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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]

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]

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]

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]

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]

Summary: India has developed its own regional navigation satellite system called the Indian Regional Navigation Satellite System (IRNSS), also known as Navigation with Indian Constellation (NavIC). IRNSS/NavIC provides standard positioning and timing services for civilians and restricted services for authorized users. In this paper, single point positioning is implemented on the NavIC receiver data. Estimation techniques of the least squares method and extended Kalman filter are implemented after applying broadcast‐based clock corrections, orbit computation, relative time correction, and ionosphere delay correction for single and dual frequency. A data extraction and storage module is developed to store computed parameters at every intermediate stage in separate files. This is followed by an error plotter module to plot the extracted parameters for each satellite and to separately analyze their performance and the obtained errors. The estimated receiver position is visualized on Google Earth. The absolute error in both estimation techniques ranges between 5 and 15 m throughout the period. [ABSTRACT FROM AUTHOR]

Spaceborne global navigation satellite system-reflectometry has become an effective technique for Soil Moisture (SM) retrieval. However, the accuracy of global SM retrieval using a single model is limited due to the complexity of land surface. Introducing redundant ancillary data may also result in over-reliance problems. Therefore, we propose a method for SM retrieval that considers geographical disparities using the data from Cyclone GNSS (CYGNSS) observations and Soil Moisture Active and Passive (SMAP) product. Based on the CYGNSS effective reflectivity and ancillary datasets of SMAP, we establish five models for each grid with different parameters to achieve global SM retrieval. Subsequently, an optimal model, determined by the performance indicator, is used for SM retrieval. The results show that the root mean square error S RMSE with the improved method is decreased by 9.1% using SMAP SM as reference with the S RMSE = 0.040 cm3/cm3 compared with using single reflectivity-temperature-vegetation method. Additionally, using the in-situ SM of International Soil Moisture Network as reference, the overall correlation coefficient R and S RMSE values with the improved method are 0.80 and 0.064 cm3/cm3, respectively. The average R of the chosen sites is increased by 22.7%, and the average S RMSE is decreased by 8.7%. The results indicate that the improved method can better retrieve SM in both global and local scales without redundant auxiliary data. [ABSTRACT FROM AUTHOR]

Star sensors play a crucial role as high-precision optical attitude navigation devices in satellite attitude control systems. The CMOS image sensor is an important component of the imaging system of the star sensor and experiences performance degradation due to the total ionizing dose effect and displacement damage effect in the radiation environment of its long-term operational workspace. As a result, the detection capability and attitude positioning accuracy of the star sensor gradually deteriorate. The performance of CMOS image sensors can be partially restored after annealing but the impact on the performance of star sensors is unclear. This study conducted 100 MeV proton irradiation experiments with different fluences on CMOS image sensors and performed room temperature and high temperature annealing treatments. By testing and analyzing the performance of star sensors equipped with irradiated and different annealing treatments on CMOS image sensors, the impact mechanism of CMOS image sensor radiation damage and annealing recovery on the performance variation of star sensors was obtained. This study provides theoretical support for reliability of long-term in-orbit star sensors. [ABSTRACT FROM AUTHOR]

Objectives: The BeiDou-3 satellite navigation system (BDS-3) can provide real-time precise point positioning (PPP) services to China and neighboring regions through PPP-B2b signals. Because PPPB2b signals do not contain ionospheric model products, the current positioning research mainly adopts ionospheric-free combination. The positioning accuracy can reach decimeter level, but requires about 30 min of convergence time. In this paper, aiming at the long convergence time of PPP-B2b positioning, the improvement of positioning convergence performance based on ionospheric model products is analyzed. Methods: Quasi-4-dimensional ionospheric modeling is introduced into regional ionospheric delay modeling in China and four schemes of 50,100,150 and 200 reference stations uniformly distributed in China (day of year 201—207) are adopted for ionospheric modeling. Results: The results show that when the number of stations used in ionospheric modeling increases from 50 to 200, the accuracy of ionospheric model products increases from 2-3 TECU to better than 0.8 TECU. Compared with the current ionospheric-free combined PPP, the convergence time of BDS-3 dynamic PPP can be deceased by 77%. In addition, the convergence time of GPS+BDS-3 dynamic PPP is reduced from 13.51 min to 4.45 min. Conclusions: High-precision ionospheric model products can significantly shorten the convergence time of PPP-B2b. [ABSTRACT FROM AUTHOR]

