Showing papers on "GNSS augmentation published in 2023"

Detecting Maritime GPS Spoofing Attacks Based on NMEA Sentence Integrity Monitoring

Abstract: Today’s maritime transportation relies on global navigation satellite systems (GNSSs) for accurate navigation. The high-precision GNSS receivers on board modern vessels are often considered trustworthy. However, due to technological advances and malicious activities, this assumption is no longer always true. Numerous incidents of tampered GNSS signals have been reported. Furthermore, researchers have demonstrated that manipulations can be carried out even with inexpensive hardware and little expert knowledge, lowering the barrier for malicious attacks with far-reaching consequences. Hence, exclusive trust in GNSS is misplaced, and methods for reliable detection are urgently needed. However, many of the proposed solutions require expensive replacement of existing hardware. In this paper, therefore, we present MAritime Nmea-based Anomaly detection (MANA), a novel low-cost framework for GPS spoofing detection. MANA monitors NMEA-0183 data and advantageously combines several software-based methods. Using simulations supported by real-world experiments that generate an extensive dataset, we investigate our approach and finally evaluate its effectiveness.

Monitoring nonlinear and fast deformation caused by underground mining exploitation using multi-temporal Sentinel-1 radar interferometry and corner reflectors: application, validation and processing obstacles

Abstract: In this study, Differential Interferometric Synthetic Aperture Radar Interferometry (DInSAR) of artificial Corner Reflectors (CRs) were validated in the area of fast and nonlinear deformation gradient caused by active coal longwall exploitation. Three Sentinel-1 datasets were processed using conventional DInSAR, Persistent Scatterer Interferometry (PSI), and Small BAseline Subset methods implemented in ENVI SARscape™. For evaluation, leveling and Global Navigation Satellite System (GNSS) measurements were used. Considering the challenge of snow cover, the removal of all winter images was not a successful strategy due to the long temporal baseline and strong movement, which cause phase unwrapping problems and underestimate the real deformation. The results indicate that only conventional DInSAR and SBAS with low network redundancy allow us to capture maximal deformation gradient and the root mean square error calculated between the CRs and the ground truth is on the level of 2–3 cm for the vertical and easting deformation component, respectively. For the small deformation gradient represented by the permanent GNSS station (4 cm/year), all SBAS techniques appeared to be more accurate than DInSAR, which corresponds to higher redundancy and better removal of the atmospheric signal. In contrast, DInSAR results allowed to capture information about two subsidence basins, which was not possible with SBAS and PSI approaches.

A ConvLSTM Neural Network Model for Spatiotemporal Prediction of Mining Area Surface Deformation Based on SBAS-InSAR Monitoring Data

Abstract: The surface deformation caused by underground mining leads to damage to surface buildings and brings potential safety hazards and property losses. The demand for reliable prediction methods of surface deformation in mining areas is becoming increasingly significant. At present, most prediction methods are based on sampling points; however, these methods neglect to consider local and overall spatial features, and this oversight affects the spatial accuracy of prediction results. The data form of the prediction output is often discontinuous and not intuitive. In order to solve this problem, the spatiotemporal prediction method of surface deformation in mining areas is a very effective proposal. However, few scholars have proposed a solution based on this idea. In this study, a convolution long short-term memory (ConvLSTM) neural network for surface deformation spatiotemporal prediction based on time-series interferometric synthetic aperture radar (InSAR) is proposed to directly predict the overall spatial deformation of the surface in the mining area. First, based on Sentinel-1A images of the Jinchuan Mining Area, Jinchang, Gansu province, China, the time-series InSAR surface deformation data of the study area from January 2018 to October 2020 (81 scenes) are obtained using small baseline subset InSAR (SBAS-InSAR) technology. Because of the large value scale of surface deformation in the mining area, we propose a method to fit the maximum and minimum values of time-series deformation, respectively, and carry out piecewise numerical compression. Then, based on the ConvLSTM neural network layer, construct the spatiotemporal prediction model of time-series InSAR surface deformation. Support vector regression (SVR), multilayer perceptron (MLP) regression, and the gray model [GM (1,1)] are used as benchmark methods. The prediction results of our models are compared with the three benchmark methods. The comparison results show that the prediction effect of the ConvLSTM model with optimal input time steps is significantly better than the benchmark methods in the comprehensive performance of various evaluation metrics, especially for the metrics used to evaluate the error. This shows that the ConvLSTM model has relatively fine spatiotemporal prediction performance for time-series InSAR surface deformation. Based on the InSAR time-series deformation monitoring results of the Jinchuan Mining Area, we carry out the spatiotemporal prediction of surface deformation in the subsequent 50 time steps (600 days). The results agree with the natural deformation development law in band collection statistics and 3-D representation of deformation; moreover, the reliability of numerical spatial distribution is relatively high. This result can be used to intuitively evaluate the overall surface deformation of the mining area in the monitoring range, find potential hazards in time, and take measures to address these hazards quickly. At the same time, this research process also provides a new concept design for such problems.

