GNSS Measurement Performance in Vegetation Environments: Assessment and Analysis in Signal Processing Level

Di Hai, Chin Lok Tsang, Guohao Zhang, and Li-Ta Hsu

Peer Reviewed

Abstract:	Accurate GNSS positioning results are crucial in various civil applications, yet the accuracy of GNSS can be greatly degraded by surrounding environments including buildings and vegetation. While various studies have explored the influence of buildings on GNSS signals and developed various algorithms to enhance positioning accuracy in urban areas, the degradation of GNSS signals resulting from vegetation has been overlooked. This study aims to investigate and evaluate the performance of GNSS signals in vegetated environments at the signal processing level, using Intermediate-Frequency (IF) data to uncover the distinctive characteristics of signal performance under vegetation. The IF signal data will be initially processed using a software-defined receiver with an extended coherent integration of 20 milliseconds to suppress noise levels. Subsequently, the processed data will be analyzed using a maximum likelihood estimation-based method to examine the signal composition. Through experiments conducted in vegetated and non-vegetated environments, four unique characteristics related to different types of disturbances in GNSS signals under vegetated environments are identified. The unique features demonstrated in this study include signal strength attenuation, unique multipath patterns, the existence of multipath due to the internal structure of vegetation, and different multipath error distributions compared to urban environments.
Published in:	Proceedings of the 37th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2024) September 16 - 20, 2024 Hilton Baltimore Inner Harbor Baltimore, Maryland
Pages:	1939 - 1951
Cite this article:	Hai, Di, Tsang, Chin Lok, Zhang, Guohao, Hsu, Li-Ta, "GNSS Measurement Performance in Vegetation Environments: Assessment and Analysis in Signal Processing Level," Proceedings of the 37th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2024), Baltimore, Maryland, September 2024, pp. 1939-1951. https://doi.org/10.33012/2024.19880
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