Kalman Filter-Based Navigation for 5G MultiLayer PNT Integrating Terrestrial and LEO/HAPS Non-Terrestrial Networks

Gabriele Ligorio, Francis Soualle, José A. del Peral-Rosado, Saggad Al Faris, Ottavio Picchi, Sophie Damy, and Francesco Menzione

Abstract:	The emergence of 5G technology has been pivotal in enabling communication and navigation services across various frequency bands. Recent studies have shown the potential of utilizing 5G signals for positioning within 5G Terrestrial Networks (TN), where 3GPP specifications include a Positioning Reference Signal (PRS) in the Orthogonal Frequency-Division Multiplexing (OFDM) frame. These methods provide alternative Positioning, Navigation, and Timing (PNT) solutions by exploiting frequency diversity, such as the S-band. A notable application of 5G-only positioning is its ability to enhance navigation resilience against strong interference or jamming in the RNSS band, benefiting a wide range of handheld users in urban environments. However, the accuracy of a 5G-only PNT solution is limited by the restricted geometric diversity of terrestrial base stations (BSs) and the Non-Line-of-Sight (N-LOS) conditions in urban settings, leading to increased positioning errors for end-users, especially in the vertical direction. The development of Non-Terrestrial Networks (NTN) promises a significant shift by extending 3GPP specifications to include Low Earth Orbit (LEO) satellites and/or High-Altitude Platform Stations (HAPSs). LEO satellites, in particular, offer unparalleled geometric diversity and dynamic performance, potentially outperforming TN solutions for PNT services. Yet, initial satellite communication missions might not provide enough satellites to meet standalone and instantaneous positioning demands. These early NTN deployments should leverage their interoperability with existing 5G ground infrastructures and HAPS to bridge this gap. A multi-layer 5G infrastructure is anticipated, where TN and NTN components work together to overcome poor geometry and limited LOS. This paper explores an effective positioning engine that integrates data from various transmission nodes, including BSs, LEO satellites, and HAPSs. A multi-epoch sequential approach is favored over a single-epoch least-squares method due to its robustness in scenarios with limited LOS visibility and the asynchronous nature of PRS transmission. The proposed work evaluates the performance of different Kalman Filter implementations in handling non-linear, asynchronous, and sparse measurements, with a focus on mitigating non-linearities from nearby transmission sources and managing users dynamic in urban environments. The assessment includes a sensitivity analysis of expected navigation performance, considering different configurations of the PRS signal and the availability or lack of the different network node categories. The study aims to contribute to the novel multi-layer 5G framework, emphasizing the potential to provide complementary PNT services even when PRS-based measurements are sporadic and asynchronous, compared to continuous GNSS and pseudolite signals.
Published in:	Proceedings of the 38th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2025) September 8 - 12, 2025 Hilton Baltimore Inner Harbor Baltimore, Maryland
Pages:	2763 - 2794
Cite this article:	Ligorio, Gabriele, Soualle, Francis, del Peral-Rosado, José A., Faris, Saggad Al, Picchi, Ottavio, Damy, Sophie, Menzione, Francesco, "Kalman Filter-Based Navigation for 5G MultiLayer PNT Integrating Terrestrial and LEO/HAPS Non-Terrestrial Networks," Proceedings of the 38th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2025), Baltimore, Maryland, September 2025, pp. 2763-2794. https://doi.org/10.33012/2025.20457
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