Improving the Position Accuracy of Rover Receiver using Differential Positioning in Indian Regional Navigation Satellite System

Abstract: Navigation with Indian Constellation (NavIC) is the Indian Regional Navigation Satellite System (IRNSS) developed by Indian Space Research Organization (ISRO) to provide the position and navigation services for Indian region. NavIC or IRNSS is individual satellite constellation which has seven satellites covering the Indian subcontinent. Accuracy of NavIC standalone is insufficient in certain applications such as civil aviation. To improve the position accuracy performance of NavIC system, differential positioning technique is utilized. In this paper, differential positioning is carried out, considering two IGS (IRNSS-GPS-SBAS) receivers (one as reference station and the other as rover), which are capable of receiving IRNSS signals from 7 satellites, GPS signals from 12 satellites, SBAS signals from 2 satellites. Here, NavIC constellation alone is considered for the analysis. The differential positioning is carried out using the pseudorange measurements on L5 (1176.45 MHz), S1 (2492.028 MHz) and dual (L5 and S1 both) and accuracies are compared in terms of the statistical parameters Circular Error Probability (CEP), Distance Root Mean Square (DRMS), 2DRMS (twice the DRMS). The improvement in the horizontal accuracy (2DRMS) of the rover using pseudorange measurements on L5 is observed to be 78.81%, on S1 it is 69.14 % and using dual frequency (L5 and S1 both) it is 80.73% when compared to NavIC standalone.

Mapping of Mean Deformation Rates Based on APS-Corrected InSAR Data Using Unsupervised Clustering Algorithms

Abstract: Different interferometric approaches have been developed over the past few decades to process SAR data and recover surface deformation, and each approach has advantages and limitations. Finding an accurate and reliable interval for preparing mean deformation rate maps (MDRMs) remains challenging. The primary purpose of this paper is to implement an application consisting of three unsupervised clustering algorithms (UCAs) for determining the best interval from SAR-derived deformation data, which can be used to interpret long-term deformation processes, such as subsidence, and identify displacement patterns. Considering Port Harcourt (in the Niger Delta) as the study area, it was essential to remove the sources of error in extracting deformation signals from SAR data, spatially ionospheric and tropospheric delays, before using UCAs to obtain its characteristics and real deformation data. Moreover, another purpose of this paper is to implement the advanced integration method (AIM) for atmospheric phase screen (APS) correction to enhance deformation signals obtained through different SAR processing approaches, including interferometric SARs (two-pass interferometry, InSAR) and multitemporal interferometry SARs (n-pass interferometry, DInSAR; permanent scatterer interferometry (PSI); and small baseline subset (SBAS)). Two methods were chosen to evaluate and find the best technique with which to create an MDRM: The first one was to compare the signals corrected by the AIM and the vertical component of the GPS station, which showed the AIM providing 58%, 42%, and 28% of the matching with GNSS station outputs for InSAR, PSI, and SBAS, respectively. Secondly, similarity measures and Davies–Bouldin index scores were implemented to find an accurate and reliable interval in which the SBAS technique with the unsupervised K-medians method has been chosen. Based on GNSS vertical deformation in a 500 m radius around the station, the SBAS K-medians technique expressed up to 5.5% better deformation patterns than the map of SAR processing techniques.

Satellite Navigation Signal Authentication in GNSS: A Survey on Technology Evolution, Status, and Perspective for BDS

Abstract: As the Global Navigation Satellite System (GNSS) is widely used in all walks of life, the signal structure of satellite navigation is open, and the vulnerability to spoofing attacks is also becoming increasingly prominent, which will seriously affect the credibility of navigation, positioning, and timing (PNT) services. Satellite navigation signal authentication technology is an emerging technical means of improving civil signal anti-spoofing on the satellite navigation system side, and it is also an important development direction and research focus of the GNSS. China plans to carry out the design and development of the next-generation Beidou navigation satellite system (BDS), and one of its core goals is to provide more secure and credible PNT services. This paper first expounds on the principles and technical architecture of satellite navigation signal authentication, then clarifies the development history of satellite navigation signal authentication, and finally proposes the BDS authentication service system architecture. It will provide technical support for the construction and development of the follow-up Beidou authentication service.

