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Copyright of Telecommunication Engineering is the property of Telecommunication Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The safe operation of unmanned ground vehicles (UGVs) demands fundamental and essential requirements for continuous and reliable positioning performance. Traditional coupled navigation systems, combining the global navigation satellite system (GNSS) with an inertial navigation system (INS), provide continuous, drift-free position estimation. However, challenges like GNSS signal interference and blockage in complex scenarios can significantly degrade system performance. Moreover, ultra-wideband (UWB) technology, known for its high precision, is increasingly used as a complementary system to the GNSS. To tackle these challenges, this paper proposes a novel tightly coupled INS/UWB/GNSS-RTK integrated positioning system framework, leveraging a variational Bayesian adaptive Kalman filter based on the maximum mixture correntropy criterion. This framework is introduced to provide a high-precision and robust navigation solution. By incorporating the maximum mixture correntropy criterion, the system effectively mitigates interference from anomalous measurements. Simultaneously, variational Bayesian estimation is employed to adaptively adjust noise statistical characteristics, thereby enhancing the robustness and accuracy of the integrated system's state estimation. Furthermore, sensor measurements are tightly integrated with the inertial measurement unit (IMU), facilitating precise positioning even in the presence of interference from multiple signal sources. A series of real-world and simulation experiments were carried out on a UGV to assess the proposed approach's performance. Experimental results demonstrate that the approach provides superior accuracy and stability in integrated system state estimation, significantly mitigating position drift error caused by uncertainty-induced disturbances. In the presence of non-Gaussian noise disturbances introduced by anomalous measurements, the proposed approach effectively implements error control, demonstrating substantial advantages in positioning accuracy and robustness. [ABSTRACT FROM AUTHOR]

Thermospheric mass densities are investigated to explore their responses to solar irradiance and geomagnetic activity during the period from 31 October to 7 November 2021. Utilizing data from the Global Navigation Satellite System (GNSS) payload and an ionization gauge mounted on the Orbital Neutral Atmospheric Detector (OAD) payload onboard the QQ-Satellite, thermospheric mass densities are derived through two independent means: precise orbit determination (POD) and pressure measurements. For the first time, observations of these two techniques are compared and analyzed in this study to demonstrate similarities and differences. Both techniques exhibit similar spatial–temporal variations, with clear dependences on local solar time (LT). However, the hemispheric asymmetry is almost absent in simulations from the NRLMSISE-00 and DTM94 models compared with observations. At high latitudes, density enhancements of observations and simulations are shown, characterized by periodic bulge structures. In contrast, only the OAD-derived densities exhibit wave-like disturbances that propagate from two poles to lower latitudes during geomagnetic storm periods, suggesting a connection to traveling atmospheric disturbances (TADs). Over the long term, thermospheric mass densities derived from the two means of POD and the OAD show good agreements, yet prominent discrepancies emerge during specific periods and under different space-weather conditions. We propose possible interpretations as well as suggestions for utilizing these two means. Significantly, neutral winds should be considered in both methods, particularly at high latitudes and under storm conditions. [ABSTRACT FROM AUTHOR]

AbstractAs a key support for people’s daily wayfinding, satellite navigation systems generate a considerable amount of by-product tracking data. Such human mobility data offer opportunities for quantitative studies of the link between human mobility and spatial information needs. Here, we propose a methodological framework for causal inference on observational individual-level spatiotemporal mobility data. We demonstrate how this framework enables to isolate and quantify the causal strength of environmental familiarity on reduced supporting navigation information needs. The results reported here show an approximately 9% average treatment effect of familiarity on reduced information needs. We explore the sensitivity of the results to variants of the realization of the causal model in the data analysis, as well as to the impact of environmental and trip-related confounders. This research introduces concepts of causal analysis on observational data to the spatial community, and mobility analytics community in particular. It is one of the first attempts to link causally spatial information needs during wayfinding across familiar and unfamiliar environments and thus advances the methodological toolkit for individual-level spatial causal inference. [ABSTRACT FROM AUTHOR]

Radio frequency interference (RFI) is emitted from various sources, terrestrial or orbital, and creates a nuisance for ground-based 21-cm experiments. In particular, single-dish observations will be highly susceptible to RFI due to their wide primary beam and sensitivity. This work aimed to simulate the contamination effects from the Radio Navigational Satellite System (RNSS) within the 1100–1350 (MHz) frequency band. The simulation can be divided into two parts: (i) satellite positioning, emission power, and the beam response on the telescope, and (ii) calibration of the satellite signals to data to improve the original model. We utilize previously observed single-dish L -band data from the Meer-Karoo Array Telescope (MeerKAT), which requires special calibration to account for regions contaminated by satellite-based RFI. We find that we can recreate the satellite contamination with high accuracy around its peak frequencies provided the satellite is not too close to the telescope's pointing direction. The simulation can predict satellite movements and signals for past and future observations, aiding in RFI avoidance and testing novel cleaning methods. The predicted signal sits below the noise in the target cosmology window in the L band (970–1015 MHz) making it difficult to confirm any out-of-band emission from satellites. However, in our simulations, this contamination still overwhelmed the 21-cm auto-power spectrum. Nevertheless, it is possible to detect the signal in cross-correlations after mild foreground cleaning. Whether such out of band contamination does exist will require further characterization of the satellite signals far away from their peak frequencies. [ABSTRACT FROM AUTHOR]

Copyright of AIN Journal is the property of Arab Institute of Navigation and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In recent years, satellite navigation systems have witnessed widespread adoption across diverse fields, including military surveillance, precision agriculture, traffic monitoring, resource exploration, and disaster assessment. However, navigation signals are susceptible to interference, with deceptive interference posing the most significant threat to navigation systems. This paper provides a comprehensive overview of satellite navigation spoofing and anti-spoofing techniques. It reviews the current state of spoofing and anti-spoofing technologies, analyzing advancements in spoofing techniques and the evolution of countermeasures. Furthermore, the paper elaborates on the impact of spoofing interference on receiver performance, examining its effects on positioning, timing, and velocity estimations. A detailed analysis of various anti-spoofing methods is presented, categorizing them into detection, identification, suppression, and localization techniques. This review aims to provide a thorough understanding of the evolving landscape of satellite navigation spoofing and anti-spoofing technologies, fostering further research and development efforts to ensure the integrity and resilience of satellite navigation systems in the face of sophisticated threats. [ABSTRACT FROM AUTHOR]

In the implementation of autonomous driving systems, accurate acquisition of the vehicle's location and orientation is crucial to providing a basis for path planning and obstacle avoidance. Although satellite navigation technology offers reliable positioning information, its signal is susceptible to interference in certain environments, such as areas with dense obstructions, which will affect the accuracy of vehicle localization and environmental mapping. To address the interference from dynamic points, we implement a method based on laser-vision multisensor fusion for identifying and extracting dynamic point clouds in environments where satellite signals are disrupted. We propose a dynamic point cloud extraction algorithm based on deep learning, utilizing semantic information to guide the network in extracting more precise information about the dynamic environment. We also construct a method for preliminary constraint of dynamic obstacles using global semantic information and design a multiframe point cloud processing approach with a sliding window mechanism, where residual data are accumulated and fed into the network as a composite model input. Experimental results demonstrate that our method significantly improves the positioning accuracy and map construction quality in dynamic environments, giving it considerable competitiveness compared with other advanced algorithms. [ABSTRACT FROM AUTHOR]

Satellite navigation interference monitoring is an important means to effectively evaluate interference and ensure the normal operation of global navigation satellite system (GNSS). Once interference is detected, this monitoring can identify the type of it, perform direction-finding and localization, evaluate its impact on GNSS, and guide the implementation of effective countermeasures. With the continuous progress of interference technology, the power required to cause the same jamming effect to the navigation system is getting smaller and smaller. Traditional radio monitoring system has been unable to meet the needs of the current satellite navigation monitoring in terms of sensitivity and accuracy. It is of great significance to develop and improve the dedicated satellite navigation monitoring system. This paper introduces the basic concept of satellite navigation interference monitoring and the composition of the system, analyzes the key technologies and finally gives an outlook on the development trends in this field. [ABSTRACT FROM AUTHOR]

