Search Results (1,353)

Deep space navigation, defined as spacecraft position tracking beyond the lunar orbit, presents significant challenges due to the extremely weak Global Navigation Satellite System (GNSS) signals and severe signal attenuation over interplanetary distances. Traditional terrestrial systems, such as NASA’s Deep Space Network (DSN) and ESA’s ESTRACK, rely on Very Long Baseline Interferometry (VLBI) for angular positioning. However, these systems are limited by relatively short baselines, atmospheric distortions requiring extensive calibration, and reduced line-of-sight (LOS) availability due to Earth’s rotation. Because VLBI angle measurements require at least two simultaneously visible stations, the measurement duty cycle is inherently constrained. This research proposes a complementary deep space navigation approach using space-based interferometry, in which radio signals from the spacecraft are received and cross-correlated onboard Geostationary Earth Orbit (GEO) satellites. By replacing terrestrial VLBI stations with dual GEO platforms, the method significantly extends the effective baseline, removes atmospheric phase errors, and provides near-continuous visibility to deep space targets. Unlike Earth-based systems, GEO-based interferometry maintains persistent mutual visibility between stations, enabling higher measurement availability and more flexible mission support. A complete system model is presented, including the principles of dual-frequency phase-based angular tracking and a structured error budget analysis. Theoretical error analysis indicates that the GEO-based system achieves a total angular error better than 4 nanoradians—within the same order of magnitude as terrestrial VLBI. In particular, the space-based architecture nearly doubles the geometric availability for interferometric tracking while eliminating the need for atmospheric calibration. These results support the feasibility of the GEO-based VLBI concept and motivate continued research, including detailed simulations, hardware implementation, and field validation. Full article

This review provides an extensive overview of the modernization of Global Navigation Satellite System (GNSS), Regional Navigation Satellite System (RNSS), and Satellite-Based Augmentation System (SBAS) up to 28 September 2025. It covers a description of the individual systems, the new launched satellites, and the new civil signals. GNSS includes the United States’ GPS, Russia’s GLONASS, the European Union’s Galileo, and China’s BDS. In the last several years there has been an intensive development of RNSS, which primarily encompass the Japan’s QZSS, India’s IRNSS, and the South Korea’s KPS. The focus of this research is analyzing the possibilities of advancing Position, Navigation, and Timing (PNT) service as well as future perspective and trends in the field of satellite positioning and navigation. SBAS supports satellite systems by providing civil aviation users with corrections and integrity information. Additional to WAAS and EGNOS, this paper examines several more SBAS currently under development. Furthermore, it provides a concise overview and discussion of the above systems, as well as innovations in space technology in the Republic of Croatia. In addition, it emphasizes the influence of political events on the development of satellite systems as well as the role of aerospace companies. Full article

To address the issues of signal loss and insufficient accuracy of traditional GNSS (Global Navigation Satellite System) navigation in agricultural machinery sheds and farm access road environments, this paper proposes a high-precision mapping method for such complex environments and a real-time localization system for agricultural vehicles. First, an autonomous navigation system was developed by integrating multi-sensor data from LiDAR (Light Laser Detection and Ranging), GNSS, and IMU (Inertial Measurement Unit), with functional modules for mapping, localization, planning, and control implemented within the ROS (Robot Operating System) framework. Second, an improved LeGO-LOAM algorithm is introduced for constructing maps of machinery sheds and farm access roads. The mapping accuracy is enhanced through reflectivity filtering, ground constraint optimization, and ScanContext-based loop closure detection. Finally, a localization method combining NDT (Normal Distribution Transform), IMU, and a UKF (Unscented Kalman Filter) is proposed for tracked grain transport vehicles. The UKF and IMU measurements are used to predict the vehicle state, while the NDT algorithm provides pose estimates for state update, yielding a fused and more accurate pose estimate. Experimental results demonstrate that the proposed mapping method reduces APE (absolute pose error) by 79.99% and 49.04% in the machinery sheds and farm access roads environments, respectively, indicating a significant improvement over conventional methods. The real-time localization module achieves an average processing time of 26.49 ms with an average error of 3.97 cm, enhancing localization accuracy without compromising output frequency. This study provides technical support for fully autonomous operation of agricultural machinery. Full article