Rail Digital Map Construction on GNSS Denied Areas

Abstract: A Digital Map of the rail infrastructure in a key element to support the adoption of GNSS in railway signalling and satisfy the strict accuracy and integrity requirements even in the presence of feared events that may hinder the positioning solution. In this work, we tackle the issue of providing an accurate rail Digital Map for localization purposes, bridging the gaps produced by the loss of Global Navigation Satellite System (GNSS) coverage using forward and backward post-processing of inertial navigation. Experimental results show that the proposed method is able to increase the accuracy of the resulting Digital Map.

Investigating ground deformation due to a series of collapse earthquakes by means of the PS-InSAR technique and Sentinel 1 data in Kandy, Sri Lanka

Abstract: Time series interferometry synthetic aperture radar (InSAR) techniques have rarely been applied to detect displacement due to low-magnitude (5.5 ≥ M) earthquakes. This study exploits the combined permanent scatterer (PS) interferometry (PS-InSAR) and differential interferometry (D-InSAR) methods to investigate the deformation rates due to low-magnitude partial series of collapse earthquakes. Kandy, the hill capital of Sri Lanka, was experiencing a series of collapsed earthquakes. Historical geological evidence of dynamic topography with prolonged vertical movement further promotes the initiatory InSAR investigation. A series of Sentinel 1A images from the years 2019 to 2021 were employed. Initial D-InSAR near-zero baseline analysis suggested possible displacement in the range of −10 mm / year and +2 mm / year for subsidence and uplift, respectively. Using these prior motion velocities, the temporal coherence was optimized in PS-InSAR. Variogram models and ordinary Kriging (OK) were employed to predict deformation for the areas with limited PS detection. Descending orbits images PS show a dominant uplift of +20 mm / year, which are concentrated over Kandy urban areas. Movements along the ascending line of sight at Victoria Dam in the south are in the range of −40 mm / year. Slopes along the Mahaweli river lineament to the east show subsidence in the range of −29 to 36 mm / year. The coregistered landslide hazard map of Kandy shows deformation areas are exposed to landslide risk. Changes in terrestrial and ground water levels measured with the gravity recovery and climate experiment/GRACE-Follow-On during the period reveal significant irregularities. The study can be considered a prototype example that can be extended to investigate low-magnitude incomplete collapse earthquakes in different geological and geotechnical setups for ground deformation.

SBAS-InSAR based validated landslide susceptibility mapping along the Karakoram Highway: a case study of Gilgit-Baltistan, Pakistan

Abstract: Abstract Geological settings of the Karakoram Highway (KKH) increase the risk of natural disasters, threatening its regular operations. Predicting landslides along the KKH is challenging due to limitations in techniques, a challenging environment, and data availability issues. This study uses machine learning (ML) models and a landslide inventory to evaluate the relationship between landslide events and their causative factors. For this, Extreme Gradient Boosting (XGBoost), Random Forest (RF), Artificial Neural Network (ANN), Naive Bayes (NB), and K Nearest Neighbor (KNN) models were used. A total of 303 landslide points were used to create an inventory, with 70% for training and 30% for testing. Susceptibility mapping used Fourteen landslide causative factors. The area under the curve (AUC) of a receiver operating characteristic (ROC) is employed to compare the accuracy of the models. The deformation of generated models in susceptible regions was evaluated using SBAS-InSAR (Small-Baseline subset-Interferometric Synthetic Aperture Radar) technique. The sensitive regions of the models showed elevated line-of-sight (LOS) deformation velocity. The XGBoost technique produces a superior Landslide Susceptibility map (LSM) for the region with the integration of SBAS-InSAR findings. This improved LSM offers predictive modeling for disaster mitigation and gives a theoretical direction for the regular management of KKH.

Early Identification and Influencing Factors Analysis of Active Landslides in Mountainous Areas of Southwest China Using SBAS−InSAR

Abstract: Potential landslides in the mountainous areas of southwest China pose a serious threat to the lives and property of local residents. Synthetic aperture radar interferometry (InSAR) technology has the advantages of wide coverage, all weather applicability, and low cost and can quickly and accurately identify large range of active landslides, making it a useful geodetic tool for the early identification and prevention of landslides. This paper employed small baseline subset InSAR (SBAS−InSAR) technology and ascending and descending Sentinel−1 data from January 2019 to December 2021 to early identify active landslides in the Maoxian County to Li County National Highway (G317 and G213). The InSAR deformation results were verified by geometric distortion analysis, optical remote sensing interpretation, and field investigation, and 115 active landslides were successfully determined, among which 23 active landslides were identified by ascending and descending Sentinel−1 data together. In addition, InSAR deformation results show that fault, stratigraphic lithology, and rainfall are the three main factors that accelerate the deformation of active landslides and can trigger new active landslides. This study can provide an important reference for the early identification and prevention of landslides in mountainous areas.