Global navigation satellite system (GNSS) integrity monitoring (IM) has been introduced in aviation, but remains challenging for urban scenarios because of limited satellite visibility and strong multipath and non-line-of-sight effects. Consequently, factors such as limited measurement redundancy and inaccurate uncertainty modeling significantly compromise positioning and IM performance. To alleviate these issues, this paper proposes an integrity-constrained factor graph optimization model for GNSS positioning augmented by switch variables. In contrast to conventional IM methods, this method enhances redundancy through the factor graph structure. Instead of directly excluding measurements, the proposed method reweights the measurements by using switch variables to satisfy a chi-square test constraint within the optimization, ultimately yielding optimal positioning accuracy. Moreover, a proper protection level that conservatively bounds the positioning error can be derived by using the modified weighting matrix under a single-fault assumption. The effectiveness of the proposed method was verified based on data sets collected in open-sky and urban-canyon areas in Hong Kong. [ABSTRACT FROM AUTHOR]

CubeSats hold promise for various applications, but their viability in demanding missions such as future low Earth orbiting position, navigation, and timing (LEO-PNT) systems hinges on higher orbital accuracy and reliable attitude information. To address these challenges, we present an array-aided combined precise orbit and attitude determination model with an optimal solution. In the estimation process, multi- and affine-constrained models are used to precisely determine the attitude, and then, highly precise observations for an antenna array are reconstructed based on fixed ambiguities and a decorrelation step. Validations confirm the significance of integer ambiguities in the model, highlighting the cost-effectiveness of this model compared with star trackers for attitude determination. The reconstructed observations outperform the original observations, leading to improved orbital components, with the three-dimensional root mean square (RMS) equal to 4.1 cm. The observation residuals are smoother, with an RMS of 6 mm, half of that obtained via a single antenna. The developed models offer great potential for CubeSats, advancing their orbit and attitude determination capabilities. [ABSTRACT FROM AUTHOR]

The first overarching objective of the Space Agenda 2030 is to strengthen the role of the space sector as a major driver of sustainable development. To achieve this objective, the European Space Agency launched already 10+ years ago the ESA Business Applications Programme to foster the adoption of space technologies in non-space sectors, promoting the development of commercial satellite-based projects (i.e., projects developing business applications based on Earth Observation, Satcom and Navigation satellite technologies and data) and contributing to achieving Sustainable Development Goals (SDGs). While space technologies undeniably offer substantial societal benefits, there exists an opportunity to provide professionals and academics with a comprehensive perspective on the ongoing progress of commercial satellite-based projects in their vital role in advancing the achievement of Sustainable Development Goals (SDGs) and tackling Grand Challenges. Our research aims to clarify commercial satellite-based applications' direct and indirect impacts on SDGs and their features contributing to achieving them. We develop a taxonomy of the ESA Business Applications programme portfolio, analysing 603 commercial satellite-based applications developed between 2014 and 2022 across 34 variables (including SDGs directly or indirectly impacted), sourced from the program's web pages. We perform descriptive statistics and exploratory data analysis to present commercial satellite-based applications' direct or indirect impact on the 169 SDG targets. Finally, we describe the features of commercial satellite-based projects (e.g., geographical scope, satellite technology adopted, non-space domains of application) contributing to the SDGs' achievement. Our results show that 603 commercial satellite-based applications impact at least one SDG. Overall, SGD3 is the most impacted (136, 22 %), followed by SDG11 (105, 17 %) and SDG2 (78, 12 %). 257 Earth Observation-based applications mostly impact SDG2 (58, 23 %), SDG15 (38, 15 %) and SDG11 (34, 13 %). 230 Satellite Navigation-based applications mostly impact SDG3 (68, 30 %), SDG11 (52, 23 %) and SDG6 (22, 10 %). 116 Satellite communication-based applications mostly impact SDG3 (33, 28 %), SDG11 (16, 14 %) and SDG4 (15, 13 %). Moreover, we identify 14 application domains, and for each of them, we investigate their impact on SDGs. The application domains that mainly impact SDGs are Health (91, 16 %), Food and Agriculture (85,15 %), and Energy (51, 9 %). Our research demonstrates and strengthens the space sector's role as a major driver of sustainable development. Researchers may adopt the methodology in other contexts, overcoming the geographical and data accessibility limitations of our research. • EO and GNSS-based applications demonstrate their value across diverse sectors and end-users. • Earth Observation-based applications mostly impact SDG2, SDG15, and SDG11. • Satellite Navigation-based applications mostly impact SDG3, SDG11, and SDG6. • Satellite communication-based applications mostly impact SDG3, SDG11, and SDG4. • Businesses tend to invest mainly satellite-based applications impacting SDGs 3, 11, 12, and 15. [ABSTRACT FROM AUTHOR]

