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Advances in GNSS Signal Processing and Navigation

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A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Navigation and Positioning".

Deadline for manuscript submissions: 31 May 2025 | Viewed by 7183

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Special Issue Editors

Prof. Dr. Ming Huang

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Guest Editor

School of Information Science and Engineering, Yunnan University, Kunming 650500, China
Interests: GNSS spoofing and jamming detection; radio monitoring; deep learning

Dr. Jingjing Yang

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Guest Editor

School of Information Science and Engineering, Yunnan University, Kunming 650091, China
Interests: wireless communication; signal processing; radio monitoring; deep learning

Dr. Zhe Xiao

E-Mail Website
Guest Editor

Institute of High Performance Computing, 1 Fusionopolis Way, #16-16 Connexis, Singapore 138632, Singapore
Interests: signal processing; deep learning; generative artificial intelligence

Special Issue Information

Dear Colleagues,

As a fundamental spatiotemporal information service infrastructure, the Global Navigation Satellite System (GNSS) provides precise Positioning, Navigation, and Timing (PNT) services and enables a wide range of innovative applications. However, due to the use of MEO/HEO satellites, the quality of received GNSS signals is highly susceptible to environmental factors, including non-line-of-sight (NLOS) reception, spoofing attacks, and jamming. Globally, more than 10,000 radio frequency interference (RFI) events were detected in 2021 through the in-flight monitoring of aircraft GNSS receivers, reported by the International Telecommunication Union (ITU). With GNSS-denied environments becoming increasingly widespread, there is an urgent need to develop new GNSS architectures, signal processing algorithms, and techniques to improve the PNT services. This Special Issue will highlight the latest technological developments in GNSS signal processing, LEO opportunistic Doppler-aided GNSS positioning, GNSS alternatives, and novel applications. We invite researchers and investigators to contribute original research or review articles to this Special Issue. The scope of this Special Issue will be broadly interpreted to include, but not be limited to, the following topics:

GNSS Signal Processing for Positioning, Navigation, and Timing;
Cybersecurity Framework of GNSS for PNT Services;
Opportunistic PNT with Signals from LEO Communication Satellites and Signal Processing;
Opportunistic PNT with Signals from Terrestrial Radio Frequency Sources and Signal Processing;
Electromagnetic Space Radio Safety and GNSS Signals Monitoring Framework;
GNSS Signal Processing based on Machine Learning, Deep Learning, and Generative Artificial Intelligence;
Artificial Intelligence Applications for GNSS;
GNSS Spoofing Detection and Signals Processing;
GNSS Jamming Detection and Signals Processing;
GNSS Signals Monitoring and Signals Processing;
Passive Radar Signal Processing based on GNSS Signals;
GPS Service for Geodynamics;
GNSS Real-Time Kinematic (RTK) Techniques and Signals Processing;
Environment Classification based on GNSS Signal;
Soil Moisture Retrieval from GNSS Observations.

Prof. Dr. Ming Huang
Dr. Jingjing Yang
Dr. Zhe Xiao
Guest Editors

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Keywords

GNSS signal processing
LEO opportunistic Doppler-aided GNSS positioning
GNSS alternatives

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Published Papers (7 papers)

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Research

14 pages, 2045 KiB

Open AccessArticle

Time to First Fix Robustness of Global Navigation Satellite Systems: Comparison Study

by Carlos Hernando-Ramiro, Óscar Gamallo-Palomares, Javier Junquera-Sánchez and José Antonio Gómez-Sánchez