Owing to the intrinsic sparsity of GNSS signals in the correlation domain, compressed sensing (CS) is attractive for the rapid acquisition of high-dynamic GNSS signals. However, the compressed measurement-associated noise folding inherently amplifies the pre-measurement noise, leading to an inevitable degradation of acquisition performance. In this paper, a novel CS-based GNSS signal acquisition algorithm is, for the first time, proposed with the efficient suppression of the amplified measurement noise and low computational complexities. The offline developed code phase and frequency bin-compressed matrices in the correlation domain are utilized to obtain a real-time observed matrix, from which the correlation matrix of the GNSS signal is rapidly reconstructed via a denoised back-projection and a non-iterative shrinkage-thresholding (NIST) operation. A detailed theoretical analysis and extensive numerical explorations are undertaken for the algorithm computational complexity, the achievable acquisition performance, and the algorithm performance robustness to various Doppler frequencies. It is shown that, compared with the classic orthogonal matching pursuit (OMP) reconstruction, the NIST reconstruction gives rise to a 3.3 dB improvement in detection sensitivity with a computational complexity increase of <10%. Moreover, the NIST-reconstructed CS acquisition algorithm outperforms the conventional CS acquisition algorithm with frequency serial search (FSS) in terms of both the acquisition performance and the computational complexity. In addition, a variation in the detection sensitivity is observed as low as 1.3 dB over a Doppler frequency range from 100 kHz to 200 kHz. Full article

Wireless low earth orbit (LEO) satellite communication ground terminals need to perform an initial time and frequency synchronization to access to the LEO system. Initial synchronization consists of three steps: detecting the presence of the LEO satellite downlink signal, synchronizing the terminal receiver to the current Doppler frequency shift and performing Doppler pre-compensation before uplink signal transmission, and ensuring low probability of false alarm at low SNR in the LEO uplink receiver. This article explains this three step synchronization procedure in detail. The major advantage is that the synchronization procedure can be carried out even without a priori knowledge of the satellite orbit ephemeris or any sort of GNSS navigation data. Initial synchronization is of particular importance for typical LEO uplink signals which are formed of short radio bursts. The packet detection in burst traffic radio systems is a crucial task to accomplish start of frame detection. It triggers the start of the digital receiver algorithms to demodulate the incoming uplink burst. The packet detection is accomplished by cross-correlation and threshold detection which show significant probability of false alarm in low signal to noise (SNR) regions. Hence, before running a stable uplink connection, the terminal must accomplish the proposed initial synchronization procedure, as outlined in this article. Full article

With location-based services becoming more common, smartphone global navigation satellite systems (GNSS) have begun to play a significant role in daily life. Providing reliable location information to smartphone users requires considering localization uncertainty, which varies with the surrounding environment. In this study, we developed an environmental context indicator (ECI) to provide interpretable, continuous information on GNSS observation quality using carrier-to-noise density ratio (C/N₀), the number of visible satellites, and positional dilution of precision (PDOP). The ECI was developed using a Samsung Galaxy S21+ and satellite signals from global positioning system (GPS) L1/L5, Galileo E1/E5, and BeiDou B1, consisting of three components: a real-valued indicator ranging from 0 to 6, an integer-valued indicator ranging from 1 to 5, and a probability density ratio representing the reliability of the integer-valued indicator. In experimental results, the ECI reflected the variations in the observation environment and corresponding quality changes. ECI values were lowest in open areas, increasing when approaching an urban area, and reaching their maximum in indoor environments where signal reception is severely limited. Consequently, ECI was influenced by building density, exhibiting large and frequent changes, particularly in urban areas. Full article