GNSS/IMU Sensor Fusion Performance Comparison of a Car Localization in Urban Environment Using Extended Kalman Filter

Abstract: Global Navigation Satellite System (GNSS) and Inertial Measurement Unit (IMU) are popular navigation sensor for position fixing technique and dead reckoning system that complement each other. GNSS can provide accurate position and velocity information when it establishes a Line of Sight (LOS) with a minimum of four satellites. However, this accuracy can decrease due to signal outage, jamming, interference, and multipath effects. On the other hand, the IMU has the advantage of measuring the platform’s orientation with a high-frequency update and is not affected by environmental conditions. However, a drift effect causes the measurement errors to accumulate. Several studies have demonstrated the fusion of both sensors in terms of the Extended Kalman Filter (EKF). This study conduct sensor fusion for car localization in an urban environment based on the loosely coupled integration scheme. In order to improve the sensor fusion performance, pre-processing GNSS and IMU data were applied. The result shows that pre-processing DGNSS and IMU filtering can increase the accuracy of the integrated navigation solution up to 80.02% in the east, 80.13% in the north, and 89.45% in the up direction during the free outage period.

Cooperative Smartphone GNSS/PDR for Pedestrian Navigation

Abstract: Pedestrian navigation using smartphone built-in sensors attracted wide attention with the booming Location-based Service (LBS). Pedestrian Dead Reckoning (PDR) and Global Navigation Satellite Navigation (GNSS) integration is recognized as a reliable solution for smartphone-based pedestrian navigation. However, GNSS is vulnerable under some conditions. Multi-path, None-Line-Of-Sight (NLOS), and signal blockage all pose negative impacts on GNSS position accuracy. PDR position errors increase with the pedestrian walking distance without GNSS. Aiming at improving the smartphone-based pedestrian position accuracy under GNSS signal challenging conditions, in this brief, we propose a cooperative PDR/GNSS integration method with Factor Graph Optimization (FGO). A factor graph is constructed to represent the relationship between the multiple agents’ states, measurements and inter-ranging information. Optimal estimation is realized considering all the historical measurements and inter-ranging measurements between these agents. Field tests were carried out to assess the performance of the proposed cooperative navigation method. Results manifest that the proposed method can improve the position accuracy especially under the GNSS signals challenging conditions.

Landslide Monitoring along the Dadu River in Sichuan Based on Sentinel-1 Multi-Temporal InSAR

Abstract: The Dadu River travels in the mountainous areas of southwestern China, one of regions with the most hazards that has long suffered from frequent geohazards. The early identification of landslides in this region is urgently needed, especially after the recent Luding earthquake (MS 6.8). While conventional ground-based monitoring techniques are limited by the complex terrain conditions in these alpine valley regions, space interferometric synthetic aperture radar (InSAR) provides an incomparable advantage in obtaining surface deformation with high precision and over a wide area, which is very useful for long-term and slow geohazard monitoring. In this study, more than 500 Sentinel-1 SAR images with four frames acquired during 2017~2022 were collected to detect the hidden landslide regions from the Jinchuan to Ebian Section along the Dadu River, based on joint-scatterer InSAR (JS-InSAR) and small baseline subset (SBAS) techniques. The results showed that our method could be successfully applied for landslide monitoring in complex mountainous regions. Furthermore, 143 potential landslide regions spreading over an 800 km area along the Dadu River were extracted by integrating the deformation measurements and optical images. Our study can provide a reference for large-scale geological hazard surveys in mountainous areas, and the InSAR technique will be encouraged for the local government in future long-term monitoring applications in the Dadu River Basin.

Probabilistic Detection of GNSS Spoofing using Opportunistic Information

Abstract: Global Navigation Satellite Systems (GNSS) are integrated into many devices. However, civilian GNSS signals are usually not cryptographically protected. This makes attacks that forge signals relatively easy. Considering modern devices often have network connections and on-board sensors, the proposed here Probabilistic Detection of GNSS Spoofing (PDS) scheme is based on such opportunistic information. PDS has at its core two parts. First, a regression problem with motion model constraints, which equalizes the noise of all locations considering the motion model of the device. Second, a Gaussian process, that analyzes statistical properties of location data to construct uncertainty. Then, a likelihood function, that fuses the two parts, as a basis for a Neyman-Pearson lemma (NPL)-based detection strategy. Our experimental evaluation shows a performance gain over the state-of-the-art, in terms of attack detection effectiveness.