Sensors 2025, 25(5), 1599; https://doi.org/10.3390/s25051599 - 5 Mar 2025

Viewed by 630

Abstract

The time to first fix (TTFF) measures the time elapsed by a global navigation satellite system (GNSS) receiver from switch-on to provision of a navigation solution. This parameter is crucial for applications where a position, within an acceptable error, is needed as soon as possible after turning the device on. The quality of the TTFF depends mainly on the receiver, the environment, and the GNSS satellites employed. Although all four available GNSSs (BeiDou, Galileo, GLONASS, and GPS) are complementary, their constellations and signals differ, providing different TTFF performances. This becomes even more relevant in hostile environments, where the TTFF degrades from nominal results. In this work, the robustness of the signals of the four GNSSs against different levels of harshness and its influence on the TTFF performance are evaluated in a comparative way. For this purpose, a typical scenario for mass-market GNSS applications, involving cold-start conditions, single-frequency signals, and a low-cost receiver, is considered. The results indicate that GPS provides the most robust TTFF, followed by GLONASS (although at the expense of positioning accuracy), BeiDou, and Galileo, in that order. Full article

(This article belongs to the Special Issue Advances in GNSS Signal Processing and Navigation)

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11 pages, 3494 KiB

Open AccessCommunication

Analysis of GNSS-RTK Monitoring Background Noise Characteristics Based on Stability Tests

by Wencong Qi, Feilong Li, Lina Yu, Lilong Fan and Kai Zhang

Sensors 2025, 25(2), 379; https://doi.org/10.3390/s25020379 - 10 Jan 2025

Viewed by 801

Abstract

GNSS-RTK offers numerous advantages and broad prospects in structural dynamic monitoring in civil engineering. However, in practical applications, GNSS-RTK accuracy is susceptible to the monitoring environments, causing actual monitoring accuracy to fall below its calibrated accuracy. This study investigates the monitoring accuracy and spectral characteristics of GNSS-RTK based on stability tests under different environments related to reflection and obstruction conditions (i.e., concrete, grass, an obstructed balcony, and a water area). The findings indicate that in open environments of grass, concrete, and water, the standard deviation (STD) of GNSS-RTK monitored displacement is below 8 mm, its accuracy meeting the specifications of structural health monitoring. In the obstructed balcony environments, GNSS-RTK signals exhibit amplitude jumps, resulting in lower accuracy; however, during non-jump intervals, the STD of monitored displacement is below 10 mm, satisfying the structural health monitoring accuracy requirements. Moreover, the amplitudes of GNSS-RTK displacements in the concrete, grass, and water areas are basically consistent with the calibration accuracy of ±10 mm in the horizontal direction and ±20 mm in the elevation direction, while the amplitudes of GNSS-RTK displacements in the obstructed balcony condition are far greater than the calibration accuracy. The spectral analysis of GNSS-RTK signals reveals that multipath errors in concrete, grass, and obstructed balcony environments are primarily concentrated in the low-frequency range within 0.04 Hz, while the internal white noise of the instrument is widely and evenly distributed across the whole frequency domain. Based on these findings, adaptive methods, such as filter methods and multipath error correction techniques, are proposed for the de-noising of GNSS-RTK background noise. Full article

(This article belongs to the Special Issue Advances in GNSS Signal Processing and Navigation)

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15 pages, 4029 KiB

Open AccessArticle

GPS Phase Integer Ambiguity Resolution Based on Eliminating Coordinate Parameters and Ant Colony Algorithm

by Ning Liu, Shuangcheng Zhang, Xiaoli Wu and Yu Shen

Sensors 2025, 25(2), 321; https://doi.org/10.3390/s25020321 - 8 Jan 2025

Viewed by 764

Abstract

Correctly fixing the integer ambiguity of GNSS is the key to realizing the application of GNSS high-precision positioning. When solving the float solution of ambiguity based on the double-difference model epoch by epoch, the common method for resolving the integer ambiguity needs to solve the coordinate parameter information, due to the influence of limited GNSS phase data observations. This type of method will lead to an increase in the ill-posedness of the double-difference solution equation, so that the fixed success rate of the integer ambiguity is not high. Therefore, a new integer ambiguity resolution method based on eliminating coordinate parameters and ant colony algorithm is proposed in this paper. The method eliminates the coordinate parameters in the observation equation using QR decomposition transformation, and only estimates the ambiguity parameters using the Kalman filter. On the basis that the Kalman filter will obtain the float solution of ambiguity, the decorrelation processing is carried out based on continuous Cholesky decomposition, and the optimal solution of integer ambiguity is searched using the ant colony algorithm. Two sets of static and dynamic GPS experimental data are used to verify the method and compared with conventional least squares and LAMBDA methods. The results show that the new method has good decorrelation effect, which can correctly and effectively realize the integer ambiguity resolution. Full article