The flex power technology in satellite navigation systems enhances anti-jamming capabilities but can impact the quality of GPS observations and the accuracy of low Earth orbit determination, such as GRACE Follow-On (GRACE-FO) mission. This study investigates the influence of GPS flex power on Hatch-Melbourne-Wübbena (HMW) linear combinations and GRACE-FO kinematic orbits from January 1 to September 30, 2020. Epoch-differenced K-Band Ranging (KBR) data is introduced in orbit determination during the flex power period to improve both absolute and inter-satellite relative accuracy. The analysis indicates that the influence of early flex power (before February 13, 2020) on HMW combinations and orbits is minimal, whereas the effect of later flex power (after February 14, 2020) is significant: (1) HMW combinations exhibit notable systematic discontinuities even with elevation angles greater than 50 degrees, causing the fixing rate of wide-lane ambiguities to drop from 96 % to 80 %. (2) Kinematic absolute orbits show significant deteriorations of approximately 9 mm and 4 mm in the three-dimensional direction for float and integer ambiguity resolution (FAR and IAR), while relative accuracy of FAR and IAR orbits decreases by 50 % and 46 %, respectively. However, using epoch-differenced KBR (DKBR) data, the accuracy of absolute orbits could be increased by up to 15 % and the accuracy of relative orbits could be improved by at least 69 %, which showcases a positive effect. Thus, this can be considered as an alternative method to improve the accuracy of GRACE-FO orbit during the flex power period. [ABSTRACT FROM AUTHOR]

Compaction quality plays a vital role in the long-term performance of highways, thereby making quality control (QC) of compaction an essential aspect in highway projects. The prevalent approach regarding QC of compaction primarily depends on manual manipulation of compaction parameters during the construction process and sporadic testing after completion. However, the former method is significantly affected by human factors, whereas the latter entails destructive detection and low efficiency; the latter method also fails to provide a comprehensive representation of the state of compaction across the entire work area of highway projects. Consequently, to achieve QC of compaction, this study used roller-integrated compaction monitoring (RICM) technology combined with the real-time kinematic-Beidou navigation satellite system (RTK-BDS). Initially, the compaction meter value (CMV) and compaction power per unit volume (E) were chosen as the real-time monitoring indexes for assessing the quality of compaction. Subsequently, a case study on the Hengyong Highway Project in China was conducted. The findings revealed that CMV exhibited a stronger correlation with compactness, resulting in smaller data dispersion and higher data stability. Thus, this study chose CMV as the characterization index of the compaction quality of high and low liquid limit (ωL) silt subgrades and constructed a fast compaction quality assessment method based on CMV and the spline interpolation method based on Green's function to obtain estimates for compaction quality over the entire work area, enabling QC of silt subgrades. The results showed that the proposed method facilitated a swift and uninterrupted evaluation of the compaction quality over the entire construction area. Thus, the proposed method can facilitate the effective prevention of compaction quality defects, thus enhancing the overall quality of highways. [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]

Earth Orientation Parameters (EOP) are essential for monitoring Earth’s rotational irregularities, impacting satellite navigation, space exploration, and climate forecasting. This study introduces a hybrid prediction model combining least-squares (LS) and vector autoregression (VAR) to improve Earth’s Pole Coordinates (x, y) forecast accuracy. Using daily sampled IERS EOP 20 C04 data from 2013 to 2023, we conducted 1,000 yearly random trials, performing 48 forecasts per year. Our method evaluates six data combinations, including primary variables (x, y) and their derivatives ( x ̇ , y ̇ $\dot{x},\dot{y}$ ). Results show a systematic improvement in prediction accuracy, especially for ultra-short-term forecasts (10 days into future), with derivative information stabilizing the solutions. The best-performing combination ( x , y , x ̇ , y ̇ $x,y,\dot{x},\dot{y}$ ) achieved a mean absolute prediction error (MAPE) reduction (with respect to the reference data combination – x, y) of up to 8 % for the y and 7 % for the x over a whole 30-day forecast horizon. These findings highlight the effectiveness of incorporating derivatives of polar motion time series into prediction procedure. [ABSTRACT FROM AUTHOR]

We present the determination of the ground-state hyperfine splitting ( ν HFS ) in laser-cooled 171Yb+ ions using our microwave quantum frequency standard (QFS). Employing Ramsey spectroscopy in a closed-loop measurement configuration, we have achieved a ν HFS value of 12 642 812 118 469.0(8) mHz with a fractional uncertainty of 6.6 × 10 − 14 . This result aligns with previously reported values and represents the highest accuracy reported to date for such measurements conducted in a single-shot closed-loop configuration, without averaging over multiple dates. The development of this accurate 171Yb+ microwave QFS holds promise as a transportable time-frequency reference for satellite navigation systems. [ABSTRACT FROM AUTHOR]