Legal Aspects of European Satellite Navigation Systems in a Time of Change

Abstract: Global Navigation Satellite System (GNSS) is an important tool in supporting innovation and developing the economy. The European Union has created two systems: Galileo and EGNOS (European Geostationary Navigation Overlay Service), which enable the localisation of points on the Earth’s surface and in the sky. The GNSS programme offers a range of opportunities for Central and Eastern European societies in which the existence of the E-GNNS (European Global Navigation Satellite System) is still not well known. The article is an attempt to raise awareness of the use of Galileo and EGNOS systems, as well as to present the legal framework concerning this programme and the changes introduced by Regulation (EU) 2021/696 of the European Parliament and of the Council of 28 April 2021. The main research goal is assessing changes in the most crucial areas of this regulation, such as security of the systems, access of third parties, compliance of the provisions with human rights standards, and issues related to budgetary implications which are particularly important for the continuity and stability of E-GNNS.

Performance of Low-cost GNSS/INS Receivers and Smartphone GNSS Positioning in Pedestrian Applications

Abstract: In recent years, there has been a significant advancement in the field of Global Navigation Satellite Systems (GNSS). The completion of newly built systems (Galileo, BeiDou) together with the modernisation of long-standing systems (GPS, GLONASS) has brought new signals and also new services to users. A significant technological advance has also been achieved in the development and availability of low-cost devices enabling positioning and navigation based on GNSS alone or a combination of several technologies. The study focuses on testing GNSS receivers in smartphones and low-cost devices combining GNSS and inertial navigation. The aim was to address the current capabilities and the quality of positioning offered by these devices. The analyses were performed on test measurements performed in kinematic mode in an urban environment at walking speed. The aim was to make test measurements that are representative enough to reflect conditions commonly encountered in life. Advanced GNSS techniques were tested in both real-time and post-processing of the raw observations. Low-cost u-blox single and multi-frequency modules combining GNSS and inertial localization, as well as standard Samsung mobile phones were used. Impact of the GNSS (multi-)constellation on the quality of positioning was also evaluated, as some GNSS signals exhibit higher multipath resistance and a higher number of satellites can significantly help with positioning initialization and improve its accuracy.

High-Accuracy Absolute-Position-Aided Code Phase Tracking Based on RTK/INS Deep Integration in Challenging Static Scenarios

Abstract: Many multi-sensor navigation systems urgently demand accurate positioning initialization from global navigation satellite systems (GNSSs) in challenging static scenarios. However, ground blockages against line-of-sight (LOS) signal reception make it difficult for GNSS users. Steering local codes in GNSS basebands is a desirable way to correct instantaneous signal phase misalignment, efficiently gathering useful signal power and increasing positioning accuracy. Inertial navigation systems (INSs) have been used as effective complementary dead reckoning (DR) sensors for GNSS receivers in kinematic scenarios, resisting various forms of interference. However, little work has focused on whether INSs can improve GNSS receivers in static scenarios. Thus, this paper proposes an enhanced navigation system deeply integrated with low-cost INS solutions and GNSS high-accuracy carrier-based positioning. First, an absolute code phase is predicted from base station information and integrated solutions of the INS DR and real-time kinematic (RTK) results through an extended Kalman filter (EKF). Then, a numerically controlled oscillator (NCO) leverages the predicted code phase to improve the alignment between instantaneous local code phases and received ones. The proposed algorithm is realized in a vector-tracking GNSS software-defined radio (SDR). Results of the time-of-arrival (TOA) and positioning based on real-world experiments demonstrated the proposed SDR.

A Hybrid RISS/GNSS Method During GNSS Outage in the Land Vehicle Navigation System

Abstract: The integrated navigation system of an inertial navigation system (INS) and a global navigation satellite system (GNSS) is a standard solution in land vehicle navigation applications. Considering a low-cost solution, the reduced inertial sensor system (RISS) is adopted in place of INS to provide better navigation performance for land vehicles with fewer inertial sensors and lower computations. However, low-cost sensors can quickly deteriorate the navigation solution during GNSS outage. Hence, a novel RISS /GNSS method with the assistance of the long short-term memory (LSTM) neural network (NN), which has the ability of adaptive memorizing, is proposed to bridge GNSS outage by means of data fusion. In addition, zero-velocity detection is applied to advance the navigation performance provided by the LSTM algorithm during GNSS outage. We examined the performance of this method by using real road test experiments in a land vehicle equipped with GNSS receivers and inertial sensors in addition to a high-end GNSS /INS to provide the reference solution. During 300-s GNSS outage, the experimental results illustrate that this hybrid method based on the LSTM algorithm can enhance the navigation accuracy by 50% when compared with the standalone RISS algorithm, and provide 30% improvements in comparison with the nonlinear autoregressive with exogenous input (NARX) algorithm.

