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The performance of Ground-Based Augmentation System (GBAS) is selected for the aircraft landing phase which relies on the accurate characterization of error models. It helps optimize the stochastic model of the Global Navigation Satellite System (GNSS) and shortens the positioning convergence time. The existing techniques contain numerous position errors that affect the ionospheric gradients' performance. To overcome this issue, this paper proposed an error correction technique named Grid Ionospheric Vertical Error (GIVE) with adaptive clipping technique in GBAS. Initially, the input signal is passed to the transmitter in which the GIVE is utilized to reduce the ionospheric error. Then the transmitted signals are given to a channel that contains some noise. The signals are passed to the receiver and the adaptive clipping technique is utilized to reduce the receiver error then the output signal is produced. The error rate is automatically reduced when increasing the signal-to-noise ratio (SNR). The performance of GIVE with adaptive clipping is estimated through detection time and standard deviation with ionospheric gradient change rate of 0.01m/s and 0.02m/s through the elevation of 10-70 and minimum gradient change rate. The proposed GIVE with adaptive clipping achieved better detection rate (s) of 20s and 26s for the elevation of 20 with the change rate of 0.01m/s and 0.02m/s. The proposed model achieves better results when compared to existing methods like One-Class Support Vector Machine (OCSVM). [ABSTRACT FROM AUTHOR]

Earth's surface velocities are routinely extracted from Global Navigation Satellite System (GNSS) position time series. In addition to velocity estimates, acceleration may be a crucial parameter for modeling non-linear motion. Typically, a statistical hypothesis test is employed to evaluate the significance of the involved parameters and guide the selection of the appropriate model. In this contribution, we formulate a statistical test procedure from the generalized likelihood ratio test to analyze the significance of the acceleration in the model. The proposed procedure is compared with results obtained using the Akaike Information Criterion and Bayesian Information Criterion. Additionally, Minimal Detectable Horizontal Acceleration is provided as an indicator of the sensitivity of the acceleration detection. The GNSS time series of position estimates from the Nevada Geodetic Laboratory were used for this study. The experiments demonstrated a good agreement between the statistical test proposed and the information criteria approach. Therefore, the proposed statistical test may be another criterion to help the user in the important task of model selection. [ABSTRACT FROM AUTHOR]

In this paper, expressions for high-precision simulation of multi-GNSS observations received in low Earth orbit are given. Based on this observation model, the real spacecraft orbit was refined. Based on real data from the GRACE space project, the results were compared with simulated measurements from foreign software. The average deviation in determining the spacecraft location was 18 mm, which confirms the correctness of the described observation model. [ABSTRACT FROM AUTHOR]

Slow Slip Events (SSEs) are like long-duration slow earthquakes during which stress is gradually released over several days to months, and a comprehensive catalog of SSEs is essential for a better understanding of the earthquake cycle. However, SSEs usually only produce mm to cm surface deformations, making them a challenge to identify from raw Global Navigation Satellite System (GNSS) time series, which are often obscured by low-frequency background noise. We devise an approach that first employs variational Bayesian Independent Component Analysis to improve the signal-to-noise ratio of GNSS time series and then utilizes deep learning combining bidirectional Long Short-Term Memory and two different attention mechanisms to identify SSEs. We apply this new method to the GNSS three-component time series at 240 stations along the Cascadia subduction zone from 2012 to 2022. A total of 56 SSEs are detected, 18 more than the number in the existing SSEs catalogs during the same period. The starting time, duration, spatial and propagation pattern of the 56 SSEs are consistent with the tremor catalog, which helps to gain new insights into the slip behavior in the Cascadia subduction zone. In general, our work provides an effective framework for extracting subtle signals hidden in GNSS time series. [ABSTRACT FROM AUTHOR]

The Copernicus Precise Orbit Determination (CPOD) Service is in charge of computing the precise orbits and auxiliary data files of the Copernicus Sentinel-1, −2, −3 and −6 missions, using the GPS&Galileo observations obtained on-board. The orbit products and auxiliary data files are provided to the corresponding Payload Data Ground Segments (PDGS) and Payload Data Acquisition and Processing (PDAP) components and to external users through the Copernicus Data Space Ecosystem (CDSE). The CPOD Service is supported by the CPOD Quality Working Group (QWG), a group of leading experts on GNSS (Global Navigation Satellite System) and POD, which provides independent orbit solutions and techniques to support the quality control (QC) and the validation of the operational products. The CPOD Service was initially developed in 2013, starting its operational phase in April 2014 after the successful launch of Sentinel-1A. The CPOD Service has accumulated almost 10 years of experience, including its initial development, operations, and periodic evolutions, to the point that currently it is a well-recognized POD Service. This paper shows in detail the architecture of the CPOD Service, its performance and its evolution over the years, and its future outlook. [ABSTRACT FROM AUTHOR]

The open access to raw Global Navigation Satellite System (GNSS) measurements from Android smartphones brings new possibilities to high-accuracy positioning with precise point positioning (PPP) technique. However, decimeter or even centimeter level positioning accuracy is still challengeable mainly due to the low completeness of dual-frequency observations and specific observation errors from a smartphone. Huawei P40 released in 2020 is the first module that can track multi-GNSS multi-frequency signals. Based on GNSS observations from P40 and a co-located geodetic-grade receiver, a method is proposed to extract and model the P40 code-carrier inconsistency errors. The P40 observation inconsistency presents a linear drift pattern with respect to time at each frequency and can even reach hundreds of meters. A correction model is then established which reduces the code-carrier differences to a level of few meters. Regarding to the P40 code-carrier inconsistency error signature, an uncombined precise point positioning (PPP) algorithm is developed with the inconsistency error treated with different schemes, including correction using established model, parameterization as a linear function, or estimated as an independent clock offset for carrier-phase observation. Meanwhile, to cope with the dual-frequency data deficiency of P40, the PPP algorithm is designed based on pure single-frequency processing which can handle mixed single- and dual-frequency observations. Positioning performances of three schemes are validated in both static and kinematic scenarios. With applying the code-carrier inconsistency schemes, P40 positioning precision reaches 0.2 m and 1.0 m for static and kinematic experiments, respectively, which is improved by an order of magnitude against the case without. Furthermore, precision can be even improved when P40 is equipped with an external geodetic-grade antenna. It reaches 5.8 and 18.2 cm in the static and kinematic tests, respectively, revealing improvements of 28.7% and 54.4% against the case without considering the inconsistencies, respectively. Such result is very encouraging and indicate a positioning accuracy level close to a geodetic receiver. [ABSTRACT FROM AUTHOR]

