Search

Satellite-based navigation systems are widely used in transportation. GNSS signal's strength or quality can easily be degraded by local environments. As a result, the position accuracy of satellite-based navigation systems decreases. In this paper, a novel approach for estimating the positioning error is proposed using ML/DL technique. For learning the relationship between position errors and increased data from GNSS receivers without any prior experience, neural networks have become the machine learning option of choice in the past few years. Signal degradation is best measured by dilution of precision, elevation angles, and carrier-to-noise ratios. To estimate the position error of satellite-based navigation systems, neural networks are trained in this paper. This paper applies a long-short-term memory (LSTM) network to model the temporal correlation of position error measurements. Therefore, neural networks are capable of learning the trend of position errors through training. [ABSTRACT FROM AUTHOR]

Processing measurement data is an essential part of surveying engineering. One can list several methods in such a context: least squares estimation, M-estimation, R-estimation, etc. Some methods were developed by surveyors, e.g., the Danish method, IGG scheme, or Msplit estimation. The last method is, in fact, a class of estimation procedures dedicated to different problems. As a new approach to processing data, Msplit estimation is still being developed and improved. That paper concerns the local robustness of Msplit estimation and introduces a new Msplit estimation variant that is less sensitive to local outliers. Such a property seems important, especially in big data processing, such as observations from Light Detection and Ranging systems. The new variant modifies the squared Msplit estimation (SMS estimation) by implementing the adapted Tukey weight function, hence its acronym SMSTL estimation. The basic theoretical and empirical analyses, which were performed for the univariate model using, among others, the appropriate measures of robustness, confirmed the expected property of the method. The further tests, based on simulated as well as real data, show that the new method might overperform other Msplit estimation variants and classical methods for the chosen types of observation sets. [ABSTRACT FROM AUTHOR]

Analysis of huge data and detection of scintillation events by human visualization is expensive and time consuming process and also unfeasible in real time. In this paper, classical approaches namely Hard, Semi-Hard and Manual annotation rules are used for detection of the scintillations. For this, one week data is acquired from Septentrio PoLaRx5S GNSS scintillation monitoring Receiver corresponding to various constellations. Seven constellations namely GPS, GLONASS, Galileo, SBAS, BeiDou, QZSS and IRNSS-L5 signals during pre-sunset and post sunset hours are considered. The occurrence of scintillations due to pre-sunset and post sunset period by using hard and semi hard detection rules are analysed. It is observed that the occurrence of scintillations is more in post-sunset hours as compared to pre-sunset hours in all constellations. The performances of Semi Hard and Hard detection rules are compared with manual annotation by using confusion matrices statistical parameters namely accuracy, misclassification and precision. Identified scintillation signals coming from the least and worst affected directions. These results would be useful for early detection of scintillation without human inspection of scintillation events. [ABSTRACT FROM AUTHOR]

The Lombok earthquake in August 2018 triggered a sequential rupture with doublet earthquake up to Mw 6.9. This tectonic activity occurred near the main earthquake due to the decay of residual energy from one event to another. This activity is suspected to be a post-seismic deformation process such as afterslip and viscoelastic. In this paper, we conducted a study to determine the deformation pattern. Each of these processes can be investigated by extracting InSAR observational data. Time series from Sentinel-1 SAR is processed using LiCSBAS as data observation and then compare with the model based on exponential and logarithmic functions. The results of combined logarithmic and exponential fitting suggest the Lombok multi-event earthquakes were influenced by seismic activity from dual-releasing residual energy comprises of afterslip and viscoelastic as a dual mechanism with long duration rather than single mechanism. [ABSTRACT FROM AUTHOR]

This document is a guest editorial from the Journal of Applied Geodesy, discussing the topic of uncertainty and quality in multi-sensor systems. The editorial explains that multi-sensor systems, which combine different sensors, are commonly used in engineering geodesy and surveying. The document highlights four research papers that were presented at a scientific workshop on this topic, covering subjects such as improving the approximation quality of B-spline surfaces, developing GPS time-based reference trajectories for quality assessment, modeling systematic distance deviations in TLS measurements, and evaluating the uncertainty of a kinematic LiDAR-based multi-sensor system. The papers provide valuable insights into these areas of research and offer potential solutions for improving the accuracy and reliability of multi-sensor systems. [Extracted from the article]