(This article belongs to the Special Issue Advances in GNSS Signal Processing and Navigation)

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16 pages, 9642 KiB

Open AccessArticle

Towards an Accurate Real-Time Digital Elevation Model Using Various GNSS Techniques

by Mohamed Abdelazeem, Amgad Abazeed, Hussain A. Kamal and Mudathir O. A. Mohamed

Sensors 2024, 24(24), 8147; https://doi.org/10.3390/s24248147 - 20 Dec 2024

Cited by 1 | Viewed by 999

Abstract

The objective of our research is to produce a digital elevation model (DEM) in a real-time domain. For this purpose, GNSS measurements are obtained from a kinematic trajectory in a clear location in New Aswan City, Egypt. Different real-time processing solutions are employed, including real-time precise point positioning (RT-PPP) and real-time kinematics (RTK); additionally, the widely used post-processed precise point positioning (PPP) processing scenario is used. Thereafter, the acquired positioning estimates are compared with the traditional kinematic differential GNSS solution counterparts. To achieve the RT-PPP mode, the instantaneous products from the Centre National d’Etudes Spatiales (CNES) are utilized. Our proposed models are validated for both kinematic positioning and DEM accuracies. For kinematic positioning accuracy validation, the findings indicate that the three-dimensional position is about 0.480 m, 0.101 m, and 0.628 for RT-PPP, RTK, and PPP solutions, respectively. Furthermore, the DEM accuracy investigation shows that the produced DEMs have accuracies within 0.249 m, 0.005 m, and 0.264 m for RT-PPP, RTK, and PPP solutions, respectively. Full article

(This article belongs to the Special Issue Advances in GNSS Signal Processing and Navigation)

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27 pages, 36855 KiB

Open AccessArticle

Evaluation and Anomaly Detection Methods for Broadcast Ephemeris Time Series in the BeiDou Navigation Satellite System

by Jiawei Cai, Jianwen Li, Shengda Xie and Hao Jin

Sensors 2024, 24(24), 8003; https://doi.org/10.3390/s24248003 - 14 Dec 2024

Viewed by 1103

Abstract

Broadcast ephemeris data are essential for the precision and reliability of the BeiDou Navigation Satellite System (BDS) but are highly susceptible to anomalies caused by various interference factors, such as ionospheric and tropospheric effects, solar radiation pressure, and satellite clock biases. Traditional threshold-based methods and manual review processes are often insufficient for detecting these complex anomalies, especially considering the distinct characteristics of different satellite types. To address these limitations, this study proposes an automated anomaly detection method using the IF-TEA-LSTM model. By transforming broadcast ephemeris data into multivariate time series and integrating anomaly score sequences, the model enhances detection robustness through data integrity assessments and stationarity tests. Evaluation results show that the IF-TEA-LSTM model reduces the RMSE by up to 20.80% for orbital parameters and improves clock deviation prediction accuracy for MEO satellites by 68.37% in short-term forecasts, outperforming baseline models. This method significantly enhances anomaly detection accuracy across GEO, IGSO, and MEO satellite orbits, demonstrating its superiority in long-term data processing and its capacity to improve the reliability of satellite operations within the BDS. Full article

(This article belongs to the Special Issue Advances in GNSS Signal Processing and Navigation)