The seismic hazard along the Himalayan arc remains a focus of discussion due to its huge potential societal impact. Taking advantage of modern, dense geodetic observations, several attempts have been made to provide a clear picture of the present‐day rate of strain accumulation caused by interseismic coupling on the Main Himalayan Thrust (MHT). However, there are differing opinions regarding the interpretation of spatial variation in interseismic coupling along some parts of the arc. Critically, the resolution of heterogeneity of coupling is limited due to sparse geodetic observations in some areas. In the present work, we use an updated compilation of all available Global Navigation Satellite System (GNSS) data along the Himalayan arc and a suite of kinematic block models to account for deformation within the overriding plate to characterize the status of interseismic plate coupling. Our results show that the MHT is highly coupled (>0.8) along its entire length and the coupling distribution is nearly binary along‐dip. This translates to a high seismic hazard in the densely populated Indo‐Gangetic plains with a seismic moment accumulation of one Mw 8.7 megathrust earthquake per 100 years. Our results suggest that previously inferred low coupling zones along the MHT are possible manifestations of block modeling artifacts, where the fault segments in the overriding plate control the megathrust slip distribution more strongly than structures within the Indian lithosphere. This result highlights a strong need for better characterization of deforming structures in the overriding plate within the Himalayas and southern Tibetan plateau. Plain Language Summary: More than two‐thirds of the Himalayan megathrust, the plate boundary between the Indian and Eurasia plates, has not ruptured in the past 200 years. Kinematic plate coupling derived from GNSS observations is an important parameter that can reveal which parts of the megathrust are likely to generate future great earthquakes (high coupling means high earthquake potential). Prior attempts have been made to provide a clear picture of the kinematic coupling along the Himalayan megathrust; however, different opinions exist. In particular, the presence of low coupling zones as a result of the interaction of sub‐surface structures has been inferred by some authors but not others. In the present study, we reevaluated the Himalayan plate coupling by considering an updated compilation of all available GNSS data and a suite of kinematic block models to account for deformation within the overriding plate. We found the megathrust is highly coupled along its entire length and stores elastic strain equivalent to an Mw 8.7 megathrust earthquake every 100 years. Our modeling results suggest that previously inferred low coupling zones are possibly related to geodetic modeling artifacts, and are not associated with sub‐surface structures within the Indian lithosphere. Key Points: Global Navigation Satellite System data suggest the Main Himalayan Thrust is highly coupled along its entire lengthPreviously inferred low coupling zones are possible manifestations of block modeling artifactsOverriding plate deformation controls the inferred megathrust slip distribution more strongly than structures within the Indian lithosphere [ABSTRACT FROM AUTHOR]

Celestial phenomena such as solar eclipses disrupt the ionosphere's inherent photochemical, dynamic, and electrodynamic processes and can be viewed as a natural experiment that provides a unique opportunity to study ionospheric perturbations. We investigate the spatiotemporal ionospheric response induced by the 14 October 2023 annular eclipse using ground‐based Global Navigation Satellite System (GNSS) receivers located over the continental region of North and South America. The largest total electron content (TEC) change (∼22 TECU decrease) is observed over the path of the eclipse at around 16°–18°N which lies just before the greatest eclipse location. However, the percentage change in TEC here is ∼44% (of the background value), which is less than that observed at midlatitudes around 30°–35°N (∼18.7 TECU, ∼50%). We observed a latitudinal dependency of TEC variation and time delay in ionospheric response to the eclipse with midlatitudes experiencing greater TEC changes and longer time delays compared to low‐latitude and equatorial regions. The SAMI3 model used to simulate the impact of the eclipse, captures the large decrease in VTEC along the eclipse path. Interestingly, increases in the TEC are also observed in several GNSS sites and it varied from 4.5 to 6.5 TECU in the Northern Hemisphere and 7 to 12 TECU in the Southern Hemisphere. The SAMI3 model results also show an enhancement in TEC but significantly less than that observed. Moreover, the SAMI3 model simulations for individual GNSS site coordinates within the conjugate regions failed to predict accurately, the TEC enhancement recorded by the GNSS sites. Key Points: The total electron content (TEC) depletion and time delay in ionospheric response to the solar eclipse exhibited a latitudinal dependency within the eclipse regionSAMI3 model accurately simulated the observed TEC drop in the eclipse region but underpredicted the TEC enhancement in the conjugate regionsTEC increase in the Southern Hemisphere conjugate region is attributed to uplifted plasma resulting from an enhanced E × B drift velocity [ABSTRACT FROM AUTHOR]

The integrated navigation system based on the Global Navigation Satellite System (GNSS) in conjunction with the strapdown inertial navigation system (SINS) and the Doppler Velocity Logger (DVL) is essential for accurate and long-distance navigation in maritime environments. However, the error of the integrated navigation system gradually diverges due to the inevitable velocity measurement error of DVL when GNSS outages occur. To ensure the high navigational accuracy and stability of SINS, it is necessary to dynamically adjust the damping state of SINS provided externally. In this paper, we have developed a novel method for damping state switching based on machine learning with SINS. We construct a model of the change in reference velocity error and use sliding window technology to obtain the reference velocity error for model training. Before training, the digital compass loop is designed to process and highlight the change in reference velocity change errors. In order to reduce the impact of the damping switching, a variable damping system is used to transform the traditional one-time switching of the damping coefficient into a gradual switching, effectively reducing the impact of a sudden change in the damping coefficient on the system. Simulation experiments and tests on ships show that the proposed method effectively reduces the overshoot error integrated underwater during state switching. This research is of great importance for the optimal design of integrated underwater navigation systems. [ABSTRACT FROM AUTHOR]

The automatic identification system (AIS) can improve situational awareness at sea, but its protocol is simple and does not guarantee message integrity, authentication, and proper use. For example, the lack of safety measures creates problems when AIS messages are used for tracking a target or predicting a target trajectory. We present a methodology for the validation of AIS messages, a prerequisite for their safe use in maritime situational awareness applications. The validation method relies on target trackers that fuse AIS data and exteroceptive sensor data, and it detects errors in position, speed and course, and rate of turn. We use radar data to exemplify exteroceptive sensor data. With the use of simulated data, we show that the proposed methods effectively detect errors in the position and velocity data received through AIS messages and are also able to detect errors in turn-rate data. The effectiveness of the methods is demonstrated on a real-world dataset with injected false AIS data. [ABSTRACT FROM AUTHOR]

In this article, we address the potential effects of construction activities around a permanent Global Navigation Satellite System (GNSS) station. The study is based on a consistent time series of GNSS observations collected over a span of almost 13 years and comprises an analysis in both observation and coordinate domains. The analysis in the observation domain revealed a significant increase of the code multipath for the C1C signal of GPS and GLONASS. In terms of standard deviations the values increased by 37 and 31%, respectively. No significant increase was observed for other signals. Interestingly, the analysis showed that the Galileo E5 AltBOC signal outperformed the other signals in distinguishing direct from indirect signals. In the coordinate domain, the relative GNSS solution results demonstrated an increase in root mean square error for the eastern component during the same period. Noteworthy, the observed increase in both domains coincided with the period of the highest level of construction activity around the GNSS station. These findings suggest that the construction activity near the station impacted the quality of GNSS observations and that the Galileo E5 AltBOC signal was better at compensating for local changes than other signals.

