Séminaire Helena Calatrava (Northeastern University, Boston)

Quand

16 juillet 2024    
11h00 - 12h30

CRAN - FST - 4ème
Campus Sciences, Boulevard des Aiguillettes, Vandoeuvre-lès-Nancy, 54506

Type d’évènement

Speaker: Helena Calatrava (Northeastern University, Boston, USA)
Title: GNSS Signal Processing for Precise and Robust Positioning

Abstract:
In this talk, we will explore two methodologies designed to enhance the performance of Global Navigation Satellite Systems (GNSS): collaborative positioning techniques to improve positioning accuracy and robust signal processing to enhance resilience against jamming attacks. First, we will introduce the Massive User-Centric Single Difference (MUCSD) algorithm, which enhances GNSS accuracy through user collaboration. MUCSD leverages a network of receivers exchanging observables and noisy estimates of position and clock bias. Implemented as an iterative weighted least squares (WLS) estimator, MUCSD achieves a performance comparable to Differential GNSS (DGNSS) without the need for costly reference stations. Simulation results demonstrate that MUCSD outperforms DGNSS as the number of collaborative receivers increases, showcasing its scalability. Next, we will discuss the Robust Interference Mitigation (RIM) framework for snapshot architectures, addressing interferences such as continuous wave and chirp jamming signals. While studies on RIM typically assume the number of quantization bits allows for full signal representation, our study examines the impact of low quantization bits on baseline snapshot receiver performance in the presence of interference. Additionally, we will analyze the effect of quantization on the median absolute deviation (MAD) robust measure of statistical dispersion. By combining collaborative positioning techniques and robust interference mitigation, this talk will showcase advancements that improve GNSS precision and resilience.

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