Pseudorange bias refers to the receiver-dependent and satellite-dependent constant bias in the pseudorange resulting from the nonideal characteristics of a signal. The impact of pseudorange bias on high-precision satellite navigation services has long been ignored. This paper proposes a pseudorange bias calibration method for two collocated receivers. Then, we calibrate pseudorange biases for two types of collocated receivers at a monitoring station within China and evaluate their impact on two high-precision services: BeiDou Navigation Satellite System 3 (BDS-3) dual-frequency pseudorange augmentation and precise point precision (PPP). Theoretical analysis reveals that the calibrated pseudorange biases contribute 17.2% and 7.7% to the user equivalent ranging error (UERE) of BDS-3 and Global Positioning System (GPS) dual-frequency pseudorange augmentation, respectively, and that the convergence time of the GPS static and kinematic PPP increases from 6 min and 26 min to 19 min and 58 min, respectively. The experimental results indicate that the calibrated pseudorange biases are consistent as the receiver location and time vary. The spatial distribution consistency is generally better than 0.1 m, and the temporal consistency is better than 0.15 m. The pseudorange biases for BDS-3 B1C and B2a are approximately 0.7 m and 0.1 m, respectively, whereas those for GPS L1C/A and L2P are both approximately 0.25 m. Furthermore, The results show that after correction of the pseudorange biases, the average convergence time for BDS-3/GPS static PPP decreases from 48.83/24.03 min to 38.54/21.12 min, respectively, a decrease of approximately 21%/12%. For BDS-3/GPS/BDS-3 + GPS kinematic PPP, the average convergence time decreases from 109.53/45.10/39.15 min to 62.99/40.83/22.94 min, respectively, a decrease of approximately 42%/41%/9%. Similarly, the three-dimensional positioning accuracy for BDS-3/GPS/BDS-3 + GPS dual-frequency pseudorange augmentation improves from 3.25/3.94/2.49 m to 2.65/3.69/2.16 m, respectively, increasing by approximately 6.3%, 18.5%, and 13.3%, respectively. The above analysis and experiments demonstrate that pseudorange bias is an important error source affecting both dual-frequency pseudorange augmentation and PPP services. [ABSTRACT FROM AUTHOR]

Soil moisture data with both a fine spatial scale and a short global repeat period would benefit many hydrologic and climatic applications. Since the radar transmitter malfunctioned on NASA's Soil Moisture Active Passive (SMAP) in 2015, SMAP soil moisture has been downscaled using numerous alternative fine-resolution data. In this paper, we describe the creation and validation of a new downscaled 3 km soil moisture dataset, which is the culmination of previous work. We downscaled SMAP enhanced 9 km brightness temperatures by merging them with L-band Cyclone Global Navigation Satellite System (CYGNSS) reflectivity data, using a modified version of the SMAP active–passive brightness temperature algorithm. We then calculated 3 km SMAP/CYGNSS soil moisture using the resulting 3 km SMAP/CYGNSS brightness temperatures and the SMAP single-channel vertically polarized soil moisture algorithm (SCA-V). To remedy the sparse daily coverage of CYGNSS data at a 3 km spatial resolution, we used spatially interpolated CYGNSS data to downscale SMAP soil moisture. 3 km interpolated SMAP/CYGNSS soil moisture matches the SMAP repeat period of ~2–3 days, providing a soil moisture dataset with both a fine spatial scale and a short repeat period. 3 km interpolated SMAP/CYGNSS soil moisture, upscaled to 9 km, has an average correlation of 0.82 and an average unbiased root mean square difference (ubRMSD) of 0.035 cm3/cm3 using all SMAP 9 km core validation sites (CVSs) within ±38° latitude. The observed (not interpolated) SMAP/CYGNSS soil moisture did not perform as well at the SMAP 9 km CVSs, with an average correlation of 0.68 and an average ubRMSD of 0.048 cm3/cm3. A sensitivity analysis shows that CYGNSS reflectivity is likely responsible for most of the uncertainty in downscaled SMAP/CYGNSS soil moisture. The success of 3 km SMAP/CYGNSS soil moisture demonstrates that Global Navigation Satellite System–Reflectometry (GNSS-R) observations are effective for downscaling soil moisture. [ABSTRACT FROM AUTHOR]