Abstract High-precision Global Navigation Satellite System (GNSS) orbit and clock products are crucial for precise applications. An evenly distributed global network enables continuous tracking for GNSS satellites, while a regional network may result in tracking gaps in the areas where monitoring stations are not deployed. This also means that the orbit determination accuracy based on a regional network is not comparable to that with a global network. Integrating the measurements from regional ground stations and Low Earth Orbit (LEO) satellites onboard receivers is a potential approach for generating GNSS orbit and clock products with centimeter-level accuracy, which is particularly important for BDS and the local commercial providers relying on a regional network. In the integrated Precise Orbit Determination (POD), LEO satellites are used to compensate for the drawback of regional ground stations in the precise orbit and clock determination of GNSS satellites. To validate the role of LEO satellites in the orbit determination with a regional network, 6 International GNSS Service stations around China and 13 LEO satellites from January 20 to 26, 2019, including GRACE-C/D, SWARM-A/B/C, Jason-3, Sentinel-3A/B, and SAT-A/B/C/D/E are selected in this study to perform the integrated POD. The orbit and clock accuracies of GPS and LEO satellites are evaluated by comparison with precise products. The average Root Mean Square (RMS)of GPS orbit errors in the radial (R), along-track (T) and cross-track (N) directions are 2.27 cm, 3.45 cm, and 3.08 cm, respectively, and the clock accuracy is better than 0.15 ns based on a comparison with the final products provided by Center for Orbit Determination in Europe (CODE). The LEO orbit accuracy is better than 2 cm in the R direction, and the position errors are mostly within 4 cm. The results indicate that the integrated POD can generate high-precision orbit and clock products for GPS and LEO satellites based on regional network stations. Finally, the integrated POD products are assessed for Precise Point Positioning (PPP). Simulated kinematic PPP has a comparable performance in terms of the convergence time and positioning accuracy. With more LEO satellites available, the orbit and clock determination accuracy and PPP positioning accuracy can be improved.

Abstract Global Navigation Satellite System (GNSS) can provide an approach for spacecraft autonomous navigation in earth–moon space to make up for the insufficiency of earth-based tracking, telemetry, and control systems. However, its weak power and poor observation geometry near the moon causes new problems. After the GNSS signal characteristics and satellite visibility were evaluated in Phasing Orbit and Lunar Transfer Orbit, we proposed an adaptive Kalman filter based on the Carrier-to-Noise ratio (C/N 0) and innovation vector to weaken the influence of GNSS accuracy attenuation as much as possible. The experimental results show that the spacecraft position and velocity accuracy are better than 10 m and 0.1 m/s near the Earth, and better than 50 m and approximately 0.2 m/s near the moon use GNSS with the proposed adaptive algorithms. Additionally, because of the deterioration of navigation performance based on the orbit filter during orbital maneuvering, we used accelerometer data to compensate for the dynamic model to maintain navigation performance. The results of the experiment provide a reference for subsequent studies.

The ocean tide loading (OTL) can result in displacements of centimeters or even decimeters at nearshore stations. Global ocean tide models exhibit errors in nearshore regions, which limit the accuracy of maintaining the coordinates of these stations. GNSS positioning can obtain tidal load displacements in nearshore areas, but it often requires long-term observation data and cannot provide timely correction models for newly established reference stations. This paper proposes a method for an empirical correction model of short-term OTL displacements using GNSS observations, where the kinematic coordinate sequences are first obtained by multi-GNSS precise point positioning with ambiguity resolution (PPP-AR), and then the OTL corrections are obtained by window-sliding forecast based on random forest modeling. Through experiments conducted in the Hong Kong region, the empirical model with a window of 15 days is established by the proposed method. After applying the empirical model, root mean square errors of the residuals are reduced by 1.5 (30.6%), 3.7 (53.6%), and 3.7 mm (37.8%) in the East, North, and Up (ENU) components, respectively. When using the global ocean tide model FES2014, the RMSE values are reduced by 1.2 (24.5%), 0.3 (4.3%), and 3.7 mm (37.8%) in the ENU components, respectively. The empirical model shows better effects for the OTL displacement compared to FES2014, especially in the N component, with an improvement ratio of about 49.3%. [ABSTRACT FROM AUTHOR]

High-precision Global Navigation Satellite System (GNSS) orbit and clock products are crucial for precise applications. An evenly distributed global network enables continuous tracking for GNSS satellites, while a regional network may result in tracking gaps in the areas where monitoring stations are not deployed. This also means that the orbit determination accuracy based on a regional network is not comparable to that with a global network. Integrating the measurements from regional ground stations and Low Earth Orbit (LEO) satellites onboard receivers is a potential approach for generating GNSS orbit and clock products with centimeter-level accuracy, which is particularly important for BDS and the local commercial providers relying on a regional network. In the integrated Precise Orbit Determination (POD), LEO satellites are used to compensate for the drawback of regional ground stations in the precise orbit and clock determination of GNSS satellites. To validate the role of LEO satellites in the orbit determination with a regional network, 6 International GNSS Service stations around China and 13 LEO satellites from January 20 to 26, 2019, including GRACE-C/D, SWARM-A/B/C, Jason-3, Sentinel-3A/B, and SAT-A/B/C/D/E are selected in this study to perform the integrated POD. The orbit and clock accuracies of GPS and LEO satellites are evaluated by comparison with precise products. The average Root Mean Square (RMS)of GPS orbit errors in the radial (R), along-track (T) and cross-track (N) directions are 2.27 cm, 3.45 cm, and 3.08 cm, respectively, and the clock accuracy is better than 0.15 ns based on a comparison with the final products provided by Center for Orbit Determination in Europe (CODE). The LEO orbit accuracy is better than 2 cm in the R direction, and the position errors are mostly within 4 cm. The results indicate that the integrated POD can generate high-precision orbit and clock products for GPS and LEO satellites based on regional network stations. Finally, the integrated POD products are assessed for Precise Point Positioning (PPP). Simulated kinematic PPP has a comparable performance in terms of the convergence time and positioning accuracy. With more LEO satellites available, the orbit and clock determination accuracy and PPP positioning accuracy can be improved. [ABSTRACT FROM AUTHOR]

An automatic identification system (AIS) is often installed on merchant ships and fishing boats to prevent collisions and ensure safe navigation. The location information of ships transmitted from AIS equipment can help maritime traffic control prevent accidents. The southern coast of Korea comprises a complex coastline with numerous fishing boats and transit vessels. In particular, the Tongyeong and Geoje Islands include high-altitude mountains and islands, resulting in several radio-shaded areas where AIS signals cannot be received, owing to geographical effects. However, only a few studies have explored this region and performed practical experiments on the reception status of AIS locations in radio-shaded areas. In this study, we performed an experiment in the Geoje Island Sea on the southern coast to analyze the impact of high terrain on the reception rate and status of automatic identification devices. Two identical pieces of AIS equipment were installed to generate multiple radio waves, and the location data transmitted via different antennae were compared. The experimental analysis forms the basis for identifying the exact location of ships in the event of maritime accidents, facilitating rapid rescue. Moreover, the accuracy of the location transmitted by the AIS equipment can aid in detecting the cause of accidents. [ABSTRACT FROM AUTHOR]