Current drone navigation systems primarily rely on Global Navigation Satellite Systems (GNSSs), but their signals are susceptible to interference, spoofing, or suppression in complex environments, leading to degraded positioning performance or even failure. To enhance the positioning accuracy and robustness of low-altitude drones in satellite-denied environments, this paper investigates an absolute visual localization solution. This method achieves precise localization by matching real-time images with reference images that have absolute position information. To address the issue of insufficient feature generalization capability due to the complex and variable nature of ground scenes, a visual-based image retrieval algorithm is proposed, which utilizes a fusion of shallow spatial features and deep semantic features, combined with generalized average pooling to enhance feature representation capabilities. To tackle the registration errors caused by differences in perspective and scale between images, an image registration algorithm based on cyclic consistency matching is designed, incorporating a reprojection error loss function, a multi-scale feature fusion mechanism, and a structural reparameterization strategy to improve matching accuracy and inference efficiency. Based on the above methods, a hierarchical absolute visual localization system is constructed, achieving coarse localization through image retrieval and fine localization through image registration, while also integrating IMU prior correction and a sliding window update strategy to mitigate the effects of scale and rotation differences. The system is implemented on the ROS platform and experimentally validated in a real-world environment. The results show that the localization success rates for the h, s, v, and w trajectories are 95.02%, 64.50%, 64.84%, and 91.09%, respectively. Compared to similar algorithms, it demonstrates higher accuracy and better adaptability to complex scenarios. These results indicate that the proposed technology can achieve high-precision and robust absolute visual localization without the need for initial conditions, highlighting its potential for application in GNSS-denied environments. Full article

Big L days are days when the lunar semidiurnal variation M₂ in the ionosphere is strongly enhanced by a factor of 2 or more. The worldwide network of ground-based receivers for the Global Navigation Satellite System (GNSS) has monitored the ionospheric total electron content (TEC) since 1998. The derived world maps of TEC are provided by the International GNSS Service (IGS) and allow the study of the characteristics of big L days in TEC. In the data analysis, the signal of the lunar semidiurnal variation M₂ in TEC is separated from the solar semidiurnal variation S₂ by means of windowing in the spectral domain. The time series of the M₂ amplitude often shows enhancements of M₂ (big L days) a few days after sudden stratospheric warmings (SSWs). The M₂ amplitude can reach values of 8 TECU. The M₂ composite of all SSWs from 1998 to 2024 shows that the M₂ amplitude is enhanced after the central date of the SSW. Regions in Southern China and South America show stronger effects of big L days. Generally, the effects of big L days on TEC show latitudinal and longitudinal dependencies. Full article

Accurate and reliable localization is crucial for autonomous systems operating in dynamic and semi-structured environments, such as precision agriculture and outdoor robotics. Advances in Global Navigation Satellite System (GNSS) technologies, particularly Differential GPS (DGPS) and Real-Time Kinematic (RTK) positioning, have significantly enhanced position estimation precision, achieving centimeter-level accuracy. However, GNSS-based localization continues to encounter inherent limitations due to signal degradation and intermittent data loss, known as GNSS outages. This paper proposes a novel complementary RTK-like position increment prediction model with the purpose of mitigating challenges posed by GNSS outages and RTK signal discontinuities. This model can be integrated with a Dual Extended Kalman Filter (Dual EKF) sensor fusion framework, widely utilized in robotic navigation. The proposed model uses time-synchronized inertial measurement data combined with the velocity inputs to predict GNSS position increments during periods of outages and RTK disengagement, effectively substituting for missing GNSS measurements. The model demonstrates high accuracy, as the total aDTW across 180 s trajectories averages at 1.6 m while the RMSE averages at 3.4 m. The 30 s test shows errors below 30 cm. We leave the actual Dual EKF fusion to future work, and here, we evaluate the standalone deep network. Full article