Kinematic multi-sensor systems (MSS) describe their movements through six-degree-of-freedom trajectories, which are often evaluated primarily for accuracy. However, understanding their self-reported uncertainty is crucial, especially when operating in diverse environments like urban, industrial, or natural settings. This is important, so the following algorithms can provide correct and safe decisions, i.e. for autonomous driving. In the context of localization, light detection and ranging sensors (LiDARs) are widely applied for tasks such as generating, updating, and integrating information from maps supporting other sensors to estimate trajectories. However, popular low-cost LiDARs deviate from other geodetic sensors in their uncertainty modeling. This paper therefore demonstrates the uncertainty evaluation of a LiDAR-based MSS localizing itself using an inertial measurement unit (IMU) and matching LiDAR observations to a known map. The necessary steps for accomplishing the sensor data fusion in a novel Error State Kalman filter (ESKF) will be presented considering the influences of the sensor uncertainties and their combination. The results provide new insights into the impact of random and systematic deviations resulting from parameters and their uncertainties established in prior calibrations. The evaluation is done using the Mahalanobis distance to consider the deviations of the trajectory from the ground truth weighted by the self-reported uncertainty, and to evaluate the consistency in hypothesis testing. The evaluation is performed using a real data set obtained from an MSS consisting of a tactical grade IMU and a Velodyne Puck in combination with reference data by a Laser Tracker in a laboratory environment. The data set consists of measurements for calibrations and multiple kinematic experiments. In the first step, the data set is simulated based on the Laser Tracker measurements to provide a baseline for the results under assumed perfect corrections. In comparison, the results using a more realistic simulated data set and the real IMU and LiDAR measurements provide deviations about a factor of five higher leading to an inconsistent estimation. The results offer insights into the open challenges related to the assumptions for integrating low-cost LiDARs in MSSs. [ABSTRACT FROM AUTHOR]

The Operational Navigation with Indian Constellation (NavIC) comprises seven satellites in the orbit, including three in geostationary orbit (GEO) and four in geosynchronous orbit (GSO). NavIC provides both Standard Positioning Service and Restricted Service, using L5 (1176.45 MHz) and S1 (2492.028 MHz) frequencies, with coverage extending 1500 km around the mainland of India. In an urban canyon, multipath interference severely reduces the precision and reliability of NavIC positioning. Many current multipath mitigation techniques often exhibit high computational requirements or reliance on external assistance. In this paper, a ranging code tracking loop is proposed that can sustain either a late or early branch in contrast to the Narrow-Spacing (NS) correlation technique for mitigating multipath for NavIC receiver. The design of proposed code tracking loop is based on steepest descent algorithm. The findings demonstrate that, in terms of calculation time and code multipath mitigation, the suggested technique performs better than both Multipath Estimated Delay Locked Loop (MEDL) and NS correlation. The proposed method produces less than 0.016 chips for the tracking error Standard Deviation (STD). In addition, the recommended method takes 24 % less computation time. [ABSTRACT FROM AUTHOR]