With the increase in the number of Global Navigation Satellite System (GNSS) satellites and their operating frequencies, richer observation data are provided for the tightly coupled Global Navigation Satellite System/Inertial Navigation System (GNSS/INS). In this paper, we propose an efficient and robust combined navigation scheme to address the key issues of system accuracy, robustness, and computational efficiency. The tightly combined system fuses multi-source data such as the pseudo-range, the pseudo-range rate, and dual-antenna observations from the GNSS and the horizontal attitude angle from the vertical gyro (VG) in order to realize robust navigation in a sparse satellite observation environment. In addition, to cope with the high computational load faced by the system when the satellite observation conditions are good, we propose a weighted quasi-optimal satellite selection algorithm that reduces the computational burden of the navigation system by screening the observable satellites while ensuring the accuracy of the observation data. Finally, we comprehensively evaluate the proposed system through simulation experiments. The results show that, compared with the loosely coupled navigation system, our system has a significant improvement in state estimation accuracy and still provides reliable attitude estimation in regions with poor satellite observation conditions. In addition, in comparison experiments with the optimal satellite selection algorithm, our proposed satellite selection algorithm demonstrates greater advantages in terms of computational efficiency and engineering practicability. [ABSTRACT FROM AUTHOR]

In August 2023, Xiaomi unveiled the Redmi K60 Ultra, the first multi-frequency smartphone integrated with BeiDou-3 Navigation Satellite System Precise Point Positioning (PPP-B2b) services and employing PPP technology as the primary positioning method. The positioning enhancement service is provided by the Assisted Global Navigation Satellite System (A-GNSS) location platform developed by the China Academy of Information and Communications Technology. The signaling interaction between the server and the users strictly adheres to the Third Generation of Mobile Communications Technology Partnership Project Long-Term Evolution Positioning Protocol and the Open Mobile Alliance Secure User Plane Location framework. To comprehensively evaluate the Redmi K60 Ultra's capabilities, this study designed six distinct experimental scenarios and conducted comprehensive research on multi-frequency and multi-GNSS observation noise, Time to First Fix (TTFF), as well as the performance of both GNSS-based and network-based positioning. Experimental results indicate that the GNSS chipset within the Redmi K60 Ultra has achieved a leading position in the consumer market concerning supported satellite constellations, frequencies, and observation accuracy, and is comparable to some low-cost GNSS receivers. A-GNSS positioning can reduce the TTFF from 30 to under 5 s, representing an improvement of over 85% in the cold start speed compared to a standalone GNSS mode. The positioning results show that the A-GNSS PPP-B2b service can achieve positioning performance with RMS errors of less than 1.5 m, 2.5 m, and 4 m in open-sky, realistic, and challenging urban environments. Compared to GNSS-based positioning, cellular network-based Observed Time Difference of Arrival (OTDOA) positioning achieves an accuracy ranging from tens to hundreds of meters in various experimental scenarios and currently functions primarily as coarse location determination. Additionally, this study explores the potential of the Three-Dimensional Mapping-Aided (3DMA) GNSS algorithm in detecting Non-Line-of-Sight signals and enhancing positioning performance. The results indicate that 3DMA PPP, as compared to conventional PPP, can significantly accelerate PPP convergence and improve positioning accuracy by over 30%. Consequently, 3D city models can be utilized as future assistance data for the A-GNSS location platform. [ABSTRACT FROM AUTHOR]

Location-based games are a highly technology-dependent game genre that has witnessed an exponential increase in popularity with the democratisation of smartphones as well as ubiquitous mobile data and access to satellite navigation. Moving forward into the future, location-based games can be expected to evolve as the technologies underlying the genre improve. In this conceptual work, we review the current state of the art in location-based games, and identify key trajectories and trends. We discovered 12 trends, based on which we jump ten years into the future and evaluate how current technology trends may end up influencing location-based gaming. For example, we propose that in the year 2035 through improvements in map data services and sensor data coverage, we will see locative games that are increasingly connected to elements in the physical world. We also expect to see gameplay that moves away from solely taking place on a smartphone screen to the adoption of multiple forms of interactions with location-based game worlds, especially as head-mounted displays and other wearables become more commonplace. [ABSTRACT FROM AUTHOR]