High-precision positioning is a fundamental requirement for autonomous vehicles. However, the accuracy of single-sensor positioning technology can be compromised in complex scenarios due to inherent limitations. To address this issue, we propose an adaptive multi-sensor fusion localization method based on the error-state Kalman filter. By incorporating a tightly coupled laser inertial odometer that utilizes the Normal Distribution Transform (NDT), we constructed a multi-level fuzzy evaluation model for posture transformation states. This model assesses the reliability of Global Navigation Satellite System (GNSS) data and the laser inertial odometer when GNSS signals are disrupted, prioritizing data with higher reliability for posture updates. Real vehicle tests demonstrate that our proposed positioning method satisfactorily meets the positioning accuracy and robustness requirements for autonomous driving vehicles in complex environments. [ABSTRACT FROM AUTHOR]

Purpose. To investigate the current state of inertial sensors for navigation of unmanned aerial vehicles (UAVs), analyse their advantages, disadvantages, methods of error correction and integration with other navigation systems, as well as identify development prospects and current trends in this area. Methodology. A systematic review of scientific literature, technical documents and studies related to various types of inertial sensors, their application in UAV navigation, and data fusion methods was conducted. A comparative analysis of modern technologies and methods to sensor integration is used. Findings. The main types of inertial sensors, their advantages and disadvantages are identified, and the most effective methods of error correction and integration with other systems are revealed. Modern trends, such as the use of artificial intelligence, the development of microelectromechanical systems and the emergence of new types of sensors that contribute to the accuracy and reliability of UAV navigation, are investigated. Particular attention is paid to the integration of inertial measurement units (IMUs) with other navigation sensors, such as the Global Navigation Satellite System and visual sensors, to ensure more reliable and accurate navigation. Error correction methods, such as the Kalman filter and adaptive filters, used to improve the accuracy of navigation systems are systematised. Originality. For the first time, the types of inertial sensors are systematized and analyzed, and data on their advantages and disadvantages in the context of navigation requirements in modern UAV navigation systems are determined. Practical value. The results obtained can be used to improve UAV navigation systems, increase their reliability and accuracy. Recommendations for the selection and integration of sensors will contribute to the development of new technologies in the field of unmanned aerial vehicles. [ABSTRACT FROM AUTHOR]

In recent years, advancements in Light Detection and Ranging (LiDAR) technology have made 3D LiDAR sensors more compact, lightweight, and affordable. This progress has spurred interest in integrating LiDAR with sensors such as Inertial Measurement Units (IMUs) and cameras for Simultaneous Localization and Mapping (SLAM) research. Public datasets covering different scenarios, platforms, and viewpoints are crucial for multi-sensor fusion SLAM studies, yet most focus on handheld or vehicle-mounted devices with front or 360-degree views. Data from aerial vehicles with downward-looking views is scarce, existing relevant datasets usually feature low altitudes and are mostly limited to small campus environments. To fill this gap, we introduce the Multi-sensor Aerial Robots SLAM dataset (MARS-LVIG dataset), providing unique aerial downward-looking LiDAR-Visual-Inertial-GNSS data with viewpoints from altitudes between 80 m and 130 m. The dataset not only offers new aspects to test and evaluate existing SLAM algorithms, but also brings new challenges which can facilitate researches and developments of more advanced SLAM algorithms. The MARS-LVIG dataset contains 21 sequences, acquired across diversified large-area environments including an aero-model airfield, an island, a rural town, and a valley. Within these sequences, the UAV has speeds varying from 3 m/s to 12 m/s, a scanning area reaching up to 577,000 m2, and the max path length of 7.148 km in a single flight. This dataset encapsulates data collected by a lightweight, hardware-synchronized sensor package that includes a solid-state 3D LiDAR, a global-shutter RGB camera, IMUs, and a raw message receiver of the Global Navigation Satellite System (GNSS). For algorithm evaluation, this dataset releases ground truth of both localization and mapping, which are acquired by on-board Real-time Kinematic (RTK) and DJI L1 (post-processed by its supporting software DJI Terra), respectively. The dataset can be downloaded from: https://mars.hku.hk/dataset.html. [ABSTRACT FROM AUTHOR]

Indoor and outdoor positioning systems are difficult to locate in large areas and complex environments. In order to compensate for the impact of indoor and outdoor scene transformation, an indoor and outdoor positioning system based on GNSS/UWB/IMU is proposed, which can realize seamless and high-precision positioning between buildings in mixed scenes. In view of this, GNSS and IMU fusion is used outdoors for Error-State Kalman Filter (ESKF) filtering for positioning. At the same time, this paper proposes a D-CEP algorithm to analyze the UWB ranging variance offline and improve the accuracy of UWB positioning data. In the mixed scene, the UWB and GNSS information are tightly coupled and nonlinearly optimized to improve the positioning accuracy and achieve seamless connection between indoor and outdoor staggered scenes. Indoor and outdoor scenes use UWB and IMU fusion for ESKF filtering to achieve indoor and outdoor high precision. In indoor complex scenes, due to the existence of Ultra-wideband non line of sight (UWB-NLOS) error, the observation data may be discontinuous. When the number of observed signals is less than the number required for nonlinear optimization, the UWB-NLOS error is compensated by IMU prior information, and the positioning data is obtained to make up for the lack of positioning data and realize indoor and outdoor seamless positioning. Compared with the traditional filtering method, the average positioning accuracy is improved by 40.97 % (the Mean Absolute Error is increased from 0.256336 m to 0.151308 m). Compared with the state-of-the-art LiDAR-SLAM (LIO-SAM), the approximate positioning result can be obtained (ESKF-UWB-NLOS Mean Absolute Error is 0.151308 m, LiDAR-SLAM Mean Absolute Error is 0.148853 m). [ABSTRACT FROM AUTHOR]