Low Earth orbit (LEO) satellites, characterized by low altitudes, high velocities, and strong ground signal reception, have become an essential and dynamic component of modern global navigation satellite systems (GNSS). However, orbit decay induced by atmospheric drag poses persistent challenges to maintaining stable trajectories. Frequent orbit maneuvers, though necessary to sustain nominal orbits, introduce significant difficulties for precise orbit determination (POD) and navigation augmentation, especially under complex operational conditions. Unlike most existing methods that rely on Two-Line Element (TLE) data—often affected by noise and limited accuracy—this study directly utilizes onboard GNSS observations in combination with real-time precise ephemerides. A novel time-series indicator is proposed, defined as the geometric root-mean-square (RMS) distance between reduced-dynamic and kinematic orbit solutions, which is highly responsive to orbit disturbances. To further enhance robustness, a sliding window-based adaptive thresholding mechanism is developed to dynamically adjust detection thresholds, maintaining sensitivity to maneuvers while suppressing false alarms. The proposed method was validated using eight representative maneuver events from the GRACE-FO satellites (May 2018–June 2022), successfully detecting seven of them. One extremely short-duration maneuver was missed due to the limited number of usable GNSS observations after quality-control filtering. To examine altitude-related applicability, two Sentinel-3A maneuvers were also analyzed, both successfully detected, confirming the method’s effectiveness at higher LEO altitudes. Since the thrust magnitudes and durations of the Sentinel-3A maneuvers are not publicly available, these cases primarily serve to verify applicability rather than to quantify sensitivity. Experimental results show that for GRACE-FO maneuvers, the proposed method achieves near-real-time responsiveness under long-duration, high-thrust conditions, with an average detection delay below 90 s. For Sentinel-3A, detections occurred approximately 7 s earlier than the reported maneuver epochs, a discrepancy attributed to the 30 s observation sampling interval rather than methodological bias. Comparative analysis with representative existing methods, presented in the discussion section, further demonstrates the advantages of the proposed approach in terms of sensitivity, timeliness, and adaptability. Overall, this study presents a practical, efficient, and scalable solution for real-time maneuver detection in LEO satellite missions, contributing to improved GNSS augmentation, space situational awareness, and autonomous orbit control. Full article

Operational satellites are critical to modern aerospace infrastructure, supporting essential services such as communication, navigation, and global surveillance. However, the increasing density of satellites and space debris in Earth’s orbit has heightened the risk of collisions, thereby threatening network reliability. This study addresses the dual challenge of managing space debris and enhancing satellite network performance by applying the concept of acyclic matching from graph theory to satellite constellations modeled as honeycomb networks. Acyclic matching identifies edge subsets without shared nodes or cycles, enabling static signal rerouting through pre-computed, loop-free paths. This ensures fault tolerance and efficient resource allocation in increasingly complex satellite constellations. The proposed method derives the general solution for acyclic matching cardinality and determines the maximum matching set for n-dimensional honeycomb networks. This technique aligns with emerging trends in autonomous fault-tolerant systems and adaptive routing protocols, proving particularly relevant for large-scale satellite systems such as Starlink and global navigation constellations. By providing alternative communication paths in the event of satellite or link failures, the approach significantly enhances the scalability, reliability, and resilience of satellite networks, ensuring uninterrupted service and improved space traffic management in the face of rising orbital congestion. Full article

The accurate localization of radio frequency (RF) emitters plays a critical role in spectrum monitoring, public safety, and defense applications, particularly in environments where global navigation satellite systems are limited. This study investigates the feasibility of a single unmanned aerial vehicle (UAV) equipped with a Doppler-based software-defined radio sensor to localize modern RF sources without the need for external infrastructure or multiple UAVs. A custom-designed localization system was developed and tested using the L3Harris AN/PRC-152A tactical radio, which represents a class of real-world, dual-use emitters with lower frequency stability than laboratory signal generators. The approach was validated through both emulation studies and extensive field experiments under realistic conditions. The results show that the proposed system can localize RF emitters with an average error below 50 m in 80% of cases even when the transmitter is more than 600 m away. Performance was evaluated across different carrier frequencies and acquisition times, demonstrating the influence of signal parameters on localization accuracy. These findings confirm the practical applicability of Doppler-based single-UAV localization methods and provide a foundation for further development of lightweight, autonomous RF emitter tracking systems for critical infrastructure protection, spectrum analysis, and tactical operations. Full article

Global Navigation Satellite Systems (GNSSs) are widely used in many applications but can be out of use in some critical conditions. Hybrid pseudolite systems utilize ground and aero stations as pseudolites to provide positioning signals for users within the covered area. The positioning accuracy is an important performance parameter for the pseudolite system and is decided by the layout of the pseudolites. This paper proposes a layout optimization method based on an Incremental Geometric Dilution of Precision (IGDOP) model. The IGDOP considers the GDOP value into two parts. One is the fixed part corresponding to the ground stations, and the other is the varying part related to the movable aero pseudolite stations. Thus, when the aero pseudolites’ position changes, the new GDOP value could be obtained only by calculating the varying part. Then, a Monte-Carlo Genetic Algorithm (MC-GA) is proposed for the IGDOP calculation for a minimum value. This algorithm comprises two main components: first, it leverages the random sampling capability of the Monte-Carlo Algorithm to provide sample points that satisfy the sample space for the subsequent Genetic Algorithm, which serve as individuals of the initial population; subsequently, it searches for the minimum value of IGDOP via the Genetic Algorithm and determines the optimized layout of the hybrid pseudolite system. Simulations are carried out using a hybrid pseudolite system with four fixed stations and n movable stations. The results validate the developed IGDOP model and show that the approach enables scalable optimization of n − 1 movable stations via four fixed stations, providing an efficient, low-complexity solution to the system layout optimization. Full article