This study reports coordinated observation of ionospheric irregularities from VHF Radar, GPS and IRNSS (Indian Regional Navigation Satellite System), from regions near the northern crest of the EIA (Equatorial Ionization Anomaly), which has not been explored earlier. Efforts have been made to study the signal‐in‐space environment for concurrent detection of ionospheric irregularities over a range of radio frequency, starting from 53 MHz of the Radar, to L‐band of GPS at 1,575.42 MHz and S band signal of IRNSS at 2,492.5 MHz. The radar is operational at Ionosphere Field Station, Haringhata (geographic latitude 22.93°N; geographic longitude 88.51°E; magnetic dip angle 36.2°N) of University of Calcutta. The GPS and IRNSS data are recorded at Calcutta (22.58°N, 88.38°E geographic; magnetic dip: 36°N), separated from Haringhata by 50 km. The spatial as well as temporal variations of irregularities affecting different radio frequencies have been presented. Coordinated observations have been made during period of March–April 2023. Results of the study reveal the common zone of impact of the different radio frequency links spanning from 53 to 2,592.5 MHz and was identified within 16°–25°N, 85°–90°E. During coordinated observations made over several days, irregularity structures have been observed with radar, having backscatter SNR (Signal to Noise ratio) intensity within −5 to 15 dB. During this time, while intense L band scintillation was recorded on multiple satellites of GPS, scintillation recorded at S band signal was moderate to intense. Key Points: Coordinated observation of ionospheric irregularities from a low latitude station near the northern crest of equatorial ionization anomalyStudy of Signal‐in‐Space (SIS) environment over a range of radio signal from 53 to 2,592.5 MHzInvestigation of spatial confinement of ionospheric irregularities using radar and space based satellite signals at L band and S band [ABSTRACT FROM AUTHOR]

Satellite‐retrieved vegetation optical depth (VOD) has provided extensive insights into global plant function (such as, carbon stocks, water stress, crop yields) because of VOD's ability to monitor plant water stress and biomass at near daily temporal frequency under all‐weather conditions. However, arguably, the greatest challenge with broadly applying VOD is its lack of validation partly because of VOD's simultaneous sensitivity to plant water status and biomass changes, as well as intensive methods required to measure these properties in‐situ. Here, inspired by the recent Yao et al. (2024), https://doi.org/10.1029/2023GL107121 article, I argue that VOD estimated from global navigation satellite systems (GNSS) and land surface models with plant hydraulic schemes are two emerging methods that show promise for more widely validating satellite‐based VOD. I encourage wider adoption of these approaches to validate and further advance satellite‐based VOD research. Plain Language Summary: Vegetation water content, or the amount of vegetation water mass over a given area, can be measured with satellites over large areas (36 km scales) globally at the microwave frequency. The satellite microwave index is called vegetation optical depth (VOD). Satellite VOD has provided new insights into the plant sciences such as into how grasses, crops, and forests respond to water stress. However, satellite VOD and relevant estimates of vegetation water content at 36 km scales are challenging to validate with ground‐based measurements. This is because vegetation water content changes with how saturated the plants are and how much dry plant biomass there is over a given area, both of which require labor‐intensive methods to measure. Recent technological advances are providing an opportunity to validate VOD more widely. First, field configurations using global navigation satellite systems (GNSS) can measure VOD using cost‐effective sensors that receive microwave signals from navigation satellites. Second, land surface models are now including methods to model vegetation water content and thus estimate VOD globally at the same spatial scales as satellite measurements. I recommend further development of these GNSS and model methods such that satellite VOD can be more comprehensively validated. Key Points: Satellite‐based vegetation optical depth (VOD) is sensitive to plant water status and biomass, but is challenging to validateGlobal navigation satellite systems (GNSS) and plant hydraulic models are emerging methods that can viably validate satellite VOD retrievals across larger spatial scalesI recommend establishing more GNSS sites and using models to validate satellite VOD across a broader range of global conditions [ABSTRACT FROM AUTHOR]

Seafloor geodetic observation technology is a pivotal method for capturing plate boundary earthquakes and related phenomena. Currently, this task is performed by Global Navigation Satellite System-Acoustic ranging (GNSS-A), a technique that integrates GNSS observations with acoustic ranging. This method involves measuring the round-trip travel time of an acoustic signal between a surface platform and a preinstalled seafloor station, which is then converted into a distance for positioning. While the horizontal positioning accuracy can reach the centimeter level, the vertical accuracy tends to be loser. Recent research has revealed that equipment-dependent distortion of sound waves causes problems for accurate travel time identification, leading to a decrease in vertical component accuracy. In this paper, we conducted an analysis of distortion tendencies using water tank test data and quantitatively identified differences in distortion magnitude related to instruments, angle dependence, and directional dependence attributed to the sea surface platform. We proposed a new identification algorithm, Acoustic Ambiguity Reduction (AAR) method, using a catalog of distortions for each device, and improved the observational capabilities of the vertical component. [ABSTRACT FROM AUTHOR]