Satellite navigation signals can provide users with accurate and continuous time and position information. Since the satellite navigation signal is susceptible to interference from terrain and other electromagnetic signals during transmission. In this study, to improve the accuracy of the traditional satellite navigation signal quality monitoring algorithm and to solve the problem of discretization in the monitoring results, the satellite navigation signal quality monitoring algorithm based on the Dung Beetle Optimization assisted Support Vector Machine (DBO-SVM) is proposed. The algorithm uses four feature quantities (correlation loss and symmetry of correlation peaks in the correlation domain, signal power in the frequency domain, eye diagram opening in the modulation domain) to classify the quality of satellite navigation signals, and optimizing the parameters of the SVM through the application of the dung beetles' foraging mechanism. Experimental validation was conducted by simulating satellite navigation signal data, and the results indicate that the DBO-SVM algorithm is more accurate than the traditional SVM algorithm, with an accuracy rate of over 98%. [ABSTRACT FROM AUTHOR]

The retrieval of global significant wave height (SWH) data is crucial for maritime navigation, aquaculture safety, and oceanographic research. Leveraging the high temporal resolution and spatial coverage of Cyclone Global Navigation Satellite System (CYGNSS) data, machine learning models have shown promise in SWH retrieval. However, existing models struggle with accuracy under high-SWH conditions and discard a significant number of such observations due to low quality, which limits their effectiveness in global SWH retrieval, particularly for monitoring tropical cyclone (TC) events. To address this, this study proposes a daily global SWH retrieval framework through the enhanced eXtreme Gradient Boosting model (XGBoost-SC), which incorporates Cumulative Distribution Function (CDF) matching to introduce prior distribution information and reduce errors for SWH values exceeding 3 m. An enhanced loss function is employed to improve accuracy and mitigate the distribution bias in low-SWH retrieval induced by CDF matching. The results were tested over one million sample points and validated against the European Centre for Medium-Range Weather Forecasts (ECMWF) SWH product. With the help of CDF matching, XGBoost-SC outperformed all models, significantly reducing RMSE and bias while improving the retrieval capability for high SWHs. For SWH values between 3–6 m, the RMSE and bias were 0.94 m and −0.44 m, and for values above 6 m, they were 2.79 m and −2.0 m. The enhanced performance of XGBoost-SC for large SWHs was further confirmed in TC conditions over the Western North Pacific and in the Western Atlantic Ocean. This study provides a reference for large-scale SWH retrieval, particularly under TC conditions. [ABSTRACT FROM AUTHOR]

Low-performing GPS receivers, often used in challenging scenarios such as attitude maneuver and attitude rotation, are frequently encountered for micro–nano satellites. To address these challenges, this paper proposes a modified robust adaptive hierarchical filtering algorithm (named IARKF). This algorithm leverages robust adaptive filtering to dynamically adjust the distribution of innovation vectors and employs a fading memory weighted method to estimate measurement noise in real time, thereby enhancing the filter's adaptability to dynamic environments. A segmented adaptive filtering strategy is introduced, allowing for flexible parameter adjustment in different dynamic scenarios. A micro–nano satellite equipped with a miniaturized dual-frequency GPS receiver is employed to demonstrate precise orbit determination capabilities. On-orbit GPS data from the satellite, collected in two specific scenarios—slow rotation and Earth-pointing stabilization—are analyzed to evaluate the proposed algorithm's ability to cope with weak GPS signals and satellite attitude instability as well as to assess the achievable orbit determination accuracy. The results show that, compared to traditional Extended Kalman Filters (EKF) and other improved filtering algorithms, the IARKF performs better in reducing post-fit residuals and improving orbit prediction accuracy, demonstrating its superior robustness. The three-axes orbit determination internal consistency precision can reach the millimeter level. This work explores a feasible approach for achieving high-performance orbit determination in micro–nano satellites. [ABSTRACT FROM AUTHOR]

Objectives: Sea level changes have significant impacts on coastal ecosystems and human survival and development. Monitoring sea level is an essential part of global climate change and marine disaster surveillance. Methods: This study uses global navigation satellite system interferometric reflectometry (GNSS-IR) technology to analyze data from 11 frequency bands across four major satellite navigation systems, inverting for long time series of tidal level results from 2018 to 2022 at HKQT station in Hong Kong, China, and at SC02 station in Seattle, USA, and performs tidal harmonic analysis and estimates long-term change trends. Results: The results indicate that the accuracy of sea level inversion varies among frequency bands. After correcting for dynamic sea level errors, the accuracy is around 10 cm. Different receivers and environments can lead to varying accuracy performances in the same frequency band. Dynamic sea level correction effectively reduces GNSS-IR sea level inversion errors, with an average precision improvement of 20.5% in terms of unbiased root mean square error. Multi-mode multi-frequency data can enhance the temporal resolution of sea level inversion, and improve the accuracy and continuity of data. Tidal harmonic analysis shows that the amplitude results across 11 frequency bands align well with the tide gauge results, with overall differences less than 1 cm. However, some frequency bands show significant phase discrepancies in certain tidal components, related to the lower temporal resolution of single-frequency sea level inversion results. Long-term trend analysis indicates a sea level rise of about 6.0 mm/a near Hong Kong, and a sea level decline of about 4.0 mm/a near Seattle which aligns well with tide gauge results. Conclusions: The findings of this paper not only assess the performance of multi-mode multi-frequency GNSS-IR technology in monitoring sea level changes, but also reveal long-term trends in sea level. It can provide valuable references for marine disaster monitoring and oceanographic research. [ABSTRACT FROM AUTHOR]

The BeiDou-3 navigation satellite system (BDS-3) has officially provided positioning, navigation, and timing (PNT) services to global users since 31 July 2020. With the application of inter-satellite link technology, global integrity monitoring becomes possible. Nevertheless, the content of integrity monitoring is still limited by the communication capacity of inter-satellite links and the layout of ground monitoring stations. Low earth orbit (LEO) satellites have advantages in information-carrying rate and kinematic velocity and can be used as satellite-based monitoring stations for navigation satellites. Large numbers of LEO satellites can provide more monitoring data than ground monitoring stations and make it easier to obtain full-arc observation data. A new challenge of redundant data also arises. This study constructs multi-source observation links with satellite-to-ground, inter-satellite, and satellite-based observation data, proposes an integrity monitoring method with optimization of observation links, and verifies the performance of integrity monitoring with different observation links. The experimental results show four findings. (1) Based on the integrity status of BDS-3, the proposed system-level integrity mode can realize full-arc anomaly diagnosis in information and signals according to the observation conditions of the target satellite. Apart from basic navigation messages and satellite-based augmentation messages, autonomous messages and inter-satellite ranging data can be used to evaluate the state of the target satellite. (2) For a giant LEO constellation, only a small number of LEO satellites need to be selected to construct a minimum satellite-based observation unit that can realize multiple returns of navigation messages and reduce the redundancy of observation data. With the support of 12 and 30 LEO satellites, the minimum number of satellite-based observation links is 1 and 4, respectively, verifying that a small amount of LEO satellites could be used to construct a minimum satellite-based observation unit. (3) A small number of LEO satellites can effectively improve the observation geometry of the target satellite. An orbit determination observation unit, which consists of chosen satellite-to-ground and/or satellite-based observation links based on observation geometry, is proposed to carry out fast calculations of satellite orbit. If the orbit determination observation unit contains 6 satellite-to-ground monitoring links and 6/12/60 LEO satellites, the value of satellite position dilution of precision (SPDOP) is 38.37, 24.60, and 15.71, respectively, with a 92.95%, 95.49%, and 97.12% improvement than the results using 6 satellite-to-ground monitoring links only. (4) LEO satellites could not only expand the resolution of integrity parameters in real time but also augment the service accuracy of the navigation satellite system. As the number of LEO satellites increases, the area where UDRE parameters can be solved in real time is constantly expanding to a global area. The service accuracy is 0.93 m, 0.88 m, and 0.65 m, respectively, with augmentation of 6, 12, and 60 LEO satellites, which is an 8.9%, 13.7%, and 36.3% improvement compared with the results of regional service. LEO satellites have practical application values by improving the integrity monitoring of navigation satellites. [ABSTRACT FROM AUTHOR]