Multi-GNSS simulation and its positioning performance for static and dynamic users

Abstract: Global navigation satellite system plays an important role in military and civil fields, providing global positioning, navigation and timing services in real time. Unfortunately, the services provided by single constellation or double constellations cannot meet the requirements of high-level navigation, and there are still some problems such as low positioning accuracy and low number of visible satellites at specific circumstances to be solved. In this paper, multi-GNSSs are constructed and their global positioning performance is analyzed with respect to static and dynamic users. Results show that with more constellations, the position dilution of precision is decreased, and the number of visible satellites and the positioning accuracy are improved, which reveals that compared with single constellation or double constellations, multi-GNSSs can obviously improve the positioning performance. The methodology proposed can serve as a technical reference for national integrated PNT systems.

Performance Analysis and Quantification of BeiDou Navigation Satellite System (BDS-3)

Abstract: Positioning, Navigation, and Timing (PNT) information play a vital role in everyday life of common persons. People greatly rely on Global Navigation Satellite System (GNSS)-enabled applications for navigation to reach their desired destination. However, GNSS navigation performance is highly degraded in urban environments due to the high probability of signal interruption, multipath (MP), and/or non-line-of-sight (NLOS) signal reception. Multipath and NLOS being the major causes of disrupted positioning performance for GNSS in urban environments. The navigation signals encountered various environmental factors they are reflected, refracted, diffracted, and completely blocked by high-roof buildings, bridges, and trees, thus leading to severe uncertainties in position estimation. GNSS system has gained notable advancements in terms of number of satellites, satellite geometry and signal quality. In this paper newly established constellation BeiDou Navigation Satellite System (BDS-3) performance is quantified with respect to environmental changes and compared in terms of positional accuracy. The paper also discussed the innovative current developments and status of BDS-3 in 2023. For this reason, series of field experiments were carried out at clear open and urban environment with BDS-3 and GPS mode during the observation time of 6 hours. The BDS-3 system is configured for data logging and used for the first time at Pakistan region. The positioning and navigation performance of BDS-3 is evaluated by utilizing key performance indicators e.g satellite availability, geometric distribution in terms of PDOP, and statistical accuracy measures (i.e., Circular Error Probable (CEP) and Distance Root Mean Square (DRMS)). The experimental results shows that BDS-3 provides more number of satellites, favorable satellite geometry and reduced position error compared to GPS constellation in clear open sky environment. In urban environment it is observed that BDS-3 performance is reduced/dropped due to obstructions that leads to increase the positioning inaccuracies. It is comprehended that BDS-3 system performance is less affected in urban site in terms of satellite availability, PDOP and position error as compared to GPS system. The statistical positional accuracy for BDS-3 and GPS found to be similar at clear open sky environment. BDS is more resilient to environmental factors.

An GNSS/INS Integrated Navigation Algorithm Based on PSO-LSTM in Satellite Rejection

Abstract: When the satellite signal is lost or interfered with, the traditional GNSS (Global Navigation Satellite System)/INS (Inertial Navigation System) integrated navigation will degenerate into INS, which results in the decrease in navigation accuracy. To solve these problems, this paper mainly established the PSO (particle swarm optimization) -LSTM (Long Short-Term Memory) neural network model to predict the increment of GNSS position under the condition of satellite rejection and accumulation to obtain the pseudo-GNSS signal. The signal is used to compensate for the observed value in the integrated system. The model takes the advantages of LSTM, which is good at processing time series, and uses PSO to obtain the optimal value of important hyperparameters efficiently. Meanwhile, the improved threshold function is used to denoise the IMU (inertial measurement unit) data, which improves the SNR (signal-to-noise ratio) of IMU outputs effectively. Finally, the performance of the algorithm is proved by actual road test. Compared with INS, the method can reduce the maximum errors of latitude and longitude by at least 98.78% and 99.10% while the satellite is lost for 60 s, effectively improving the accuracy of the GNSS/INS system in satellite rejection.