A technique is proposed to detect the presence of the multipath effect in Global Navigation Satellite Signal (GNSS) signals using a convolutional neural network (CNN) as the building block. The network is trained and validated, for a wide range of C / N 0 values, with a realistic dataset constituted by the synthetic noisy outputs of a 2D grid of correlators associated with different Doppler frequencies and code delays (time-domain dataset). Multipath-disturbed signals are generated in agreement with the various scenarios encompassed by the adopted multipath model. It was found that pre-processing the outputs of the correlators grid with the two-dimensional Discrete Fourier Transform (frequency-domain dataset) enables the CNN to improve the accuracy relative to the time-domain dataset. Depending on the kind of CNN outputs, two strategies can then be devised to solve the equation of navigation: either remove the disturbed signal from the equation (hard decision) or process the pseudoranges with a weighted least-squares algorithm, where the entries of the weighting matrix are computed using the analog outputs of the neural network (soft decision). [ABSTRACT FROM AUTHOR]

Sea ice plays a critical role in the Earth's climate system, and its variations affect ecosystem stability. This study introduces a novel method for detecting sea ice in the Arctic Ocean using bidirectional radar reflections from the Global Navigation Satellite System (GNSS). Utilizing delay-Doppler maps (DDM) from the UK TechDemoSat-1 (TDS-1) satellite mission and surface data from the U.S. National Oceanic and Atmospheric Administration (NOAA), we employ the local linear embedding (LLE) algorithm for feature extraction. This approach notably reduces training costs and enhances real-time performance, while maintaining a high accuracy and robust noise immunity level. Focusing on the region above 70° north latitude throughout 2018, we aimed to distinguish between sea ice and seawater. The extracted DDM features via LLE are input into a support vector machine (SVM) for classification. The results indicate that our method achieves an accuracy of over 99% for selected low-noise data and a monthly average accuracy of 92.74% for data containing noise, while the CNN method has a monthly average accuracy of only 77.31% for noisy data. A comparative analysis between the LLE-SVM approach and the convolutional neural network (CNN) method demonstrated the superior anti-interference capabilities of the former. Additionally, the impact of the sea ice melting period on detection accuracy was analyzed. [ABSTRACT FROM AUTHOR]

Oil spill detection plays an important role in marine environment protection. The technique of global navigation satellite system-reflectometry (GNSS-R) has the advantage of a short revisit time, which could help with timely cleanup of marine oil pollution. The conventional GNSS-R oil spill detection algorithm can resolve only the dielectric constant of oil based on power ratio measurements, while that of water cannot be realized. This is because the dielectric constant of water is much larger than that of oil such that the range of the equation used in the conventional algorithm is inadequate. To resolve this problem, we proposed a new algorithm containing a new equation with a larger scope, which has never been applied previously to GNSS-R oil spill detection. We derived a lookup method to resolve the dielectric constant of both oil and water. To validate our method, a drone-borne GNSS-R experiment based on dual-frequency QZSS reflection signals was conducted on 17 July 2023 using experimental pools simulating oil spills. Raw IF data in the L1 and L5 bands, collected using dual antennas and a data recorder, were processed using a software-defined receiver to deduce the power ratios and SNR of the GNSS signals. Results showed that the proposed algorithm is capable of resolving the dielectric constants of the reflected surface. In addition, the L5 signal was found to provide more detail and better contrast than the L1 C/A signal. [ABSTRACT FROM AUTHOR]

This study is aimed at evaluating the adjacent band compatibility of single frequency multi-Global Navigation Satellite System (GNSS), consisting of the Global Positioning System (GPS) L1 coarse acquisition (C/A) and Galileo E1 open service (OS) signals. The study is conducted using GNSS simulation, which allows for the tests to be held with various repeatable conditions, as defined by the users. It is found that the factors that affect the level of disruption from adjacent band interference include GNSS receiver parameters, as well as carrier frequency and bandwidth of interference signals. GNSS receivers with lower receiver sensitivity and higher receiver noise would be more susceptible to adjacent band interference. Moving the carrier frequency of interference signals away from the frequency of the GNSS L1 / E1 band (1575.42 MHz) as well as increasing their bandwidths increase the power levels that affect GNSS performance. The GPS + Galileo mode has slightly improved performance against interference as compared to the GPS only mode due to the alternative binary offset carrier (AltBOC) modulation that is employed for the Galileo E1 OS signal, which is improves its robustness. [ABSTRACT FROM AUTHOR]