Satellite navigation spoofing is a major challenge in the field of satellite/inertial integrated navigation security. To effectively enhance the anti-spoofing capability of a low-cost GNSS/MEMS-SINS integrated navigation system, this paper proposes a method integrating a dual-antenna global navigation satellite system (GNSS) and a micro-inertial measurement unit (MIMU) to determine the two-dimensional directions of spoofing signal sources. The proposed method evaluates whether the single-difference carrier-phase measurements conform to the corresponding directions given in ephemeris files and employs micro-inertial navigation technology to determine the two-dimensional directions of the signal source. Based on a set of short-baseline dual-station measurements, the accuracy of the proposed method in determining the two-dimensional azimuths of satellites in synchronous orbits is verified, and the deviation from the real value is evaluated. The experimental results show that the proposed method can effectively identify the spoofed satellite signals while providing high-precision direction information at three different distances: 100 m, 10 km, and 36,000 km. The two-dimensional angle errors do not exceed 0.2 rad, 0.05 rad, and 0.01 rad, respectively. [ABSTRACT FROM AUTHOR]

The recent rapid development of low Earth orbit (LEO) constellation-based navigation techniques has enhanced the ability of position, navigation, and timing (PNT) services in deep attenuation and interference environments. However, existing navigation modulations face the challenges of high acquisition complexity and do not improve measurement precision at the same signal strength. We propose a pulsed orthogonal time frequency space (Pulse-OTFS) signal, which naturally converts continuous signals into pulses through a special delay-Doppler domain pseudorandom noise (PRN) code sequence arrangement. The performance evaluation indicates that the proposed signal reduces at least 89.4% of the acquisition complexity. The delay measurement accuracy is about 8 dB better than that of the traditional binary phase shift keying (BPSK) signals with the same bandwidth. It also provides superior compatibility and anti-multipath performance. The advantages of fast acquisition and high-precision measurement are verified by processing the real signal in the developed software receiver. As Pulse-OTFS occupies only one time slot of a signal period, it can be easily integrated with OTFS-modulated communication signals and used as a navigation signal from broadband LEO satellites as an effective complement to the global navigation satellite system (GNSS). [ABSTRACT FROM AUTHOR]

With the gradual enlargement of the application of satellite navigation spoofing signals in the field of anti-drone and other areas, spoofing signals have severely threatened the application of satellite navigation system. As spoofing signals exhibit strong concealment characteristics and difficulties in detection and identification, this study proposed a GPS deception signal detection method based on a low-frequency power spectrum. Data acquisition was achieved using a conventional satellite navigation spoofing signal receiving equipment, and a spoofing signal processing method based on low-frequency power spectrum and Kalman filtering was adopted. The method achieved a spoofing signal detection accuracy reaches 92.8%. [ABSTRACT FROM AUTHOR]

When mooring a ship near the quay, it is important to monitor its speed at the time of contact with the quay to ensure the safe execution of the mooring operation. During mooring, the speed of the ship must not exceed specified values; therefore, it is very important to have the possibility to measure it with high accuracy and its appropriate adjustment. This article aims to present the assessment methodology of the forces acting on quay equipment when a ship is mooring using data provided by the real-time kinematic (RTK) application of the navigation satellite system, as well as a way to calculate the comparative index, which can show the advantages of using data provided by high-accuracy measurement systems compared with the typical one. The methodology of assessing the forces acting on quay equipment when the ship is mooring using data provided by high-precision systems was applied. To verify the developed methodology, the experiments were carried out on real ships and using a calibrated simulator. Based on the research results, it was stated that when planning and managing ships' mooring operations in ports using data provided by the RTK application, it is possible to reduce the planned energy absorption of quay fenders up to 1.5–1.8 times while preparing the investment in quay development. The implementation of the developed methodology may contribute to the improvement of navigation safety when ships are mooring near the quays and thus allow for the reduction in the probability of undesirable situations occurring. The research results may be of interest to representatives of seaports authorities, traffic management offices, shipowners and other institutions involved in safe ships' navigation in seaports and approaches to them. [ABSTRACT FROM AUTHOR]

Space weather events, including solar flares, coronal mass ejections, and geomagnetic storms, have significant effects on various transportation systems. This review provides a comprehensive examination of the current understanding and future outlook of space weather effects on air, maritime, railway, and ground transportation. It explores the mechanisms through which space weather causes communication blackouts, satellite navigation failure, elevated cosmic radiation, and geomagnetically induced currents, leading to disruptions in transportation operations. Historical events are analyzed to underscore the diversity and severity of these impacts. Additionally, this review discusses the anticipated challenges posed by the upcoming solar maximum of Solar Cycle 25 and highlights the need for improved forecasting, mitigation strategies, and resilient infrastructure to safeguard transportation systems against space weather threats. By integrating findings from recent studies and historical data, this review aims to enhance the preparedness and response strategies of the transportation sector in the face of evolving space weather risks. Plain Language Summary: Space weather, which includes events like solar flares, coronal mass ejections, and geomagnetic storms, can seriously affect various transportation systems. This review thoroughly examines how these space weather phenomena impact air, maritime, railway, and ground transportation. It explains how space weather events can cause problems such as communication blackouts, failure of satellite navigation systems, increased levels of cosmic radiation, and geomagnetically induced currents. These issues can disrupt transportation operations significantly. The review looks at past events to show the range and seriousness of these impacts. It also discusses the upcoming solar maximum of Solar Cycle 25 and the challenges it may bring. The review emphasizes the need for better forecasting methods, effective mitigation strategies, and stronger infrastructure to protect transportation systems from space weather threats. By combining recent research and historical data, this review aims to improve how the transportation sector prepares for and responds to the risks posed by space weather. This is crucial for ensuring that transportation systems remain functional and safe despite the challenges posed by space weather. Key Points: Mechanisms of space weather‐caused disruptions in critical infrastructure are identifiedThe effects of space weather on various transportation modes are examinedRecommendations for mitigating space weather effects on transportation systems are discussed [ABSTRACT FROM AUTHOR]

The quality of Galileo system services is affected by the accuracy of distance determination from the user's application to the individual satellite. The goal of our research was to find out what influence the accuracy of distance determination between the user's application of the Galileo system and the cooperating satellites of the Galileo system has on the ability to determine the location of the user's application. A solution based on Groebner's algebraic approaches was used to determine the receiver user's position. When creating distance measurement error models between the Galileo system user's receiver and cooperating satellites, we assumed that the values of those errors considered all factors that affected the accuracy of those distance measurements. To evaluate the algorithms, we used a statistical set of 500 simulation results to determine the positioning of the user's application of the Galileo system. If the distances between the user's application and the individual satellite were measured accurately, then the user's application coordinate errors had values between 1.86 × 10−9 m and −1.8 × 10−8 m. These errors should be equal to zero. The positioning error was caused by a numerical error in the calculation due to the software used. If the errors of distance determination from the user's application to the individual satellite varied from −0.05 m to 0.09 m, then the error in determining the positioning of the user's application of the Galileo system was from 0.0 m to 1.2 m. If the distances of the user's receiver to the satellites were measured with errors greater than 0.09 m, the errors in determining its position were much larger. The simulation results confirmed the known fact that the satellites' geometry influences the accuracy of determining the location of the user's application. In the following research, we will solve the problem of how to reduce the sensitivity of the mentioned algorithms when determining the position of the satellite navigation system receiver due to errors in determining the distance from the user's application to the individual satellite. [ABSTRACT FROM AUTHOR]

The field of satellite navigation has seen significant advancements due to the fast development of multi-constellation Global Navigation Satellite Systems (GNSS). Around 150 satellites will be in service when all six systems – GPS, GLONASS, Galileo, BeiDou, QZSS, and NAVIC – are launched by 2030, offering both enormous potential and advantages for research and engineering applications. This study used an experiment on the accuracy, particularly for short, medium, long baselines (Wide Lane ambiguity solution) of the BeiDou, QZSS and QZSS/BeiDou combinations. It showed that with the integration of BeiDou/QZSS static measurements in the study region millimetre-centimetre accuracy for short, medium, and long baselines can be attained. Based on the results of this study, it can be concluded that the 1st (QZSS/BeiDou), 2nd (BeiDou), and 3rd (QZSS) strategies feature different horizontal accuracies for all categories. The obtained results with different satellite configurations for the Fixed-Wide-Lane integer ambiguity solution are compared with each other. Accuracy at the short baseline (BeiDou, QZSS, and BeiDou/QZSS satellites) was obtained in the range of 0.5–0.7 cm. For the medium baseline, it was computed around 1.8–82 cm. For the long baseline, the accuracy was 5.6–13.3 cm. [ABSTRACT FROM AUTHOR]