Grid partitioning plays a crucial role in real-time zenith total delay (ZTD) modeling. However, commonly employed methods rely on empiricism to establish uniform grid resolutions, which do not conform to the actual distribution of ZTD in real-time scenarios. In this study, we address this issue by employing the two-dimensional Fourier transform to analyze the horizontal perturbation characteristics of ZTD. We propose a multi-scale adaptive grid partition method based on the amplitude and frequency of horizontal ZTD variations to achieve rational grid partitioning for real-time modeling. This method reduces systematic differences in ZTD values within the grid and accurately describes the horizontal distribution of ZTD using fewer parameters. Furthermore, it enables adaptive grid partitioning of two-dimensional ZTD data in arbitrary regions. We conduct global experiments involving 864 sets and regional experiments comprising 408 sets of two-dimensional ZTD data obtained from the 2021–2023 global reanalysis dataset provided by the European Centre for Medium-Range Weather Forecasts, while validating our method against International GNSS service products and Radiosonde data as in-situ observations. The results demonstrate that the multi-scale adaptive grid partition method accurately captures annual periodic variations in horizontal disturbance caused by seasonal changes in the temporal dimension while reflecting a strong correlation between horizontal disturbance and latitude variations in the spatial dimension. The statistical results from 1272 experiments, coupled with validation using in-situ datasets, reveal that the mean standard deviation (STD) of ZTD within the partitioned grids ranges approximately between 1.200 and 2.500 cm. This range is relatively minor compared to the magnitude of the ZTD value. This finding reflects the uniformity observed in ZTD data within the partitioned grids. Moreover, the STD across all grids, around 9.500 cm, is several times higher than the mean STD within each grid, highlighting significant variability across distinct grid regions. These verify the validity and reliability of the proposed method. Additionally, in comparison with the traditional method, the proposed method has shown a notable improvement, enhancing accuracy by 12.541% and grid utilization rate by 29.131%. Furthermore, our method demonstrates robust reliability and applicability even under adverse weather conditions, thus offering valuable theoretical support and substantial guidance for the real-time discretized modeling of ZTD. [ABSTRACT FROM AUTHOR]

Accurately measuring precipitable water vapor (PWV) is challenging, especially in the absence of the measured meteorological data. We propose a novel grid model, CZP, that directly converts zenith tropospheric delay to PWV, leveraging ERA5 reanalysis data from 2016 to 2019. The CZP model considers the seasonal variability of the PWV and the spatial characteristics of the conversion coefficients, achieving high accuracy PWV retrieval in the tropics efficiently. Our findings demonstrate the CZP model's high accuracy and reliability across tropical IGS stations, with a mean bias and root mean square (RMS) well within acceptable limits compared to both ERA5, GNSS and radiosonde (RS) PWV measurements. The bias and RMS values for CZP PWV compared to GNSS PWV are less than 1.1 mm and 1.4 mm, while those values with respect to RS PWV are 1.61 mm and 3.11 mm, respectively. Furthermore, the real-time CZP PWV estimates show superior accuracy over the GPT3 model, with mean bias and RMS of − 0.55 mm and 3.55 mm, respectively. Such results underscore the CZP model's potential for enhancing weather prediction and climate research in data-scarce environments. [ABSTRACT FROM AUTHOR]

Global Navigation Satellite System (GNSS) can provide an approach for spacecraft autonomous navigation in earth–moon space to make up for the insufficiency of earth-based tracking, telemetry, and control systems. However, its weak power and poor observation geometry near the moon causes new problems. After the GNSS signal characteristics and satellite visibility were evaluated in Phasing Orbit and Lunar Transfer Orbit, we proposed an adaptive Kalman filter based on the Carrier-to-Noise ratio (C/N0) and innovation vector to weaken the influence of GNSS accuracy attenuation as much as possible. The experimental results show that the spacecraft position and velocity accuracy are better than 10 m and 0.1 m/s near the Earth, and better than 50 m and approximately 0.2 m/s near the moon use GNSS with the proposed adaptive algorithms. Additionally, because of the deterioration of navigation performance based on the orbit filter during orbital maneuvering, we used accelerometer data to compensate for the dynamic model to maintain navigation performance. The results of the experiment provide a reference for subsequent studies. [ABSTRACT FROM AUTHOR]

One of the key challenges in Multi-Spectral Automatic Diagnostic (MAD) robot design is the precise targeting of narrow-angle cameras on a specific part of the equipment. The paper shows that a low-cost MAD robot, whose navigation system is based on open-source ArduRover firmware and a pair of low-cost Ublox F9P GNSS receivers, can inspect the 8 × 4 degree ultraviolet camera bounding the targeting error within 0.5 degrees. To achieve this result, we propose a new targeting procedure that can be implemented without any modifications in ArduRover firmware and outperforms more expensive solutions based on LiDAR SLAM and UWB. This paper will be interesting to the developers of robotic systems for power equipment inspection because it proposes a simple and effective solution for MAD robots' camera targeting and provides the first quantitative analysis of the GNSS reception conditions during power equipment inspection. This analysis is based on the experimental results collected during the inspection of the overhead power transmission lines and equipment inspections on the open switchgear of different power plants. Moreover, it includes not only satellite, dilution of precision, and positioning/heading estimation accuracy but also the direct measurements of angular errors that could be achieved on operating power plants using GNSS-only camera targeting. [ABSTRACT FROM AUTHOR]

The Global Navigation Satellite System (GNSS) can be utilized for long-distance and high-precision time transmission. With the ongoing development of low Earth orbit (LEO) satellites and the rapidly changing geometric relationships between them, the convergence rate of ambiguity parameters in Precise Point Positioning (PPP) algorithms has increased, enabling fast and reliable time transfer. In this paper, GPS is used as an experimental case, the LEO satellite constellation is designed, and simulated LEO observation data are generated. Then, using the GPS observation data provided by IGS, a LEO-enhanced PPP model is established. The LEO-augmented PPP model is employed to facilitate faster and more reliable high-precision time transfer. The application of the LEO-augmented PPP model to time transfer is examined and discussed through experimental examples. These examples show multiple types of time transfer links, and the experimental outcomes are uniform. GPS + LEO is compared with exclusive GPS time transfer schemes. The clock offset of the time transfer link for the GPS + LEO scheme converges more swiftly, meaning that the time required for the clock offset to reach a stable level is the briefest. In this paper, standard deviation is employed to assess stability, and Allan deviation is utilized to assess frequency stability. The results show that the clock offset stability and frequency stability achieved by the GPS + LEO scheme are superior within the convergence time range. Controlled experiments with different numbers of satellites for LEO enhancement indicate that time transfer performance can be improved by increasing the number of satellites. As a result, augmenting GPS tracking data with LEO observations enhances the time transfer service compared to GPS alone. [ABSTRACT FROM AUTHOR]

The Rodl-Kaplice-Blanice fault system (RKB) of Variscan shear origin, repeatedly active since the Late Paleozoic to the Recent, is expressed by a number of lithological contacts, distinct geophysical gradients and many landforms. A general trend of the RKB as well as linear configuration of its internal architecture is fairly similar to those of topical near Rhine Graben and Alpine-Carpathian transition area as the two other consistent recently reactivated large-scale tectonic structures in the extended (thinned) crust of central Europe. In middle part of the RKB, the occurring linear topographic and geological features parallel to the main RKB sections point to the existence of a wide tectonic zone in the crust following the fault system. Our multidisciplinary study includes a summary of corresponding basic geological data, overview of seismic, regional geophysical and geomorphological conditions, primary model of recent kinematic activity in the RKB area derived from the space (Global Navigation Satellite System—GNSS) monitoring and terrestrial (repeated high precision levelling) geodetic data and comparison of these various information. The obtained knowledge indicates that the RKB is active up to ~ 1.0 mm horizontally and > 0.5 mm vertically. The fault system area in the Bohemian Massif can be subdivided into the three parts of diverse tectonic structure and block kinematics. Sinistral horizontal movements are highest near the southern surface sections (Rodl-Kaplice, Rudolfov and Drahotěšice faults), whereas noticeable vertical differentiation is going on mainly along the Blanice and Kouřim faults in the north where the RKB activity is gradually decreasing towards the extensive Elbe shear zone with transverse movements. The middle part of the RKB is dislocated by a large active transverse tectonic structure of the South Bohemian Basins (SBB) with variable horizontal velocity vectors of surface GNSS stations. Most of the weak regional earthquakes have been recorded west of the RKB. Besides faults of the SBB, these were mainly associated with the RKB-subparallel Lhenice fault. Based on the earthquake distribution and foci depths, the latter fault can have similar structural position as the RKB related to lower part of the Variscan level in the ~ 10–12 km depth. [ABSTRACT FROM AUTHOR]