The modeling and forecasting of Total Electron Content (TEC) play a major role in influencing signals from satellite-based navigation systems and impact the performance of diverse satellite-dependent technologies. The intensity of solar ionizing radiation and the state of geomagnetic field activity influence the Global Navigation Satellite System (GNSS)-TEC. This paper uses a Linear TEC Function (LTF) climatology model to understand ionospheric behavior under solar and geomagnetic activities that cause variations in the electron distribution of the ionosphere medium. The LTF model integrates representations of solar EUV photon (MgII) and geomagnetic (SYMH) activities, incorporating solar-modulated oscillations (periodic variations) at four seasonal cycles and a linear trend. The LTF model examined the time series of GPS-TEC at a location (geographic 34.95° N, 134.05° E) with a time resolution of 1 h, from 1997 to 2016, covering solar cycles 23 and 24. The Root Mean Square Deviation (RMSD) and correlation coefficient between the GNSS-TEC and model TEC (LTF) was 5.30 TECU and 95 %. The results indicate that solar components, as well as annual and semi-annual variations, have a significant impact on the daily average TEC. Solar activity appears to be the predominant determining factor of TEC during the solar phases of cycles 23 and 24. In contrast, periodic influences primarily outline TEC during periods characterized by minimal solar activity. The geomagnetic component presents an increased influence, particularly during storm periods. The model demonstrates superior performance in Total TEC modeling compared to other state-of-the-art approaches. [ABSTRACT FROM AUTHOR]

The GPS Aided Geo Augmented Navigation (GAGAN) system provides the navigational services for single-frequency GNSS user via broadcasting the differential corrections with GEO stationary satellites. The significant differential correction contribution comes from ionospheric time delays and is necessary to be determined precisely. Dual-frequency GPS receivers measure the ionospheric time delays using GPS code and carrier phase measurements. The determination of absolute ionospheric Total Electron Content (TEC) requires the calibration of GPS satellites and receiver hardware biases due to different frequency-dependent signals (L1 and L2) due to environmental changes (Temperature and Humidity). In this paper, A receiver-based Differential Code Biases (DCB) algorithm is implemented to derive a joint estimation of TEC and RDCB parameters using the weighted Least Square (WLS) method. The daily averaged DCBs data for 26 GPS receivers are obtained for 3 years (2014–2016) from 26 GPS reeivers over Indian region. The receiver DCB algorithmis validated with the Fitted Receiver Biases (FRB) method. The correlation (R) between VTEC and RDCB is conducted to investigate the RDCB stability. The results would be useful for the accurate determination of ionospheric differential corrections to GAGAN users. [ABSTRACT FROM AUTHOR]

The paper presents monitoring of spatial displacements and deformation of hydraulic structures of hydroelectric power plants of the Dnipro and Dnister cascades using permanent deformation monitoring systems (PDMS). The architecture of the geodetic (measuring) component of monitoring systems deployed at Kaniv, Dnipro, Seredniodniprovska and Dnister HPP (all in Ukraine) are presented, as well as deformation monitoring structure of this systems. Analysis of the impact of geodynamic and seismic factors on the operation of selected monitoring systems are presented. The spatial deformations of the base points on all the studied monitoring systems were determined. As a result of the analysis of the obtained values, it was found that the deformations of the dam crest have a seasonal nature (with half-annual period) of movements, and are characterized by the corresponding vector field and the absolute value of spatial movements. [ABSTRACT FROM AUTHOR]

Laser scanning is a wide-spread practice to capture the environment. Besides the fields of robotics and self-driving cars, it has been applied in the field of engineering geodesy for documentation and monitoring purposes for many years. The registration of scans is still one of the main sources of uncertainty in the final point cloud. This paper presents a new keypoint-based method for terrestrial laser scan (TLS) registration for high-accuracy applications. Based on detected 2D-keypoints, we introduce a new statistical matching approach that tests wheter keypoints, scanned from two scan stations, can be assumed to be identical. This approach avoids the use of keypoint descriptors for matching and also handles wide distances between different scanner stations. The presented approach requires a good coarse registration as initial input, which can be achieved for example by artificial laser scanning targets. By means of two evaluation data sets, we show that our keypoint-based registration leads to the smallest loop closure error when traversing several stations compared to target-based and ICP registrations. Due to the high number of observations compared to the target-based registration, the reliability of the our keypoint-based registration can be increased significantly and the precision of the registration can be increased by about 25 % on average. [ABSTRACT FROM AUTHOR]