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15 pages, 3438 KiB

Open AccessCommunication

Galileo and BeiDou AltBOC Signals and Their Perspectives for Ionospheric TEC Studies

by Chuanfu Chen, Ilya Pavlov, Artem Padokhin, Yury Yasyukevich, Vladislav Demyanov, Ekaterina Danilchuk and Artem Vesnin

Sensors 2024, 24(19), 6472; https://doi.org/10.3390/s24196472 - 8 Oct 2024

Viewed by 1395

Abstract

For decades, GNSS code measurements were much noisier than phase ones, limiting their applicability to ionospheric total electron content (TEC) studies. Ultra-wideband AltBOC signals changed the situation. This study revisits the Galileo E5 and BeiDou B2 AltBOC signals and their potential applications in TEC estimation. We found that TEC noises are comparable for the single-frequency AltBOC phase-code combination and those of the dual-frequency legacy BPSK/QPSK phase combination, while single-frequency BPSK/QPSK TEC noises are much higher. A two-week high-rate measurement campaign at the ACRG receiver revealed a mean 100 sec TEC RMS (used as the noise proxy) of 0.26 TECU, 0.15 TECU, and 0.09 TECU for the BeiDou B2(a+b) AltBOC signal and satellite elevations 0–30°, 30–60°, and 60–90°, correspondingly, and 0.22 TECU, 0.14 TECU, and 0.09 TECU for the legacy B1/B3 dual-frequency phase combination. The Galileo E5(a+b) AltBOC signal corresponding values were 0.25 TECU, 0.14 TECU, and 0.09 TECU; for the legacy signals’ phase combination, the values were 0.19 TECU, 0.13 TECU, and 0.08 TECU. The AltBOC (for both BeiDou and Galileo) SNR exceeds those of BPSK/QPSK by 7.5 dB-Hz in undisturbed conditions. Radio frequency interference (the 28 August 2022 and 9 May 2024 Solar Radio Burst events in our study) decreased the AltBOC SNR 5 dB-Hz more against QPSK SNR, but, due to the higher initial SNR, the threshold for the loss of the lock was never broken. Today, we have enough BeiDou and Galileo satellites that transmit AltBOC signals for a reliable single-frequency vTEC estimation. This study provides new insights and evidence for using Galileo and BeiDou AltBOC signals in high-precision ionospheric monitoring. Full article

(This article belongs to the Special Issue Advances in GNSS Signal Processing and Navigation)

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17 pages, 6457 KiB

Open AccessEditor’s ChoiceArticle

A Cumulant-Based Method for Acquiring GNSS Signals

by He-Sheng Wang, Hou-Yu Wang and Dah-Jing Jwo

Sensors 2024, 24(19), 6234; https://doi.org/10.3390/s24196234 - 26 Sep 2024

Cited by 3 | Viewed by 1039

Abstract

Global Navigation Satellite Systems (GNSS) provide positioning, velocity, and time services for civilian applications. A critical step in the positioning process is the acquisition of visible satellites in the sky. Modern GNSS systems, such as Galileo—developed and maintained by the European Union—utilize a new modulation technique known as Binary Offset Carrier (BOC). However, BOC signals introduce multiple side-peaks in their autocorrelation function, which can lead to significant errors during the acquisition process. In this paper, we propose a novel acquisition method based on higher-order cumulants that effectively eliminates these side-peaks. This method is capable of simultaneously acquiring both conventional ranging signals, such as GPS C/A code, and BOC-modulated signals. The effectiveness of the proposed method is demonstrated through the acquisition of simulated signals, with a comparison to traditional methods. Additionally, we apply the proposed method to real satellite signals to further validate its performance. Our results show that the proposed method successfully suppresses side-peaks, improves acquisition accuracy in weak signal environments, and demonstrates potential for indoor GNSS applications. The study concludes that while the method may increase computational load, its performance in challenging conditions makes it a promising approach for future GNSS receiver designs. Full article

(This article belongs to the Special Issue Advances in GNSS Signal Processing and Navigation)

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