In the next generation of smart cities, Unmanned Aerial Vehicles (UAV) also known as drones are playing a vital role in many advanced applications such as power transmission line inspection, transportation, aerospace and surveillance etc. Due to the excessively high and wide transmission tower heights, the conventional methods of power line inspection are generally ineffective. This manuscript’s primary focus is the development of an autonomous UAV/ quadcopter that can hover over transmission towers and capture photographs and videos by flying along pre-planned routes. Quadcopters have a distinct feature that distinguishes them with the existing aerial vehicles and have a vital role in wide range of applications such as live monitoring of traffic and crowded areas, remote locations, delivery and inspection. This manuscript also explains about the advanced sensors & components such as Global Navigation Satellite System (GNSS), optical flow sensor and Here Link etc. required for fabrication of an autonomous quadcopter for power transmission line applications. The fabricated quadcopter includes a light weight S-500 frame equipped with intelligent controller such as Pixhawk cube orange (2.1) and NVIDIA nano board for receiving and analyzing the data from the onboard sensors and camera based on pre-determined criteria. The proposed approach increases effectiveness and accuracy, has a promising future for intelligent insulator detection and inspection which is a valuable addition to power networks. The suggested deep learning technique has a detection speed of 51.8 frames/sec and a detection accuracy of up to 90.31 percent. The suggested DL algorithm has a promising future in terms of intelligent insulator inspection in power grids. [ABSTRACT FROM AUTHOR]

The paper solves the problem of deriving the relationship between the variability of statistical characteristics of atmospheric parameters measured by GNSS receivers and the characteristics of convective processes based on monitoring data near the Kazan city for 2013–2021. The GNSS monitoring results are compared with the convective indices, which are physical and statistical parameters of instability, calculated from ERA5 reanalysis: upward vertical velocity, vortex generation parameter, and WMAXSHEAR. Statistical characteristics of the horizontal gradient of the zenith tropospheric delay are shown to significantly change under conditions of deep convection. The results of the work can be used to develop a technique for sub-satellite monitoring of convective processes in the tasks of operational forecasting of severe weather phenomena. [ABSTRACT FROM AUTHOR]

Abstract Ionospheric scintillation causes major impairments to Global Navigation Satellite System (GNSS) in low-latitude regions. In severe scenarios, this event can lead to complete loss of lock, thus making GNSS measurements unusable for navigation. In this paper, we derive a cooperative localization algorithm where a set of partially connected aircraft exchange messages with neighboring nodes on the network to improve their own position estimates. We consider the scintillation events as abrupt changes in the measurement variance, which are modeled by a discrete-valued Markov process at the nodes which have access to GNSS measurements. Simulation results show that Markovian modeling and cooperation via factor graph message passing reduce the average 3D root mean square localization error and yield an average vertical position error that meets civil aviation standards for approach and landing.

Abstract Monitoring and predicting fault slip behaviors in subduction zones is essential for understanding earthquake cycles and assessing future earthquake potential. We developed a data assimilation method for fault slip monitoring and the short-term prediction of slow slip events, and applied to the 2010 Bungo Channel slow slip event in southwest Japan. The observed geodetic data were quantitatively explained using a physics-based model with data assimilation. We investigated short-term predictability by assimilating observation data within limited periods. Without prior constraints on fault slip style, observations solely during slip acceleration predicted the occurrence of a fast slip; however, the inclusion of slip deceleration data successfully predicted a slow transient slip. With prior constraints to exclude unstable slip, the assimilation of data after slow slip event occurrence also predicted a slow transient slip. This study provides a tool using data assimilation for fault slip monitoring and prediction based on real observation data. Graphical Abstract

Assessing the condition of roads is crucial to the maintenance and rehabilitation process as a country's progress is closely linked to its transport infrastructure. Therefore, it is essential to have well-maintained roads and to be able to control and monitor them properly. Technological advancements have transformed the way pavement inspections are carried out. This study presents an innovative approach that combines stereo cameras and a GPS module for efficient and accurate data collection. This integration of low-cost technologies provides a detailed three-dimensional view of pavements, complemented by accurate geospatial information. The experimental results showed that the 3D images of pavement damage had a relative volume measurement error of 0.80 %. Unlike traditional systems such as LIDAR and ground-penetrating radar, which involve more expensive technologies, the proposed method offers a cost-effective solution. This methodology not only simplifies the inspection process but also improves the planning and execution of road maintenance and repair activities. Its low cost makes it a viable option for various projects and applications in road infrastructure.

Real-time monitoring technologies of surface deformation represented by the global navigation satellite system (GNSS) are essential for landslides early warning. Monitoring methods such as GNSS require on-site manual installation. Therefore, it becomes nearly impossible to deploy surface monitoring equipment when landslides are located in high mountain valleys that are challenging for personnel to access, and/or in hazardous situations. We propose an intelligent real-time monitoring and early-warning technology that employs an unmanned aerial vehicle (UAV) as a carrier to deploy GNSS equipment. A system was initially designed with five components: an adaptive sampling GNSS receiver, an intelligent cooperative network transmission module, UAV-dropped GNSS equipment, special delivery UAV, and an intelligent monitoring and early warning cloud platform. This new technology was applied to a real landslide in Gansu Province, China, in 2020. The mean absolute error of 30 days in the east, north, and upward directions were 1.2, 1.3, and 2.9 mm/d, respectively, comparing the deformation velocity between the traditional monitoring station and the UAV-dropped monitoring station. This observation facilitated the successful prediction of a landslide hazard on 27 January 2021, allowing for a timely alert to be issued. Collectively, the results of this study established that UAV-deployed GNSS technology can accomplish unmanned deployment of GNSS equipment for landslide monitoring to ensure early warning issuance in inaccessible and/or high-risk areas.