In recent years, global forests have faced frequent wildfires due to climate change, leading to significant ecological and economic losses. Traditional fire monitoring technologies like MODIS and VIIRS are often hindered by cloud cover and smoke. This study explores the potential of Global Navigation Satellite System Reflectometry (GNSS-R) for fire monitoring in complex environments. By analyzing cumulative burned areas in southeastern Brazil, a new fire detection method combining GNSS-R with Convolutional Neural Networks (CNN) is proposed to improve accuracy and response time. Results show high agreement between predicted and actual fire areas, with CNN outperforming Random Forest (RF) by 3.3% in prediction accuracy and achieving a 17.4% increase in model fitting. Error analysis indicates no systematic errors, with CNN exhibiting lower fire detection errors and better spatial alignment with actual conditions than RF, which tends to overestimate. This study provides a novel approach to fire detection using GNSS-R, with significant implications for fire prediction and management strategies. [ABSTRACT FROM AUTHOR]

The rapid development of Low Earth Orbit (LEO) satellite navigation systems requires modulation schemes with strong anti-jamming capabilities, high spectral efficiency, and the ability to achieve precise tracking in high-dynamic environments. Traditional Binary Offset Carrier (BOC) modulation suffers from multi-peak ambiguity, leading to false lock issues. To address this, FH-BOC modulation, which integrates BOC modulationand frequency hopping, significantly improves both anti-jamming performance and spectral efficiency. Against this background, this paper proposes a comprehensive high-dynamic tracking algorithm for FH-BOC signals. (1) Based on the adaptive Kalman filter algorithm, high-precision carrier tracking was achieved in high-dynamic environments. (2) By leveraging the correlation between the ranging code and frequency-hopping offset carrier, a composite pseudo-code is generated through the XOR operation, and a corresponding composite code-tracking loop is introduced. (3) Based on code loop tracking results, the frequency-hopping moments of the subcarrier are detected, and a phase-locked loop for the frequency-hopping subcarrier is established. Simulation results indicate that the algorithm achieves centimeter-level pseudorange measurement accuracy for FH-BOC navigation signals under the JPL high-dynamic model. [ABSTRACT FROM AUTHOR]

The utilization of the global navigation satellite systems (GNSS) services in both military and civilian applications as well as for scientific investigation has grown exponentially. However, the increasing reliance on GNSS applications has raised concerns about potential risks from intentional radio frequency interference (RFI) transmitters. RFI significantly affects GNSS's environmental monitoring capabilities by inflating the scintillation index and misleading the scientific community with scintillation indices not attributable to ionospheric dynamic events. Consequently, the existing climatological distribution of GNSS scintillations may require careful reevaluation, as it may not adequately filter out RFI induced scintillations. Thus, characterizing the global RFI occurrence regions and developing real‐time detection capabilities to mitigate its effects is critically important. Leveraging GNSS measurements from ground stations and six COSMIC‐2 satellite constellations, we have developed a technique to detect RFI events and identify RFI active regions. Additionally, for the first time, we have implemented techniques that differentiate RFI associated scintillations from scintillations caused by ionospheric turbulence. Plain Language Summary: The global navigation satellite systems (GNSS) signals, transmitted by different navigation satellite constellations, are utilized by both military and civilian users for positioning, navigation, and timing (PNT) purposes. The GNSS services are also critically important for a wide range of modern economies, such as for surveying, geodesy, infrastructure, and farming applications. However, the performance of such services can be impacted by unauthorized radio frequency interference (RFI) transmitters that emit artificial noise (jamming) or false/modified pseudorandom noise (PRN) codes to deceive a receiver into calculating a false position (spoofing). We developed a technique that allow us to identify RFI events from GNSS observations and to pinpoint distinct regions where RFI is more active and intense. We also demonstrate that RFI can induce scintillation—referred to as "fake scintillation"—which is distinct from the scintillation caused by ionospheric irregularities, potentially sending false alarm to users of scintillation all‐clear zone map. Our result clearly shows that RFI is often present in the vicinity of conflict zones and affect GNSS signals similarly to how signal blockage, foliage attenuation, ionospheric scintillation, and multipath do. Intentionally generated L‐band (GNSS frequency band) RFI transmitters can be ground‐based or space‐based (orbital transmitters) and are frequently deployed for military purposes by governments and independent groups to deny regional access to GNSS capabilities, and more recently, to prevent the use of unmanned aerial vehicles (drones). However, such unintended RFI transmitters have the potential to disrupt GNSS applications or halt service operations (navigation blackout), thereby endangering human safety by providing false information to the users. Key Points: Intentional radio frequency interference (RFI) affects global navigation satellite systems signalsRFI significantly inflate the scintillation index not attributable to ionospheric dynamic eventsRFI active zone correlate with regional conflicts and other geopolitical activity/events [ABSTRACT FROM AUTHOR]

The International Global Navigation Satellite System (GNSS) Service (IGS) has recommended calibrating the extended satellite antenna Phase Center Variation (PCV) model for all navigation satellites to support low-Earth-Orbit (LEO) satellite applications. Owing to the absence of ground-calibrated PCVs for the BeiDou Navigation Satellite System (BDS), tracking data from global ground stations were used for in-orbit estimations. However, limited by the observed maximum nadir angle, PCVs based on ground data cannot cover the entire range of nadir angles observed using by LEO satellites. In this study, the FengYun-3C and LuTan-1 missions were used to extend the PCVs of the BDS Inclined GeoSynchronous orbit (IGSO) and medium-Earth-orbit (MEO) satellites. The PCVs corresponding to the ionosphere-free linear combinations of B1I/B2I, B1I/B3I, and B1C/B2a were calibrated in-orbit by extending the maximum nadir angle from 9° to 10° for the IGSO and from 13° to 15° for the MEO. There was good consistency among the estimated PCVs of satellites of the same type. In addition, these estimated PCVs were close to the corresponding satellite block-specific values estimated based on ground tracking data. The impact of the extended PCVs of the BDS satellite antenna was investigated by comparing them with the unextended PCVs model in the receiver antenna PCVs pattern estimation and precise orbit determination of the FengYun-3C and LuTan-1 satellites. The results showed that the extended BDS satellite PCVs effectively reduced the unmodeled error of the unextended BDS satellite PCVs in the low-elevation region of the LEO receiver antenna PCV patterns. In addition, compared with the introduction of phase center offset alone, the introduction of ground-based PCVs can improve the overlapping orbit differences (OODs) of LEO satellites, and the extended BDS satellite PCVs can further improve the OODs. Taking B1C/B2a as an example, the improvement ratio of OODs in the 3D direction of Lutan-1A increased from 5.2 % to 8.0 %, and that of Lutan-1B can rise from 1.7 % to 4.2 %. [ABSTRACT FROM AUTHOR]

It is essential to provide high-integrity navigation information for safety-critical applications. Global navigation satellite systems (GNSSs) play an important role in these applications because they can provide global, high-accuracy, all-weather navigation services. Therefore, it has been a hot topic to improve GNSS integrity performance. This paper focuses on an initial proposal of the next-generation BeiDou Navigation Satellite System (BDS) integrity subsystem, with the aim of providing high-quality and global integrity services for the BDS. This paper first reviews the current status of the third-generation BDS integrity service. Following this, this paper proposes a space–ground integrated integrity monitoring design for the BDS that integrates the traditional ground-based integrity monitoring method, the advanced satellite autonomous integrity monitoring (A-SAIM) method, and the augmentation from low-earth-orbit (LEO) satellites. Specifically, this work offers an initial design of the A-SAIM method, which considers both single-satellite autonomous integrity monitoring and multi-satellite joint integrity monitoring. In addition, this work describes two different ways to augment BDS integrity with LEO satellites, i.e., (a) LEO satellites act as space monitoring stations and (b) LEO satellites act as navigation satellites. Simulations are carried out to validate the proposed design using CAT-I operation in civil aviation as an example. Simulation results indicate the effectiveness of the proposed design. In addition, simulation results suggest that if the fault probability of LEO satellites is worse than 1 × 10−4, LEO satellites can contribute more to BDS integrity performance improvement by acting as space monitoring stations; otherwise, it would be better to employ LEO satellites to broadcast navigation signals. The results also suggest that after taking LEO satellites into account, the global coverage of CAT-I can be potentially improved from 67% to 99%. This work is beneficial to the design of the next-generation BDS integrity subsystem. [ABSTRACT FROM AUTHOR]