Analysis of the impact of GNSS disruptions on aircraft operations at Romanian airports

Abstract: In the transition towards space-based air navigation, the reliance on Global Navigation Satellite Systems (GNSS) is increasing. However, GNSS disruptions and interference can cause GPS loss in the cockpit. The purpose of this paper is to assess the impact of GNSS vulnerabilities, especially interference, on aircraft operations. The data used for this analysis was collected by GNSS monitoring stations installed at two Romanian airports, specifically selected due to their proximity to possible interference sources. In order to obtain relevant results, the entire assessment is based on the scenario in which all the flights at the airport are using GNSS as their primary means of navigation. Therefore, the flights that could have possibly been affected were identified and the operational impact of interference was assessed. This study emphasises the importance of GNSS monitoring at airports in order to reduce the negative effects of GNSS disruptions on the safe and efficient operations of aircraft.

Optical Technologies for Future Global Navigation Satellite Systems

Abstract: Accurate, robust and reliable positioning and timing has become crucial for a wide spectrum of applications. New technologies will further improve the services offered by Global Navigation Satellite Systems (GNSSs). Optical technologies are promising candidates to achieve significant improvements in terms of accuracy, robustness and reliability of GNSSs in near future. First and foremost, optical inter-satellite links (OISLs) and optical clock technologies show enormous potential for future applications at the core of next generation GNSS architectures. Both technologies can be implemented independently from each other in current GNSS as the development lines may differ, in particular in terms of technology readiness. We will present different tracks on how optical key technologies could potentially be integrated in next generations of GNSS, and assess the corresponding improvements.

Integrity of SBAS before Reception of Message Type 28

Abstract: 衛星航法システムに対する補強情報を送信する補強システムとして，静止衛星を使用するSBAS（Satellite-Based Augmentation System）が標準規格となっている．SBASが送信する補強情報にはユーザ位置に応じて適切に測距精度を見積もるためのクロック－エフェメリス共分散行列がメッセージタイプ28として含まれているが，このメッセージは当初のSBAS規格では規定されていなかった．メッセージタイプ28を含まない当初規格に対する後方互換性を確保するために，現在のSBAS規格ではメッセージタイプ28を受信しない場合の動作が規定されている．このため，メッセージタイプ28の受信前であってもユーザ受信機はメッセージタイプ28を使用せずに動作でき，メッセージタイプ28の存在を前提として完全性パラメータが生成されている場合には所要の完全性が確保されないことがあり得る．MSASを対象としてこのような動作をする可能性を調査したところ，実際にそのようなタイミングがわずかながら（約0.14%）あることを確認したので，回避策とともに報告する．

Doppler Positioning of Dynamic Targets with Unknown LEO Satellite Signals

Abstract: A new concept of global navigation based on Doppler measurements from a large low Earth orbit (LEO) constellation is investigated that has potential to serve as a complement or backup to global navigation satellite systems (GNSSs) to provide navigation and positioning services in GNSS denial environments. In this work, we investigate the potential of LEO communication satellite opportunity signals in dynamic navigation, establish LEO satellite Doppler positioning equations, derive the main error sources affecting the Doppler positioning results of a dynamic target, and analyze the impact of each error source on positioning accuracy through a simulation. The results show that the orbit error and clock drift had a large impact on positioning accuracy. This navigation scheme would be more competitive if it could provide high-precision satellite orbits and accurate Doppler measurements. The obtained results show that the LEO satellite signals used as navigation opportunity signals are an attractive alternative in GNSS rejection environments for high dynamic targets.

การประเมินค่าความถูกต้องทางตำแหน่งโดยใช้ค่าแก้จากระบบดาวเทียม sbas ร่วมกับการรังวัดด้วยระบบดาวเทียม gps สำหรับการประมวลผลการรังวัดตำแหน่งแบบจุดเดี่ยวในพื้นที่ประเทศไทย