Kinematic multi-sensor systems (MSS) are widely used for various applications, like mobile mapping or for autonomous systems. Depending on the application, insufficient knowledge of a system, like wrong assumptions about the accuracy of calibrations, might lead to inaccurate maps for mapping tasks or it might endanger humans in the context of autonomous driving. Uncertainty modeling can help to gain knowledge about the data captured by a system. Usually, uncertainty estimations for MSSs are done as backward modeling based on a comparison to reference datasets. In this paper, a forward modeling approach for the uncertainty modeling of a LiDAR-based kinematic MSS is chosen to estimate the uncertainty of an acquired point cloud. The MSS consists of a Leica Absolute Tracker and a platform with a 6-DoF sensor and Velodyne VLP-16 LiDAR. Results of multiple calibrations are used as the source for the uncertainty information for a Monte Carlo (MC) variance propagation of the point uncertainties. The deviations of the acquired point clouds in comparison to a ground truth can be decreased by an ensemble referencing process using the MC samples. Furthermore, the predicted uncertainties for the point clouds are well representing the actual deviations for reference panels closer to the system. Panels farther away indicate remaining distance depending effects. [ABSTRACT FROM AUTHOR]

Global Navigation Satellite Systems (GNSS) have become an integral part of modern life, supporting various applications, from precise positioning and navigation to timing and synchronization. However, GNSS signals are vulnerable to natural interferences including various atmospheric disturbances, with ionospheric scintillations being a significant challenge. Ionospheric scintillations, caused by irregularities in the Earth’s ionosphere, introduce rapid fluctuations in the amplitude and phase of GNSS signals. These fluctuations can severely degrade the accuracy and reliability of GNSS receivers, leading to positioning errors and navigation failures. Hence, it is crucial to develop effective mitigation strategies. One of the promising approaches to mitigate ionospheric scintillations is the utilization of Software Defined Radio (SDR) technology in GNSS receivers. SDR allows for real-time adaptation to changing signal conditions, enabling the receiver to detect scintillations and adjust its signal processing accordingly. This adaptability enhances the receiver’s stability against ionospheric disturbances, ensuring more robust and accurate positioning and navigation. In this paper, preliminary results of GNSS SDR (Make: iP-Solutions, Japan) installed at Koneru Lakshmaiah Education Foundation (KLEF), Vaddeswaram (Guntur) (16.44° N, 80.62° E) are presented. Amplitude scintillation index (S4) variations for different PRNs and subsequent positioning results are interpreted from April to September 2023. The results are compared and validated with those of the co-located Novatel GNSS receiver and NAVIC receiver. Most of the S4 variations correlate well with the S4 values from the Novatel and NAVIC receivers. S4 observations from the Septentrio receiver at Daytona Beach (Florida) are also presented. The results of SDR will be extended further for the development of scintillation mitigation algorithms. We plan to install an SDR and employ similar mitigation strategy at this location in the near future. [ABSTRACT FROM AUTHOR]

In order to study the coupling relationship between earthquakes and ionospheric disturbances, TEC data during the Mw 7.3 earthquake that occurred near Fukushima, Japan on March 16, 2022, were processed using global ionospheric data provided by the Center for Orbit Determination in Europe (CODE). In this paper, the sliding quartile interval method is used to eliminate solar activity in a 27-day window, including sunspot number (SSN), F10.7 cm radio flux (F10.7), total solar irradiation (TSI), solar wind velocity (Vsw) and geomagnetic activity. The impact of disturbance storm time index (DST) and global geomagnetic activity index (KP) on TEC anomaly disturbance can obtain more accurate TEC anomaly information. The results indicate that when the solar and geomagnetic activity cycles are inconsistent with the TEC anomalies on fifth day before the earthquake, the TEC anomalies above the epicenter are significantly greater than those observed in other regions, and the corresponding magnetic conjugate region is accompanied by anomalies, which is the characteristic of TEC anomalies caused by earthquakes. This means that the detected TEC anomalies can be used as a potential ionospheric precursors, indicating that the Fukushima earthquake is imminent. [ABSTRACT FROM AUTHOR]

