at each measurement, the Gauss Hermite H_&#x221E; Filter based on hybrid TDOA/FDOA geolocation measurements are proposed in this work. Numerous scenarios with the different rotation speed of Radio Frequency (RF) emitter has been considered. Multi LEO satellites have used to estimate and track the location of the unknown Unmanned Aerial Vehicle (UAV) under uncertainties of measurements. The uncertainties of measurements have been considered because the position and velocity of sensors are not fixed, which may affect the emitter location estimation measurements. The Cramer-Rao Lower Bound (CRLB) is used as a metric for measuring and analyzing the performance of the H_&#x221E;/GHKF 3^rd degree and H_&#x221E;/GHKF 5^th degree algorithm, as well as compare it with state-of-the-art algorithms. The simulation results of the proposed algorithm indicate that the significant improvement in performance for example, 10% based on TDOA, 40% for FDOA, and 50% on TDOA/FDOA have been achieved.