Abstract: Satellite Based Augmentation System (SBAS) เป็นระบบเสริมดาวเทียมที่ให้บริการค่าแก้สำหรับดาวเทียม GNSS ซึ่งครอบคุมพื้นที่บริการเป็นบริเวณกว้างและมีการพัฒนาในประเทศต่างๆทั่วโลก เนื่องจากประเทศไทยไม่ได้อยู่ในพื้นที่บริการแต่ก็รับสัญญาณจากระบบดาวเทียม SBAS ได้ ดังนั้นงานวิจัยนี้จึงมุ่งเน้นศึกษาการประเมินค่าความถูกต้องทางตำแหน่งโดยการใช้ค่าแก้จากระบบดาวเทียม SBAS ประมวลผลร่วมกับข้อมูลรังวัดด้วยดาวเทียมนำหน GPS สำหรับการประมวลผลการรังวัดตำแหน่งแบบจุดเดี่ยวในพื้นที่ประเทศไทย โดยใช้ข้อมูลจากสถานีรับสัญญาณดาวเทียมอ้างอิงถาวร (Continuously Operating Reference Stations: CORS) จากกรมแผนที่ทหาร จำนวน 40 สถานี ในช่วงเดือนกันยายน 2562, เดือนธันวาคม 2562 และเดือนเมษายน 2563 และข้อมูลค่าแก้จากระบบดาวเทียม SBAS ที่ครอบคลุมประเทศไทยโดยใช้ข้อมูลรังวัดด้วยระบบดาวเทียมนำหน GPS ประมวลผลด้วยวิธีการประมวลผลจุดเดี่ยวความละเอียดสูง (Precise Point Positioning: PPP) เป็นค่าพิกัดอ้างอิงเพื่อใช้เปรียบเทียบกับการประมวลผลค่าพิกัดจากข้อมูลรังวัดด้วยระบบดาวเทียมนำหน GPS เพียงอย่างเดียว ด้วยวิธีการประมวลผลหาตำแหน่งจุดเดี่ยว (Single Point Positioning: SPP) และการประมวลผลค่าพิกัดจากข้อมูลรังวัดด้วยระบบดาวเทียมนำหน GPS โดยใช้ค่าแก้จากระบบดาวเทียม SBAS ด้วยวิธีการประมวลผลหาตำแหน่งจุดเดี่ยว (Single Point Positioning: SPP) ผลการศึกษาพบว่าปัจจุบันประเทศไทยสามารถรับสัญญาณจากระบบดาวเทียม SBAS ได้ 3 ระบบ คือ SPAN, GAGAN, และ BDSBAS ซึ่งค่าแก้ทั้ง 3 ระบบข้างต้น ไม่สามารถเพิ่มค่าความถูกต้องทางตำแหน่งทางราบและทางดิ่งได้โดยเฉลี่ย

Design and Implementation of a Low-Cost Local Beacon System for GPS-Denied Environments

Abstract: GNSS-denied navigation has been the topic of much research for decades. Interference and occlusion by the surrounding environment limit GNSS access in urban environments. Poor GNSS coverage in the Arctic is another reason to pursue local navigation systems independent on satellite coverage. Our solution is to develop specially designed beacon systems that transmit the beacons' position data to a vehicle over radio signals. The receiving vehicle then uses the signal strength to estimate its position relative to the beacons. This paper provides the design and implementation of a low-cost beacon system that provides position information required for navigation in GNSS-denied environments.

A workflow to study land subsidence based on InSAR analysis and hydro-mechanical modeling: A case study of Hanoi, Vietnam

Abstract: In recent years, land subsidence has been intensively studied due to its severe impacts on urban communities and the environment. Amongst others, groundwater withdrawal is suspected to be the main trigger for such land subsidence. A prominent example is the Red River Delta in Northeastern Vietnam, where Hanoi is located. Radar remote sensing for mapping ground movement has been successfully applied for Hanoi City to quantify the land subsidence. Specifically, SAR data at the X, C, and L bands have been used, mainly based on the small baseline subset (SBAS) and Persistent Scatterer InSAR (PSInSAR) methods for extracting deformation in the urban setting of Hanoi from 1995 to the present. In these previous studies, line-of-sight land deformation was converted into the vertical direction with the assumption that horizontal movement is insignificant. However, a detailed analysis of the hydro-mechanical processes triggering the subsidence would strongly benefit from more complete InSAR deformation data, accounting also for horizontal movement. Therefore, the study applies PSInSAR to process both ascending and descending Sentinel-1 data acquired from 2017 to the end of 2019 to extract both vertical and horizontal (along the east-west direction) deformation in the study area. Our results show that in some areas, total displacement adds up to 32 mm/y in the vertical (subsidence) and 17 mm/y in the horizontal direction, indicating that horizontal movements are not negligible when it comes to interpreting deformation and relating it to hydro-mechanical processes in a heterogeneous subsurface. An interdisciplinary workflow is introduced that illustrates how remotely sensed subsidence data can be interpreted with the help of a geological subsurface model and coupled hydro-mechanical simulations conducted with numerical multi-physics software. We present the data basis and model set-up for the planned modeling study with the open-source software platform OpenGeoSys.