The paper presents the analysis of single-point GPS positioning results obtained from smartphones, using code observations on the L1 and L5 frequencies. In this research we used two Huawei P30 Pro mobile phones and one geodetic receiver (Javad Alpha) acting as the reference receiver. Smartphones were placed at an equal distance of 0.5 m from this receiver. Such a close distance was specially planned by the authors in order to achieve identical observation conditions. Thus, it was possible to compare the accuracy of GPS positioning using pseudoranges on the L1 and L5 frequencies for individual observation epochs. The analysis was carried out from static GPS positioning, using the results from the open-source RTKLib software. In general, the usefulness of code measurements on the L5 frequency to determine the GPS position made it possible to increase the accuracy by several times with respect to the positions determined using the C/A code on the L1 frequency. Average errors of horizontal and vertical coordinates were about 70 % lower for the GPS solution using the L5 code observations than using the L1 code observations. Based on statistical analysis, a horizontal accuracy of about 0.45 m and vertical accuracy of about 1.8 m (STDEV) with only five GPS satellites may be obtained using a smartphone with L5 code observations. [ABSTRACT FROM AUTHOR]

The demand for real-time high-precision positioning for global navigation satellite system applications is difficult to satisfy. In this regard, a single-frequency receiver is found to play an important role in overcoming this challenge, especially in developing countries where economic factors are a major restriction. Hence, the development of built-in models, such as the Klobuchar model, is an important objective for single-frequency users to mitigate the effect of ionospheric delay errors in real-time applications. Accordingly, this study aims to devise a new approach to enhance the behavior of the Klobuchar model and increase its efficiency in resolving the aforementioned problem. The new approach seeks to enhance the behavior of the Klobuchar model without refining or increasing its coefficients. To eliminate the ionospheric delay disturbance, the proposed methodology applies normalization and filtration processes to the raw ionospheric delay probability distribution estimated by the unified least squares technique. A final assessment of the new method for enhancing the Klobuchar behavior in predicting the precise position of a single-frequency static receiver under different weather conditions around the globe is presented in this paper. [ABSTRACT FROM AUTHOR]

Global navigation satellite systems (GNSS) are used to provide position estimation to the users. These navigation systems must meet the required navigation parameters (RNP) parameters. Among them integrity being the important parameter, defined as a navigation system's honesty of the information provided to the user by satellites. The extremity of error due to clocks, ephemeris etc., broadcasted in navigation message of NavIC will result in inaccurate information provided by the satellites that tamper the Navigation with Indian constellation (NavIC) system integrity. The information provided by the satellites may be faulty due to various error sources and cannot be used for applications which require very high accuracy. Integrity of the information provided by satellites plays a vital role and the system needs to be notified accordingly. The traditional methods receiver autonomous integrity monitoring (RAIM) algorithms require both navigation and observation data for implementation and involves several computations, hence in this paper an efficient approach considering only navigation message is proposed to monitor the integrity of NavIC. The NavIC Navigation data of 28 days data corresponding to 4 months is collected from IGS website. The integrity check is performed considering the satellite's User Range Accuracy Upper Bound (URA UB), fit interval and health parameters from navigation message. It is observed from the results that there are specific instances of integrity failure of NavIC system. However, it is also noticed that 99.5 % of times the integrity provided by NavIC is within specified limits that guarantee the NavIC utility for critical applications. [ABSTRACT FROM AUTHOR]

The interaction between laser beams and backscattering object surfaces lies at the fundamental working principle of any Terrestrial Laser Scanning (TLS) system. Optical properties of surfaces such as concrete, metals, wood, etc., which are commonly encountered in structural health monitoring of buildings and structures, constitute an important category of systematic and random TLS errors. This paper presents an approach for considering the random errors caused by object surfaces. Two surface properties are considered: roughness and reflectance. The effects on TLS measurements are modeled stepwise in form of a so-called synthetic variance-covariance matrix (SVCM) based on the elementary error theory. A line of work is continued for the TLS stochastic model by introducing a new approach for determining variances and covariances in the SVCM. Real measurements of cast stone façade elements of a tall building are used to validate this approach and show that the quality of the estimation can be improved with the appropriate SVCM. [ABSTRACT FROM AUTHOR]