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Advanced GNSS Technologies: Measurement, Analysis, and Applications

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Earth Sciences".

Deadline for manuscript submissions: 20 February 2026 | Viewed by 561

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Guest Editor
School of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China
Interests: GNSS positioning; multi-source sensor fusion; intelligent structural health monitoring; mine and underground measurement; laser point cloud intelligent processing
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Global Navigation Satellite System (GNSS) technologies are pivotal to modern society due to their role in providing precise location and time synchronization. The term GNSS encompasses multiple satellite systems, such as GPS, GLONASS, Galileo, and BeiDou, which together offer global coverage and enhanced accuracy. These systems are fundamental to a variety of applications, including, but not limited to, navigation, geodesy, surveying, transportation, and environmental monitoring.

The core of GNSS technology relies on the measurement of signals transmitted by satellites and received by ground-based equipment. The time delay in these signals is used to calculate the distance between the satellite and receiver, thereby pinpointing the receiver's location. Advanced analysis techniques, such as Kalman filtering and smoothing algorithms, are employed to refine the measurements and improve the accuracy.

GNSS applications are vast, impacting fields such as navigation, location-based services, precise positioning, agriculture through precision farming, urban planning with traffic management, and scientific research in Earth sciences. The integration of GNSS into other technologies, such as inertial navigation systems, LiDAR, vision, and mobile communications, further extends its utility. As research and development continue, GNSS technologies are becoming more robust, with increased resilience to interference and jamming, ensuring their continued relevance in a rapidly evolving technological landscape.

Prof. Dr. Qiuzhao Zhang
Guest Editor

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Keywords

  • GNSS
  • hybrid positioning
  • co-operative positioning
  • integrity monitoring
  • reliability enhancement
  • multi-sensor integration

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Published Papers (2 papers)

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Research

19 pages, 8067 KiB  
Article
BDS-PPP-B2b-Based Smartphone Precise Positioning Model Enhanced by Mixed-Frequency Data and Hybrid Weight Function
by Zhouzheng Gao, Zhixiong Wu, Shiyu Liu and Cheng Yang
Appl. Sci. 2025, 15(13), 7169; https://doi.org/10.3390/app15137169 - 25 Jun 2025
Viewed by 143
Abstract
Compared to high-cost hardware-based Global Navigation Satellite System (GNSS) positioning techniques, smartphone-based precise positioning technology plays an important role in applications such as the Internet of Things (IoT). Since Google released the Nougat version of Android in 2016, this has provided a new [...] Read more.
Compared to high-cost hardware-based Global Navigation Satellite System (GNSS) positioning techniques, smartphone-based precise positioning technology plays an important role in applications such as the Internet of Things (IoT). Since Google released the Nougat version of Android in 2016, this has provided a new method for achieving high-accuracy positioning solutions with a smartphone. However, two factors are limiting smartphone-based high-accuracy applications, namely, real-time precise orbit/clock products without the internet and the quality-adaptive precise point positioning (PPP) model. To overcome these two factors, we introduce BDS PPP-B2b orbit/clock corrections and a hybrid weight function (based on C/N0 and satellite elevation) into smartphone real-time PPP. To validate the performance of such a method, two sets of field tests were arranged to collect the smartphone’s GNSS measurements and PPP-B2b orbit/clock corrections. The results illustrated that the hybrid weight function led to 5.13%, 18.00%, and 15.15% positioning improvements compared to the results of the C/N0-dependent model in the east, north, and vertical components, and it exhibited improvements of 71.10%, 72.53%, and 53.93% compared to the results of the satellite-elevation-angle-dependent model. Moreover, the mixed-frequency measurement PPP model could also provide positioning improvements of about 14.63%, 19.99%, and 9.21%. On average, the presented smartphone PPP model can bring about 76.64% and 59.84% positioning enhancements in the horizontal and vertical components. Full article
(This article belongs to the Special Issue Advanced GNSS Technologies: Measurement, Analysis, and Applications)
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24 pages, 4270 KiB  
Article
Differentiated GNSS Baseband Jamming Suppression Method Based on Classification Decision Information
by Zhongliang Deng, Zhichao Zhang, Xiangchuan Gao and Peijia Liu
Appl. Sci. 2025, 15(13), 7131; https://doi.org/10.3390/app15137131 - 25 Jun 2025
Viewed by 111
Abstract
In complex urban electromagnetic environments, wireless positioning signals are subject to various types of interference, including narrowband, chirp, and pulse jamming. Traditional generic suppression methods struggle to achieve global optimization tailored to specific interference mechanisms. This paper proposes a classification-driven differentiated jamming suppression [...] Read more.
In complex urban electromagnetic environments, wireless positioning signals are subject to various types of interference, including narrowband, chirp, and pulse jamming. Traditional generic suppression methods struggle to achieve global optimization tailored to specific interference mechanisms. This paper proposes a classification-driven differentiated jamming suppression (CDDJ) method, which adaptively selects the optimal mitigation strategy by pre-identifying interference types and integrating classification confidence levels. First, the theoretical bounds of the output carrier-to-noise ratio (C/N0out) under typical interference scenarios are derived, characterizing the performance distribution of anti-jamming efficiency (Γ). Then, a mapping relationship between interference categories and their corresponding suppression strategies is established, along with decision criteria for strategy switching based on signal quality evaluation metrics. Finally, an OpenMax-Lite rejection layer is designed to handle low-confidence inputs, identify unknown jamming using the Weibull distribution, and implement a broadband conservative suppression policy. Simulation results demonstrate that the proposed method exhibits significant advantages across different interference types. Under high JSR conditions, the signal recovery rate improves by over 10% and 8% compared to that of the WPT and KLT methods, respectively. In terms of SINR performance, the proposed approach outperforms the AFF, TDPB, and FDPB methods by 1.5 dB, 1.1 dB, and 5.3 dB, respectively, thereby enhancing the reliability of wireless positioning in complex environments. Full article
(This article belongs to the Special Issue Advanced GNSS Technologies: Measurement, Analysis, and Applications)
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