• Real-time high-precision single-epoch relative position determination based on GNSS. • Optimized measurements considering the influence of GEO satellites in BDS. • Developed a real-time measurement module for high-dynamic satellite formations. • Error is within centimeter-level, computed in less than 0.1 s for a single epoch. With the establishment of the Chinese space station, a series of space science missions will be conducted in its vicinity. One of the extended tasks for the in-orbit service of space station is the formation flying of small satellites centered around the space station. Satellite formations can perform simultaneous three-dimensional observations of the space station, generating three-dimensional images and monitoring and assessing the status of critical components of the space station. The real-time and accurate relative position measurement is one of the key issues in formation flying. It is a fundamental prerequisite for maintaining and reconfiguring formation configurations, collision avoidance and safety assurance. GNSS-based relative positioning is a low-cost and high-precision measurement method, which is not constrained by light, weather, or relative attitude of satellites. This study introduces a novel approach to determine the relative position of satellites based on single-epoch Global Navigation Satellite System (GNSS) carrier phase difference measurements. Unlike traditional methods, the proposed technique eliminates the need for precise ephemeris and clock bias files and does not require historical observation data. The algorithm avoids the complexity associated with full cycle ambiguity jumps, facilitating real-time, high-precision calculations of relative position baseline vectors. Special attention is given to the influence of Geostationary Earth Orbit (GEO) satellites in the BeiDou Navigation Satellite System (BDS), and measures are taken to mitigate their impact on measurement accuracy by adjusting their observation weights. Our newly developed GNSS-based real-time measurement module, designed for high-quality GNSS signal reception and data communication, was tested on terrestrial and simulated low-orbit platforms. Remarkably, over baselines ranging from 10 m to 9.3 km, while traditional pseudorange differential measurements showed errors up to 1.5571 m, our proposed method consistently held errors under 5 cm and ensured computational speeds within 0.1 s per epoch. High-dynamic zero-baseline tests further validated its potential, with errors less than 1 cm. The innovations encapsulated in this work, resonating with the evolving trends of miniaturized and scalable satellites, present a cost-efficient and real-time solution for inter-satellite relative position measurement. This promises a new horizon in satellite formation technology, with future endeavors focusing on on-orbit experiments. [ABSTRACT FROM AUTHOR]

Ionospheric scintillation causes major impairments to Global Navigation Satellite System (GNSS) in low-latitude regions. In severe scenarios, this event can lead to complete loss of lock, thus making GNSS measurements unusable for navigation. In this paper, we derive a cooperative localization algorithm where a set of partially connected aircraft exchange messages with neighboring nodes on the network to improve their own position estimates. We consider the scintillation events as abrupt changes in the measurement variance, which are modeled by a discrete-valued Markov process at the nodes which have access to GNSS measurements. Simulation results show that Markovian modeling and cooperation via factor graph message passing reduce the average 3D root mean square localization error and yield an average vertical position error that meets civil aviation standards for approach and landing. [ABSTRACT FROM AUTHOR]

This study proposes a model using 5G time-of-arrival data to assist global navigation satellite system precise point positioning ambiguity resolution. Specifically, the model addresses the problem of PPP requiring a long convergence time in partially satellite-occluded GNSS environments, such as urban canyons. First, we apply the ionosphere-free PPP model to estimate uncalibrated phase delays. Next, we combine real 5G data with GNSS data to determine whether introducing 5G observations will decrease the convergence time of the PPP solution. Experimental results reveal that the 5G-assisted PPP model can effectively improve the convergence efficiency of the float solution, lower the fixed time, and achieve greater positional reliability. Notably, the combination of GPS, BDS, and 5G with a sampling interval of 1 s obtains a fixed solution in an average of 1.12 min. Moreover, 5G-assisted GNSS positioning effectively compensates for partial satellite occlusion, optimizes the PDOP value, and speeds up ambiguity fixing. The introduction of three and more 5G base stations helps to obtain fixed solutions within 9 min when it is difficult to obtain fixed solutions relying only on GNSS. Our findings have important implications for improving the widespread applicability and effectiveness of satellite-based navigation systems in light of increasing urbanization and the rise of signal-occluding environments. [ABSTRACT FROM AUTHOR]

In this paper, we study the structure of the least square solutions to overdetermined systems with no solution. In the main theorem, we prove that if an overdetermined system with no solution is deformed into a system of linear equations by the semi-equivalent deformations defined in this paper, then an approximate solution to the original overdetermined system with no solution can be given as the unique least square solution to the deformed system of linear equations. We also introduce some applications of our main theorem to practical inverse problems. [ABSTRACT FROM AUTHOR]

Monitoring and predicting fault slip behaviors in subduction zones is essential for understanding earthquake cycles and assessing future earthquake potential. We developed a data assimilation method for fault slip monitoring and the short-term prediction of slow slip events, and applied to the 2010 Bungo Channel slow slip event in southwest Japan. The observed geodetic data were quantitatively explained using a physics-based model with data assimilation. We investigated short-term predictability by assimilating observation data within limited periods. Without prior constraints on fault slip style, observations solely during slip acceleration predicted the occurrence of a fast slip; however, the inclusion of slip deceleration data successfully predicted a slow transient slip. With prior constraints to exclude unstable slip, the assimilation of data after slow slip event occurrence also predicted a slow transient slip. This study provides a tool using data assimilation for fault slip monitoring and prediction based on real observation data. [ABSTRACT FROM AUTHOR]

Site selection for global navigation satellite system (GNSS) monitoring stations is the primary task in landslide GNSS monitoring work, and the selected site directly determines the monitoring effect of landslide deformation. Currently, the method for selecting site locations predominantly relies on the manual judgment of geological disaster experts by site inspections, which is experimental and labor-intensive. In this study, we propose an alternative site selection method on GNSS landslide monitoring station aided by interferometric synthetic aperture radar (InSAR) and unmanned aerial vehicle (UAV) photogrammetry methodology. Firstly, InSAR technology is used to obtain historical deformation data of the landslide area as prior information. Then, high-resolution digital surface model (DSM) and digital orthophoto map (DOM) are obtained by using UAV photogrammetric methodology, and relevant site selection criteria such as slope, aspect, surface roughness index, and vegetation index are extracted. Finally, the analytic hierarchy process (AHP) method is applied to evaluate and quantify the suitability of GNSS station site selection at various positions in the landslide area. The suitability of GNSS monitoring station site selection was evaluated in an experimental area located in the Heifangtai landslide in Northwest China's Gansu province. Seven evenly and reasonably distributed locations with suitability values exceeding 0.67 were recommended as potential sites for the construction of GNSS monitoring stations, which can meet the requirements for their establishment. With less manual intervention, this method provides quantitative and intuitive representation of suitability distribution, which make GNSS site selection more intelligent. [ABSTRACT FROM AUTHOR]