To enhance the anti-interference capabilities and increase flexibility in frequency allocation between the lower and upper sidebands of the navigation signal, we introduce frequency-hopping binary offset carrier modulation with independent frequency-hopping patterns in lower and upper sidebands (IFH-BOC). This novel modulation is classified as a constant-envelope multiplexing (CEM) method, with independent frequency-hopping patterns for the lower and upper sidebands, in contrast with frequency-hopping binary offset carrier (FH-BOC) and binary offset carrier (BOC) modulations, which share the same patterns. IFH-BOC represents a generalized modulation that incorporates FH-BOC and BOC, thus retaining their advantages while introducing new characteristics, such as independent frequency-hopping pattern design and flexible spectral splitting. The results indicate that IFH-BOC maintains the same time–frequency characteristics and measurement accuracy as FH-BOC when using identical modulation parameters, yet it demonstrates superior anti-interference performance due to its varied frequency-hopping patterns. Furthermore, IFH-BOC provides enhanced flexibility in spectral splitting compared with BOC modulation, potentially allowing for increased availability of L-band frequencies for satellite navigation. With these benefits, IFH-BOC is poised to be a promising modulation for the signal design of next-generation global navigation satellite systems. [ABSTRACT FROM AUTHOR]

Featured Application: This paper introduces a two-dimensional GNSS signal positioning method for tunnels, characterized by low cost, seamless positioning continuity between the interior and exterior of the tunnel, and ease of engineering implementation. To address the issue of GNSS receivers being unable to function properly in tunnels due to the loss of Global Navigation Satellite System (GNSS) signals, this paper proposes a two-dimensional differential positioning system for tunnel environments based on dual leaky coaxial (LCX) cables with GNSS signal frequency relay forwarding. The system receives mixed GNSS signals from open environments and utilizes the frequency selection capabilities of the MAX2769E chip to separate and generate radio frequency signals at different frequencies corresponding to GPS, BDS, and GLONASS. These signals are then used to drive three ports of the LCX cables, which are laid in parallel within the tunnel. By leveraging the uniform radiation characteristics of the LCX cables, stable GNSS signal coverage is achieved throughout the tunnel. On the receiving end, the GNSS receiver achieves two-dimensional positioning by utilizing inter-satellite pseudorange differences and reference point error correction. The simulation results indicate that the dual T-shaped radiating LCX cables configuration offers excellent positioning accuracy and noise resistance, achieving meter-level positioning accuracy in tunnel environments. [ABSTRACT FROM AUTHOR]

Lunar exploration currently requires guidance and navigation based on satellite self-position estimation with an accuracy of 100 m or better to achieve pinpoint landing of spacecraft for scientific survey missions. Various terrain relative navigation methods have been proposed for estimating spacecraft position. For landing small spacecraft on a gravity target, simple and reliable methods are highly desirable due to the limited onboard computing resources available for optical navigation. Position estimation methods based on point pattern matching are promising for this purpose. The lunar landing project “Smart Lander for Investigating Moon” (SLIM) of the Japan Aerospace Exploration Agency (JAXA) plans to use line segment matching, which employs line segments created using the center coordinates of craters, for lander position estimation. Since the original method for the SLIM project may require direction matching to be performed twice for each line segment, the method can be improved by reducing the number of direction matches. In this study, an improved line segment matching method that uses crater size in addition to center coordinates is proposed to reduce the computation time for the original method for SLIM. The usefulness of the proposed method is confirmed by simulations. [ABSTRACT FROM AUTHOR]

The time of a satellite navigation system is primarily generated by the main control station of the ground system. Consequently, when ground stations fail, there is a risk to the continuous provision of time services to the equipment and users. Furthermore, the anticipated launch of additional satellites will further strain the satellite–ground link. Next-generation satellite navigation systems will rely on time deviation measurements from inter-satellite links to independently establish and maintain a space-based time reference, enhancing the system's reliability and robustness. The increasing number of low-Earth-orbit satellite navigation constellations provides ample resources for establishing a space-based time reference. However, this also introduces challenges, including extensive time scale computations, increased link noise, and low clock resource utilization. To address these issues, this paper proposes a Distributed Kalman Plus Weight (D-KPW) algorithm, which combines the benefits of Kalman filtering and the weighted average algorithm, balancing the performance with computational resources. Furthermore, an adaptive clock control algorithm, D-KPW (Control), is developed to account for both the short-term and long-term frequency stability of the time reference. The experimental results demonstrate that the frequency stability of the time reference established by the D-KPW (Control) algorithm reaches 7.40 × 10 − 15 and 2.30 × 10 − 15 for sampling intervals of 1000 s and 1,000,000 s, respectively, outperforming traditional algorithms such as ALGOS. The 20-day prediction error of the time reference is 1.55 ns. Compared to traditional algorithms such as AT1, ALGOS, Kalman, and D-KPW, the accuracy improves by 65%, 65%, 66%, and 67%, respectively. [ABSTRACT FROM AUTHOR]

The ionospheric state holds significant implications for satellite navigation, radio communication, and space weather; however, precise forecasting of the ionosphere remains a formidable challenge. To improve the accuracy of traditional forecasting models, we developed an enhancement model based on the CODE and IRI forecasting methods, termed the Global Ionospheric Maps Forecast Enhancement Model (GIMs-FEM). The results indicated that by extracting the GIM features from existing forecasts and incorporating additional proxies for geomagnetic and solar activity, the GIMs-FEM provided stable and reliable forecasting outcomes. Compared to the original forecasting models, the overall model error was reduced by approximately 15–17% on the test dataset. Furthermore, we analyzed the model's performance under different solar activity conditions and seasons. Additionally, the RMSE for the C1pg model ranged from 0.98 TECu in the solar minimum year (2019) to 6.91 TECu in the solar maximum year (2014), while the enhanced GIMs (C1pg) model ranged from 0.91 to 5.75 TECu, respectively. Under varying solar activity conditions, the RMSE of GIMs-FEM for C1pg (C2pg) ranged from 0.98 to 6.91 TECu (0.96 to 7.26 TECu). Seasonally, the GIMs-FEM model performed best in the summer, with the lowest RMSE of 1.9 TECu, and showed the highest error in the autumn, with an RMSE of 2.52 TECu. [ABSTRACT FROM AUTHOR]

Increasing climatic and human pressures are changing the world's water resources and hydrological processes at unprecedented rates. Understanding these changes requires comprehensive monitoring of water resources. Hydrogeodesy, the science that measures the Earth's solid and aquatic surfaces, gravity field, and their changes over time, delivers a range of novel monitoring tools that are complementary to traditional hydrological methods. It encompasses geodetic technologies such as Altimetry, Interferometric Synthetic Aperture Radar (InSAR), Gravimetry, and Global Navigation Satellite Systems (GNSS). Beyond quantifying these changes, there is a need to understand how hydrogeodesy can contribute to more ambitious goals dealing with water‐related and sustainability sciences. Addressing this need, we combine a meta‐analysis of over 3,000 articles to chart the range, trends, and applications of satellite‐based hydrogeodesy with an expert elicitation that systematically assesses the potential of hydrogeodesy. We find a growing body of literature relating to the advancements in hydrogeodetic methods, their accuracy and precision, and their inclusion in hydrological modeling, with a considerably smaller portion related to understanding hydrological processes, water management, and sustainability sciences. The meta‐analysis also shows that while lakes, groundwater and glaciers are commonly monitored by these technologies, wetlands or permafrost could benefit from a wider range of applications. In turn, the expert elicitation envisages the potential of hydrogeodesy to help solve the 23 Unsolved Questions of the International Association of Hydrological Sciences and advance knowledge as guidance toward a safe operating space for humanity. It also highlights how this potential can be maximized by combining hydrogeodetic technologies simultaneously, exploiting artificial intelligence, and accurately integrating other Earth science disciplines. Finally, we call for a coordinated way forward to include hydrogeodesy in tertiary education and broaden its application to water‐related and sustainability sciences in order to exploit its full potential. Plain Language Summary: Increasing climatic and human pressures are changing the world's water resources and hydrological processes at unprecedented rates. Understanding these changes requires comprehensive monitoring of water resources. Hydrogeodesy, the science that measures the Earth's solid and aquatic surfaces, gravity field, and their changes over time, delivers a range of novel monitoring tools complementary to traditional hydrological methods. It encompasses technologies such as Altimetry, Interferometric Synthetic Aperture Radar (InSAR), Gravimetry, and Global Navigation Satellite Systems (GNSS). Beyond quantifying these changes, we need to understand the potential of hydrogeodesy to contribute to more ambitious goals of water‐related and sustainability sciences. Addressing this need, we combine a meta‐analysis of over 3,000 articles to chart the range, trends, and applications of hydrogeodesy with an expert elicitation that systematically assesses this potential. We find a growing body of literature relating to advancements in hydrogeodetic methods, their accuracy and precision, and their inclusion in hydrological modeling. The expert elicitation envisages the large potential to solve hydrological problems and sustainability challenges. It also highlights how this potential can be maximized by combining several hydrogeodetic technologies, exploiting artificial intelligence, and accurately integrating other Earth science disciplines. Key Points: This is a community view on hydrogeodesy, the science that measures the Earth's solid and aquatic surfaces, gravity field, and their changesHydrogeodesy encompasses geodetic technologies such as Altimetry, Interferometric Synthetic Aperture Radar, Mass gravimetry, and Global Navigation Satellite SystemsWe study the evolution of hydrogeodesy and its role within current hydrological, sustainability science, and management frameworks [ABSTRACT FROM AUTHOR]

