Kassas and student win Best Student Paper at IEEE Vehicular Technology Conference

Posted: January 13, 2023
Zak Kassas and student standing next to each other

Electrical and Computer Engineering Professor Zak Kassas and student, Nadim Khairallah, won the overall Best Student Paper award at the 2022 Institute of Electrical and Electronics Engineers (IEEE) Vehicular Technology Conference (VTC). The paper was chosen from 614 papers accepted.

“An Interacting Multiple Model Estimator of LEO Satellite Clocks for Improved Positioning," addressed a critical problem facing the exploitation of unknown low Earth orbit (LEO) satellite signals for positioning, navigation, and timing (PNT).

"We are witnessing a space renaissance. Tens of thousands of broadband LEO satellites are expected to be launched by the end of this decade," said Kassas. "These planned megaconstellations of LEO satellites along with existing constellations will shower the Earth with a plethora of signals of opportunity that could be exploited for PNT in the inevitable event that GNSS signals become unavailable or untrustworthy.”

To use LEO satellite signals for PNT, the LEO satellite clock error must be known. Unlike global navigation satellite system (GNSS) satellites, LEO satellites generally do not openly transmit information about their clock error in their downlink signals. While the clock error states can be estimated, the stability of the oscillator is generally unknown. Knowledge of the oscillator’s stability is essential to calculate the covariance matrix of the process noise driving the clock error states.

The paper addressed this challenge by developing an interacting multiple-model (IMM) estimator to adaptively estimate the process noise covariance of LEO satellite clocks. Experimental results were presented showing a stationary ground receiver localizing itself with carrier phase measurements from a single Orbcomm LEO satellite. The developed IMM is shown to reduce the localization error and improve filter consistency over two fixed, mismatched extended Kalman filters (EKFs).

"I am proud of Nadim's hard work and ingenuity in tackling this problem. I am grateful for the Office of Naval Research (ONR), the National Science Foundation (NSF), and the U.S. Department of Transportation (USDOT) for supporting this research," Kassas said.  

Categories: ResearchAwards