JOURNAL ARTICLE

GNSS Meta-Signal Tracking Using a Bicomplex Kalman Filter

Daniele BorioMelania Susi

Year: 2024 Journal:   NAVIGATION Journal of the Institute of Navigation Vol: 71 (4)Pages: navi.674-navi.674   Publisher: Wiley

Abstract

Global navigation satellite system (GNSS) signals from different frequencies can be effectively treated as a single entity, characterized by common delays and carrier phases, leading to so-called GNSS meta-signals. A convenient approach for deriving meta-signal acquisition and tracking algorithms has been recently introduced based on bicomplex numbers, which are a bidimensional extension of complex numbers. Bicomplex numbers allow one to represent two signals from different frequencies as a single quantity, providing a compact notation for algorithm development. In this work, an error-state Kalman filter (KF) is developed, and two signals from different frequencies are tracked simultaneously using the bicomplex number paradigm. A triple-loop architecture, in which loop filters are replaced by a single KF, is developed, implemented, and tested using real Galileo alternative binary offset carrier and BeiDou B1I/B1C meta-signals. This analysis clearly shows the advantages of KF tracking for processing GNSS meta-signals with components from different frequencies.

Keywords:
GNSS applications Kalman filter Tracking (education) SIGNAL (programming language) Extended Kalman filter Computer science Remote sensing Telecommunications Artificial intelligence Geography Global Positioning System

Metrics

2
Cited By
2.64
FWCI (Field Weighted Citation Impact)
30
Refs
0.88
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

GNSS positioning and interference
Physical Sciences →  Engineering →  Aerospace Engineering
Inertial Sensor and Navigation
Physical Sciences →  Engineering →  Aerospace Engineering
Target Tracking and Data Fusion in Sensor Networks
Physical Sciences →  Computer Science →  Artificial Intelligence

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