This study considers a relative orbit estimation problem wherein an observing spacecraft navigates with respect to a target space object at a large separation distance (several kilometers) using only the bearing angles obtained by a single onboard camera. Generally, the extended Kalman filter (EKF), which is based on linear relative motion equations such as the Clohessy–Wiltshire equation, is used for the relative navigation of satellites. The EKF linearizes the estimation error around the current estimate and applies the Kalman filter equations to this linearized system. However, it has been shown that nonlinearities of the orbit determination problem can make the linearization assumption insufficient to represent the actual uncertainty. Therefore, an analytical second-order extended Kalman filter (ASEKF) for relative orbit estimation is proposed in this study. The ASEKF, to sequentially estimate the relative states of satellites and their associated uncertainties, is formulated based on a second-order analytic relative-motion equation under J2-perturbtation, which can overcome the deficiencies of existing approaches that mainly focus on applications in two-body, near-circular, and linearized orbit dynamics. Numerical results show that the proposed method provides superior robustness and mean-square error performance compared to linear estimators under the conditions considered. [ABSTRACT FROM AUTHOR]

The continental United States is well instrumented with facilities for mid‐latitude upper atmosphere research that operate on a continuous basis. In addition, citizen scientists provide a wealth of information when unusual events occur. We combine ionospheric total electron content (TEC) data from distributed arrays of GNSS receivers, magnetometer chains, and auroral observations obtained by citizen scientists, to provide a detailed view of the intense auroral breakup and westward surge occurring at the peak of the 10–11 May 2024 extreme geomagnetic storm. Over a 20‐min interval, vertical TEC (vTEC) increased at unusually low latitude (∼45°) and rapidly expanded azimuthally across the continent. Individual receiver/satellite data sets indicate sharp bursts of greatly elevated of vTEC (∼50 TECu). Intense red aurora was co‐located with the leading edge of the equatorward and westward TEC enhancements, indicating that the large TEC enhancement was created by extremely intense low‐energy precipitation during the rapid substorm breakup. Plain Language Summary: For over 12 hr, the 10–11 May 2024 the extreme Gannon geomagnetic storm sent brilliant auroral displays into the night skies at mid and low latitudes around the world. Precipitating auroral electrons and protons ionize the upper atmosphere at 100–500 km altitude, increasing ionospheric total electron content (TEC). We use the perturbation of the signals received by the distributed array of navigation satellite receivers to map the intensification and spread of an extreme auroral event across the continental US. Photo and video observations of the auroral event contributed by citizen scientists indicate that the TEC enhancement closely matched the westward and equatorward expansion of strong red aurora. Coincident with the auroral breakup, sharp bursts of greatly elevated TEC were observed. Auroral breakup was accompanied by a bright red over green discrete auroral feature at the leading edge of the equatorward expansion of strong red aurora. Based on the direct auroral observations, we believe that the westward expansion of low‐energy electron precipitation is likely the driver of the large TEC enhancements observed during the event. Key Points: Total electron content (TEC) maps show the intensification and spread of the 11 May 2024 extreme auroral event across the continental US over a 20‐min intervalAll sky camera imagery indicates that the TEC enhancement closely matches the westward and equatorward expansion of strong red auroraCoincident with auroral breakup, individual receiver/satellite data sets show sharp bursts of greatly elevated TEC 50 TECu above background [ABSTRACT FROM AUTHOR]

Algal blooms, resulting from the overgrowth of algal plankton in water bodies, pose significant environmental problems and necessitate effective remote sensing methods for monitoring. In recent years, Global Navigation Satellite System–Reflectometry (GNSS-R) has rapidly advanced and made notable contributions to many surface observation fields, providing new means for identifying algal blooms. Additionally, meteorological parameters such as temperature and wind speed, key factors in the occurrence of algal blooms, can aid in their identification. This paper utilized Cyclone GNSS (CYGNSS) data, Sentinel-3 OLCI data, and ECMWF Re-Analysis-5 meteorological data to retrieve Chlorophyll-a values. Machine learning algorithms were then employed to classify algal blooms for early warning based on Chlorophyll-a concentration. Experiments and validations were conducted from May 2023 to September 2023 in the Hongze Lake region of China. The results indicate that classification and early warning of algal blooms based on CYGNSS data produced reliable results. The ability of CYGNSS data to accurately reflect the severity of algal blooms opens new avenues for environmental monitoring and management. [ABSTRACT FROM AUTHOR]

The Direction of Arrival (DOA) parameter is a key parameter in directional channel modeling for GNSS systems and multipath suppression. However, achieving high-precision, low-complexity DOA estimation of multiple signal sources without requiring a known source number is still a challenge. This paper introduces a satellite navigation DOA parameter estimation method based on deconvolution beamforming. By exploiting the translational invariance property of the uniform linear array pattern, the deconvolution process is applied to the de-spread array pattern of satellite navigation signals, achieving high-precision estimation of DOA parameters. This method can achieve high-precision blind DOA estimation of multiple signal sources while significantly reducing the estimation complexity. Compared with traditional methods, precise DOA estimation can be achieved even in low-signal-to-noise-ratio conditions and with a small number of elements in the array. The theoretical analysis and simulation results verify the effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

Traditional pseudo‐satellite‐based indoor positioning techniques are greatly affected by the presence of multipath effects, leading to a notable reduction in the positioning precision. In order to tackle this challenge, a pseudo‐satellite indoor positioning method based on deep learning is proposed. The method grids the localization region, thus transforming positioning from a regression problem to a classification problem in the gridded areas. 1D‐convolutional neural network is employed to extract the correlation between pseudo‐satellite data and the positioning of indoor areas. Data are collected and the method is validated in three types of areas of the experimental field, namely unobstructed area, semi‐unobstructed area and obstructed area. The experimental results demonstrate that the method exhibits superior positioning accuracy compared to traditional methods, enabling effective localization even in obstructed area. [ABSTRACT FROM AUTHOR]

Smartphones with integrated sensors play an important role in people's lives, and in advanced multi-sensor fusion navigation systems, the use of individual sensor information is crucial. Because of the different environments, the weights of the sensors will be different, which will also affect the method and results of multi-source fusion positioning. Based on the multi-source data from smartphone sensors, this study explores five types of information—Global Navigation Satellite System (GNSS), Inertial Measurement Units (IMUs), cellular networks, optical sensors, and Wi-Fi sensors—characterizing the temporal, spatial, and mathematical statistical features of the data, and it constructs a multi-scale, multi-window, and context-connected scene sensing model to accurately detect the environmental scene in indoor, semi-indoor, outdoor, and semi-outdoor spaces, thus providing a good basis for multi-sensor positioning in a multi-sensor navigation system. Detecting environmental scenes provides an environmental positioning basis for multi-sensor fusion localization. This model is divided into four main parts: multi-sensor-based data mining, a multi-scale convolutional neural network (CNN), a bidirectional long short-term memory (BiLSTM) network combined with contextual information, and a meta-heuristic optimization algorithm. [ABSTRACT FROM AUTHOR]