Global Navigation Satellite System (GNSS) spoofing, which manipulates PVT solutions through false measurements, increasingly threatens GNSS reliability and user safety. However, most existing simulator-based spoofers, constrained by their inability to access real-time ionospheric information (e.g., Global Ionosphere Maps, GIMs) from external sources, struggle to replicate authentic total electron content (TEC) along each signal propagation path accurately and in a timely manner. In contrast, widespread dual-frequency (DF) receivers with access to the internet can validate local TEC measurements against external references, establishing a pivotal spoofing detection distinction. Here, we propose an Ionospheric Information-Assisted Spoofing Detection Technique (IIA-SDT), exploiting the inherent consistency between TEC values derived from DF pseudo-range measurements and external references in spoofing-free scenarios. Spoofing probably disrupts this consistency: in simulator-based full-channel spoofing where all channels are spoofed, the inaccuracies of the offline ionospheric model used by the spoofer inevitably cause TEC mismatches; in partial-channel spoofing where the spoofer fails to control all channels, an unintended PVT deviation is induced, which also causes TEC deviations due to the spatial variation of the ionosphere. Basic principles and theoretical analysis of the proposed IIA-SDT are elaborated in the paper. Simulations using ionospheric data collected from 2023 to 2024 at a typical mid-latitude location are conducted to evaluate IIA-SDT performance under various parameter configurations. With a window length of 5 s and satellite number of 8, the annual average detection probability approximates 75% at a false alarm rate of $1\times {10}^{-3}$, with observable temporal variations. Field experiments across multiple scenarios further validate the spoofing detection capability of the proposed method. Full article

The area encompassing the Campi Flegrei and Vesuvio volcanoes, situated approximately 25 km apart and bisected by the city of Naples, Italy, is recognised as one of the most hazardous regions globally. In recent decades, the Campi Flegrei caldera has undergone significant changes in its monitored geophysical, geochemical and geodetical signals. The most recent, ongoing unrest began in 2005, resulting in an uplift of over 150 centimetres in the area of maximum uplift. Previous analyses of deformation data from ERS/ENVISAT (available up to 2010) and Sentinel-1 (available since 2015) Synthetic Aperture Radar (SAR) imagery, as well as global navigation satellite system data, have suggested that the shape of the deformation field at Campi Flegrei has remained constant and that the area around Vesuvio experienced a slight subsidence in the early 2000s, concurrently with a change in the sign of the ground deformation (from subsidence to uplift) at Campi Flegrei. This study presents and provides the ground displacement time series obtained from RADARSAT-2 images of the entire volcanic area from 2010 to 2015, thus filling the temporal gap between the ERS/ENVISAT and Sentinel-1 missions. The time series were generated using a bespoke procedure, based on the Sentinel Application Platform and the GMTSAR software. The validity of the displacement time series has been confirmed through comparison with continuous Global Positioning System data from the Neapolitan Volcanoes Continuous GPS network. Analysis of RADARSAT-2 ground displacements indicates that velocities in the vicinity of Vesuvio were no greater than a few millimetres per year, and no discernible deformation pattern is evident. Consequently, given the uncertainty in Differential Interferometry Synthetic Aperture Radar (DInSAR) measurements, there is no evidence to suggest deformation activity close to Vesuvio between 2010 and 2015. In contrast to Vesuvio, significant deformation is evident in the Campi Flegrei area. The shape of the ground displacement field remained constant between 2010 and 2015, within the uncertainty of DInSAR measurements. The mean upward velocity reaches a maximum of approximately 5 cm y⁻¹, while the mean eastward velocity reaches 2.4 cm y⁻¹. Full article