Carrier frequency phase differences of global navigation satellite system (GNSS) signals between multiple antennas are measured in many coordinate and navigation applications. GNSS signal simulators are used for determining and controlling instrumental errors of consumer navigation equipment. Therefore, determining the systematic error of the carrier frequency phase of the generated signals is imperative. On this basis, in this study, a calibration method of GNSS signal simulators based on the refined error model of the generated phase differences between simulator outlets was developed and tested. The proposed method was implemented using a wideband oscilloscope as an analog-to-digital converter. Validation of the simulator calibration method was performed by comparison with the measurement results obtained using the State secondary standard of units of complex transmission coefficients in the range of 0–60 dB and complex reflection coefficients in the range of 0.002–1 in the frequency range of 0.05–65 GHz (registration No. 2.1.ZZT.0210.2015). The proposed simulator calibration method can be used to determine calibration corrections to the phase differences of the carrier frequencies of radio signals reproduced by the simulator with an expanded uncertainty of 1° at a coverage factor of 3. The proposed method provides the required accuracy of generating phase differences of the carrier frequencies of GNSS signals for modern types of simulators. [ABSTRACT FROM AUTHOR]

Many studies have investigated the spatial variations of the ionosphere, but the quantitative characteristics of the ionosphere are rarely reported. In this paper, we utilize the total electron content (TEC) data to evaluate the latitudinal gradient of the ionosphere within 10°-50° N over the China sector. It is found that the magnitudes of latitudinal gradient are significantly higher within 10°-40° N and 45°-50° N, respectively. The database of TEC from 1 November 2018 to 31 October 2022 is processed to figure out the local time, seasonal, and solar activity dependency of the latitudinal gradient. The results suggest that the gradient within 10°-40° N is higher in the daytime and during high solar activity period. They are more noticeable in the spring and autumn, and least visible in the summer. Conversely, the gradient within 45°-50° N strengthens in the nighttime and under lower solar activity, and has larger values in the summer months. Furthermore, the International Reference Ionosphere (IRI-2020) model is assessed in terms of the reproducibility of latitudinal gradient. The IRI-2020 basically represents the latitudinal gradient within 10°-40° N, whereas it overestimates the gradient in the low solar activity period and misses the gradient features near 45°–50° N. [ABSTRACT FROM AUTHOR]

Multipath (MP) reception has been among the main issues for accurate and reliable positioning in urban environments. It has been shown to introduce positioning errors of up to tens of meters for conventional two-step (2SP) receivers. The direct position estimation (DPE) has been introduced as a more robust positioning algorithm compared to the conventional two-step (2SP) receivers in terms of MP mitigation. However, its high computational load prevents DPE from real-time positioning for commercial receivers. Thus, we present a novel grid-based maximum likelihood estimation (MLE) algorithm based on DPE by making use of pseudorange measurements to obtain the correlogram on a predefined searching space. Unlike DPE, which performs correlations at the intermediate frequency (IF) level, correlations are done by directly comparing the code phase of each candidate position, velocity, and timing with the incoming pseudorange. This way, the proposed method retains MP mitigation properties from DPE through the use of MLE from DPE and allows for a significantly reduced computational load compared to DPE. The proposed method was tested with both open-sourced datasets collected in urban environments as well as IF simulation data, and its performance is evaluated against a 2SP receiver. Results show that the proposed method manages to acquire the MP mitigation capability of DPE and outperforms 2SP by up to around 23% in the tested urban datasets and 91% in the simulation data, at a much-reduced computational time. The resilience of our proposed method against MP and NLOS could even potentially offer applications in geodetic networks, where robust estimators are traditionally employed to counteract outliers. [ABSTRACT FROM AUTHOR]

A dual-band circular polarized antenna with broad bandwidth is proposed. Two circular grooves with different radii are carved on the ground to generate two frequency bands. Two rectangular slots are engraved on the outside of the circular groove. By adjusting the length of the two slots, this antenna can radiate right-handed circularly polarized (RHCP) waves at two frequency bands, which can cover GPS L5 (1.176 GHz), L2 (1.227 GHz), L1 (1.575 GHz), BDS, GALILEO, and GLONASS bands. The measured −10 dB bandwidth is 46.3 % (1.13–1.81 GHz) and 3 dB axial ratio bandwidths are 15.6 % (1.11–1.30 GHz) and 17.8 % (1.38–1.65 GHz). The measured gains are 2.51 dBi and 2.67 dBi at 1.2 GHz and 1.56 GHz, respectively. [ABSTRACT FROM AUTHOR]

This paper presents estimates of surface reflectivity (SR) over time of global navigation satellite system (GNSS) signals scattered from a partially frozen lake surface. A portable ground-based GNSS reflectometry sensor system that collects both scattered global positioning system L1 signals and independent validation data (lidar and camera) was deployed on the Lake Michigan waterfront in Chicago at a time when the lake surface was a mixture of ice and water. Lidar surface scans were merged with camera images and mapped, along with estimated reflection zones. For three satellites whose reflection points scan across ice and water over time, the relative SR and mean red intensity (differentiating ice from water) of camera pixels inside the first Fresnel zone were computed and shown to be correlated. This system concept will be used in the future for more complete mapping of phase changes of snow and ice in the cryosphere. [ABSTRACT FROM AUTHOR]

The presence of Global Navigation Satellite System (GNSS) interference poses a significant risk to both GNSS and the infrastructures that depend on them. This article describes how an existing GNSS infrastructure, the Swedish Continuously Operating Reference Stations network SWEPOS with more than 500 stations, can be leveraged to control the quality of GNSS signals and to be able to detect interferences in GNSS and adjacent frequency bands. This study introduces a SWEPOS-based automatic system that effectively detects GNSS interference by examining the signal-to-noise ratio (SNR) of Global Positioning System, Globalnaya Navigatsionnaya Sputnikovaya Sistema, Galileo, and BeiDou frequency bands. By comparing the SNR of tracked satellites against historical data, the system detects radio frequency interference (RFI) by statistically characterizing the SNR of simultaneously tracked satellites. Furthermore, based on the SNR characteristics across satellites, the system distinguishes between RFI and non-RFI sources. The effectiveness of the detection system is demonstrated through both simulated signal interference waves and real-world interference events.

Destructive earthquakes with high deformations have occurred in the Aegean region since the historical period. The most destructive of these earthquakes in recent years is the October 30, 2020 (M w = 6.9) Samos (Aegean Sea) earthquake. This earthquake affected a wide area and caused numerous losses of lives and property especially in Izmir city. For examining the effects of the earthquake, Global Navigation Satellite System (GNSS) data before, during, and after the earthquake were processed, and coseismic and postseismic displacement evaluations were made. Interferometric Synthetic Aperture Radar (InSAR) ascending, descending interferograms, line of sight velocity, and displacement maps were obtained for the earthquake-affected area. The GNSS and InSAR data were evaluated together, and the areas with subsidence and uplift were determined in conjunction with the fault zone. In addition, the horizontal displacements were analyzed by using Coulomb failure criteria, and peak ground displacements were obtained from the strong motion stations located in the study region. As a result, from all the displacement analyses, it was determined that high-amplitude energy was released, at the regional scale from Ayvalık in the North to Datça in the South after the earthquake, and this earthquake generated permanent deformation in the affected region.