Objectives: The satellite attitude quaternion products have been proposed by International GNSS Service in the third data reprocessing campaign (repro3). These satellite attitude quaternion products are not only contributed to combining the precise satellite products during the eclipse season, but also can improve the reliability of precision point positioning (PPP) when satellites are in abnormal yaw attitude. Methods: The four final and rapid BeiDou-3 satellite navigation system (BDS-3) satellite attitude products provided by Wuhan University (WHU), Geo Forschungs Zentrum and Center for Orbit Determination in Europe have been compared. Attitude model characteristic of BDS-3 with different type from different analysis centers have been also analyzed in the eclipse seasons, and the effect of different satellite model on satellite clock and kinematic PPP have been investigated. Results: The results demonstrate that the BDS-3 yaw angle difference can reach up about 120° from different analysis centers when the sun elevation angle is approximately 0°. In this period, different analysis centers used different attitude models. Furthermore, when the satellite attitude quaternions are used from different analysis centers, the PPP positing accuracy can be improved during the eclipse season. In detail, a significant improvement rate is achieved by using WHU rapid products, compared with nominal attitude strategy, the 3D positioning accuracy of kinematic PPP solutions with satellite attitude quaternions can be improved approximately 18. 4%. Conclusion: Although the positioning accuracy of PPP solutions can be improved by using the publicly BDS-3 attitude model, various attitude strategies may be adopted in different analysis centers. Therefore, in order to obtain reliable PPP results, the satellite attitude quaternions should be used. [ABSTRACT FROM AUTHOR]

Research on augmentation and supplement systems for navigation systems has become a significant aspect in comprehensive positioning, navigation and timing (PNT) studies. The BeiDou-3 navigation satellite system (BDS-3) has constructed a dynamic inter-satellite network to gain more observation data than ground monitoring stations. Low Earth orbit (LEO) satellites have advantages in their kinematic velocity and information carrying rate and can be used as satellite-based monitoring stations for navigation satellites to make up for the distribution limitation of ground monitoring stations. This study constructs multi-source observation links with satellite-to-ground, inter-satellite and satellite-based observation data, proposes an orbit synchronization method for navigation satellites and LEO satellites and verifies the influence thereof on orbit accuracy with different observation data. The experimental results under conditions of real and simulated observation data showed the following: (1) With the support of satellite-based observation links, the orbit accuracy of the BDS-3 MEO satellites could be improved significantly, with a 78% improvement with the simulation data and a 76% improvement with the real data. When the navigation satellites leave the monitoring area of the ground monitoring stations, the accuracy reduction tendency of the orbit prediction could also be slowed down with the support of the LEO satellites and the accuracy could be maintained within centimeters. (2) Comparing the orbit accuracy with the support of the satellite-to-ground observation links, the orbit accuracy of the MEO satellites could be improved by 65.5%, 73.7% and 79.4% with the support of the 6, 12 and 60 LEO satellites, respectively. When the observation geometry and the covering multiplicity meet the basic requirement of orbit determination, the improvements to the orbit accuracy decrease with the growth of LEO satellite numbers. (3) The accuracy of orbit determination with the support of the LEO satellites or the inter-satellite links was at the centimeter level for both, verifying that inter-satellite links and satellite-based links can be used as each other's backups for navigation satellites. (4) The accuracy of orbit determination with the multi-source observation links was also at the centimeter level, which was not better than the results with the support of the satellite-to-ground and inter-satellite links or the satellite-to-ground and satellite-based links. [ABSTRACT FROM AUTHOR]

Low Earth orbit (LEO) satellites have unique advantages in navigation because of their high signal intensity and rapid geometric changes in a short period. In order to solve the problem of constellation performance degradation after a potential failure pertaining one or more medium Earth orbit (MEO) navigation satellites, this paper designs the LEO navigation constellation and considers the task requirements of different stages of constellation deployment. Firstly, the LEO navigation constellation is designed by a non-dominated sorting genetic algorithm II (NSGA-II). The average position dilution of precision (PDOP) is 1.676, which is an improvement compared to the average PDOP offered by the four traditional GNSS. Secondly, the staged deployment of constellation takes into account the degradation of constellation performance caused by the failure of MEO navigation satellites, and the Monte Carlo method is used to analyze the case of three simultaneous satellite failures. The results show that a single satellite failure within each orbital plane and adjacent satellites with close phase separation has a great impact on the performance of the MEO navigation constellation. On this basis, a staged deployment strategy was adopted in order to balance cost, risk, and performance. The three phases deploy 66, 156, and 288 satellites, respectively; as a make-up constellation under contingencies, a navigation enhancement constellation, and an independent navigation constellation, the deployment of the staged sub-constellations meets the mission requirements. The constellation design and staged deployment method proposed in this paper can provide reference for the future study of LEO navigation constellations. [ABSTRACT FROM AUTHOR]

The collaborative use of camera near-field sensors for monitoring the number and status of tourists is a crucial aspect of smart scenic spot management. This paper proposes a near-field perception technical system that achieves dynamic and accurate detection of tourist targets in mountainous scenic areas, addressing the challenges of real-time passive perception and safety management of tourists. The technical framework involves the following steps: Firstly, real-time video stream signals are collected from multiple cameras to create a distributed perception network. Then, the YOLOX network model is enhanced with the CBAM module and ASFF method to improve the dynamic recognition of preliminary tourist targets in complex scenes. Additionally, the BYTE target dynamic tracking algorithm is employed to address the issue of target occlusion in mountainous scenic areas, thereby enhancing the accuracy of model detection. Finally, the video target monocular spatial positioning algorithm is utilized to determine the actual geographic location of tourists based on the image coordinates. The algorithm was deployed in the Tianmeng Scenic Area of Yimeng Mountain in Shandong Province, and the results demonstrate that this technical system effectively assists in accurately perceiving and spatially positioning tourists in mountainous scenic spots. The system demonstrates an overall accuracy in tourist perception of over 90%, with spatial positioning errors less than 1.0 m and a root mean square error (RMSE) of less than 1.14. This provides auxiliary technical support and effective data support for passive real-time dynamic precise perception and safety management of regional tourist targets in mountainous scenic areas with no/weak satellite navigation signals. [ABSTRACT FROM AUTHOR]

The polar motion (PM, including two parameters PMx and PMy) ultra-short-term prediction (1–10 days) is demanded in the real-time navigation of satellites and spacecrafts. Improving the PMx and PMy ultra-short-term predictions accuracies are a key to optimize the performance of these related applications. Currently, the least squares (LS)+autoregressive (AR) hybrid method is regarded as one of the most capable approaches for ultra-short-term predictions of PMx and PMy. The Kalman filter has proven to be effective in improving the ultra-short-term prediction performance of the LS+AR hybrid method, but the PMx and PMy ultra-short-term predictions accuracies are still not able to satisfy some related applications. In order to improve the performance of PM ultra-short-term prediction, it is worth exploring the combinations of existing methods. Throughout the existing predicted methods, the LS+multivariate autoregressive (MAR) hybrid method by using the Kalman filter has the potential to improve the accuracy of PM ultra-short-term prediction. In addition, a PM prediction performance analysis of the LS+MAR hybrid method by using the Kalman filter, namely the LS+MAR+Kalman hybrid method, is still missing. In this contribution, we proposed the LS+MAR+Kalman hybrid method for PM ultra-short-term prediction. The data sets for PM predictions, which range from 1 to 10 days, have been tested based on the International Earth Rotation and Reference Systems Service Earth Orientation Parameter (IERS EOP) 14 C04 series to assess the performance of the LS+MAR+Kalman hybrid model. The experimental results illustrated that the LS+MAR+Kalman hybrid method can effectively execute PMy ultra-short-term predictions. The improvement of PMy prediction accuracy can rise up to 12.69% for 10-day predictions, and the improvement of ultra-short-term predictions is 7.64% on average. [ABSTRACT FROM AUTHOR]

For the relativistic navigation system where the position and velocity of the spacecraft are determined through the observation of the relativistic perturbations including stellar aberration and starlight gravitational deflection, a novel parallel Q-learning extended Kalman filter (PQEKF) is presented to implement the measurement bias calibration. The relativistic perturbations are extracted from the inter-star angle measurement achieved with a group of high-accuracy star sensors on the spacecraft. Inter-star angle measurement bias caused by the misalignment of the star sensors is one of the main error sources in the relativistic navigation system. In order to suppress the unfavorable effect of measurement bias on navigation performance, the PQEKF is developed to estimate the position and velocity, together with the calibration parameters, where the Q-learning approach is adopted to fine tune the process noise covariance matrix of the filter automatically. The high performance of the presented method is illustrated via numerical simulations in the scenario of medium Earth orbit (MEO) satellite navigation. The simulation results show that, for the considered MEO satellite and the presented PQEKF algorithm, in the case that the inter-star angle measurement accuracy is about 1 mas, after calibration, the positioning accuracy of the relativistic navigation system is less than 300 m. [ABSTRACT FROM AUTHOR]

This research tackles the critical challenge of BeiDou signal spoofing in vehicular ad-hoc networks and addresses significant risks to vehicular safety and traffic management stemming from increased reliance on accurate satellite navigation. The study proposes a novel hybrid machine learning framework that integrates Autoencoders and long short-term memory (LSTM) networks with an advanced cryptographic method, attribute-based encryption, to enhance the detection and mitigation of spoofing attacks. Our methodology leverages both real-time and synthetic navigational data in a comprehensive experimental setup that simulates various spoofing scenarios to test the resilience of the proposed system. The findings demonstrate a significant improvement in the accuracy of spoofing detection and the robustness of mitigation strategies by ensuring the integrity and reliability of navigational data. This investigation enhances the existing body of knowledge by demonstrating the effectiveness of integrating machine learning with cryptographic techniques to secure VANETs. Ultimately, it effectively paves the way for future research into adaptive security mechanisms that can dynamically respond to evolving cyber threats. [ABSTRACT FROM AUTHOR]

In the field of navigation and positioning, the inertial navigation system (INS)/global navigation satellite system (GNSS) integrated navigation system is known for providing stable and high-precision navigation services for vehicles. However, in extreme scenarios where GNSS navigation data are completely interrupted, the positioning accuracy of these integrated systems declines sharply. While there has been considerable research into using neural networks to replace the GNSS signal output during such interruptions, these approaches often lack targeted modeling of sensor information, resulting in poor navigation stability. In this study, we propose an integrated navigation system assisted by a novel neural network: an inverted-Transformer (iTransformer) and the application of a frequency-enhanced channel attention mechanism (FECAM) to enhance its performance, called an INS/FECAM-iTransformer integrated navigation system. The key advantage of this system lies in its ability to simultaneously extract features from both the time and frequency domains and capture the variable correlations among multi-channel measurements, thereby enhancing the modeling capabilities for sensor data. In the experimental part, a public dataset and a private dataset are used for testing. The best experimental results show that compared to a pure INS inertial navigation system, the position error of the INS/FECAM-iTransformer integrated navigation system reduces by up to 99.9%. Compared to the INS/LSTM (long short-term memory) and INS/GRU (gated recurrent unit) integrated navigation systems, the position error of the proposed method decreases by up to 82.4% and 78.2%, respectively. The proposed approach offers significantly higher navigation accuracy and stability. [ABSTRACT FROM AUTHOR]

3Cat-4 is the fourth member of the CubeSat series of UPC's NanoSat Lab, and it was selected by the ESA Academy's Fly Your Satellite! program in 2017. This mission aims at demonstrating the capabilities of nano-satellites, and in particular those based in the 1-Unit CubeSat standard, for challenging Earth Observation (EO) using Global Navigation Satellite System-Reflectometry (GNSS-R) and L-band microwave radiometry, as well as for Automatic Identification Systems (AIS). The following study presents the results of the thermal analysis carried out for this mission, evaluating different scenarios, including the most critical cases at both high and low temperatures. The results consider different albedos and orbital parameters in order to establish the optimal temperatures to achieve the best mission performance within the nominal temperatures, and in all operational modes of the satellite. Simulation results are included considering the thermal performance of other materials, such as Kapton, as well as the redesign of the optical properties of the satellite's solar panels. The correlation with the thermal model and the TVAC test campaign was conducted at the ESA ESEC-GALAXIA facilities in Belgium. [ABSTRACT FROM AUTHOR]

Deriving the precise true height electron density profile from the measured ionosonde virtual heights is quite a challenging problem. Recently, Ankita and Tulasi Ram (2023, https://doi.org/10.1029/2023RS007808) presented a new method, Iterative Gradient Correction (IGC) method, for true height analysis that uses HF radio wave propagation path computations to reconstruct the true height profile. Through iterative corrections on electron density gradients between successive points, the IGC method minimizes errors below a specified tolerance at each point and reconstructs a complete electron density profile. The derived profiles from the IGC method are found to be accurate when compared with Incoherent Scatter Radar and Global Navigation Satellite System—Radio Occultation observations. To facilitate true height analysis by IGC method for a wider user community, a MATLAB‐based software has been developed and is outlined in this report. The software can be installed on any Windows platform and is designed with a user‐friendly interface for easy and efficient application by the users. It can analyze multiple scaled ionograms in a single run and outputs the real height profiles in ASCII format. Further, the software also captures important ionospheric parameters such as the base altitudes and peak frequencies of E‐ and F‐layers (e.g., hE, hF, foE, and foF2) etc., from the computed true height profiles and tabulates in a separate output file for the ready use. The software also provides the option for extrapolation of true height profile into top‐side ionosphere up to a user‐specified height and reconstructs the complete vertical electron density profile. Key Points: A new software with user‐friendly interface is developed for true height analysis of ionograms using Iterative Gradient Correction methodIt can compute multiple true height profiles in one run with an option to extrapolate into top‐side ionosphere up to a user‐specified heightIt also captures the important ionospheric parameters such as hE, hF, foE, foF2, etc., for ready use in research/practical applications [ABSTRACT FROM AUTHOR]

A novel probe fed right hand circularly polarized (RHCP) shared aperture antenna with concentric configuration is designed for L5 and S-bands NavIC receiver application. The structure consists of a square loop-type patch antenna for the L5 band, serves as the top radiator, and a concentrically truncated corner patch antenna for the S-band is embedded in the non-radiating portion of the L5 band antenna. The square loop is orthogonally fed with electromagnetically coupled strips with equal power and quadrature phased shift through symmetric vias. These vias are connected to the feeding network, which consists of a Wilkinson power divider that is designed on opposite sides of the ground to mitigate spurious radiations. Furthermore, the S-band antenna, placed inside the L5 band substrate, achieves CP by corner truncation. This technique increases the aperture reuse efficiency and improves the isolation between both radiators. The overall profile of the antenna is 75×75×8mm3 and exhibits a wide impedance bandwidth of 25.5% for the L5 band and 6.5% for the S-band, with an isolation of better than 20dB for both bands. The axial ratio bandwidth achieved is 25.5% and 4.1% for the L5 and S bands, respectively, with boresight gain of 3.57 dBiC and 4.8 dBiC in the L5 band and S-band, respectively. The proposed antenna is based on a shared aperture technique, which has different feeding ports for both bands; thus, it improves the G/T performance and noise figure of the overall system. These characteristics make the proposed antenna suitable for use in NavIC application. [ABSTRACT FROM AUTHOR]

Soil moisture monitoring is a research hotspot in the application of navigation satellite reflected signals. In order to retrieve soil moisture in any period with high precision and solve the problem that soil moisture cannot be retrieved when satellite observation data is partially missing, the principle of generalized extension in engineering science is applied to GNSS-IR technology in the paper. Firstly, the generalized extension approximation method is used to interpolate the precise ephemeris to obtain the altitude angle information of each satellite in each epoch. Then, the generalized extended interpolation and extrapolation models were used to supplement the initial phase of the reflected signal corresponding to the missing data as the input of the inversion model to predict soil moisture. The soil moisture inversion experiment was completed according to the observation data provided by PBO. The results show that the generalized extension method can cope with the missing data of different lengths and distributions in GNSS-IR soil moisture retrieval, When the data were confirmed for 15 days, the correlation coefficient of inversion results was 0.916, RSME was 0.03358 cm3/cm3, and MAE was 0.02912 cm3/cm3, and the correlation coefficient of more than 0.85 can be maintained when the amount of missing data reaches 60 % of the test set. [ABSTRACT FROM AUTHOR]