High-precision time–frequency is widely used in time measurement, satellite navigation, scientific research, and other fields. With the rapid development of optical clock technology, the fractional frequency instability and uncertainty of optical clock have reached 10−18 orders of magnitude, which is expected to contribute to generating the International Atomic Time and may even be used to redefine the "second" in the future. Therefore, the long-distance transfer of time–frequency signals between optical atomic clocks is of great significance. Free-space optical frequency transfer technology is one of the important technologies for solving the space-based optical clock comparison because of its high transfer precision and easy networking characteristics. In order to solve the long-distance space-based optical clock comparison, this paper investigates a free-space active phase noise compensation method using an Acousto-Optic Modulator (AOM), based on the traditional optical fiber phase noise compensation scheme. This new method is more flexible and scalable than the optical fiber time–frequency transfer technology. The optical frequency transfer over a 64 m free-space link is demonstrated. The fractional frequency transfer instability during free running is 9.50 × 10−16 at 1 s, and 4.44 × 10−16 at 2000 s, and the fractional frequency instability after compensation is 7.10 × 10−17 at 1 s, 3.07 × 10−19 at 2000 s, which is about 1–3 orders of magnitude better than that in free running, and provides a feasible scheme for space-based optical clock comparison. [ABSTRACT FROM AUTHOR]

After the 2011 Tohoku-oki earthquake, a seafloor observation system observed rapid landward deformation. These seafloor observation data are potentially explicable via modeling of a low-viscosity zone under the subducting plate, called the lithosphere–asthenosphere boundary (LAB). However, the effect of a low-viscosity LAB has not been empirically examined in past earthquakes because of the absence of seafloor observation data, which are expected to have high sensitivity in the detection of a low-viscosity LAB. The Nankai Trough, southwest Japan, is one location where seafloor geodetic stations are in operation that could detect a low-viscosity LAB after a future earthquake. Therefore, we quantitatively model how the low-viscosity of the LAB is expected to affect postseismic crustal deformation following an anticipated future large earthquake under the Nankai Trough. Calculating viscoelastic deformation using a model that takes into account the realistic crustal structure in the southwestern Japanese Archipelago, we examine the effects of LAB viscosity on surface deformation patterns. The results show for very low LAB viscosities ( 2.5 × 10 17 Pa s), rapid landward displacement as large as 38 cm/yr occurs in the offshore area, with uplift and subsidence patterns highly dependent on the viscosity structure. Especially in the first year after the earthquake, the difference in deformation between the cases with and without a low-viscosity LAB was much larger than the observational error level of the current seafloor observation system. For such low LAB viscosities, the probability of detection is therefore high. On the other hand, for moderately low LAB viscosities ( 2.5 × 10 18 Pa s), the deformation patterns in the cases with and without a low-viscosity LAB are similar. Indeed, the difference in displacement lies within the observational error level of the current observational network, so detection is expected to be difficult for a LAB of only moderately low-viscosity. However, such a LAB may be detected by improving observational accuracy in the Global Navigation Satellite System–acoustic observation technique by performing more frequent measurements. Additional detection potential lies in expected future accuracy improvements in vertical displacement estimates at the DONET stations. [ABSTRACT FROM AUTHOR]

With the rapid development of technologies such as autonomous driving and robotic navigation, the demand for accurate and reliable positioning results with BDS has increased. The current status and future development of BDS high precision services are reviewed. The operational PPP-B2b of BDS-3 achieves positioning accuracy at decimeter-level within 14 min and has the drawbacks in regional coverage and long convergence time compared with the international counterparts, such as CLAS of QZSS and HAS of Galileo. A development frame for multi-layer BDS high-precision services is proposed by considering its construction cost, compatibility of user terminal, operating maintenance burden, and service level. The global high-precision service with the improved orbit and clock accuracy enhanced with the inter-satellite link is taken as the most fundamental layer. By incorporating inter-satellite link observations, the orbit errors URE and clock errors are significantly reduced to approximately 0.05 m and 0.16 ns, respectively, which will expand PPP service to global. Based on this, the regional PPP-AR and PPP-RTK services with improved convergence performance are taken as the second layer. With PPP-AR, the convergence time drops to 10 min. With PPP-RTK, the convergence time would be further shortened to less than 3 min. The LEO enhanced PPP service is taken as the third layer which overcomes both drawbacks of the long convergence time of the inter-satellite link enhanced service (the first layer) and the regional coverage of the PPP-AR/PPP-RTK services (the second layer). The simulation results show that by introducing a LEO constellation of 288 satellites, the LEO enhanced PPP can achieve positioning accuracy better than 5 cm within approximately 1 min. In addition, the integration of LEO constellation and PPP-RTK is further proposed to enable instantaneous convergence. The implementation challenges are also presented. [ABSTRACT FROM AUTHOR]

Understanding satellite system-specific artifacts and geophysical phenomena affecting coordinate estimates using multi-Global Navigation Satellite System (GNSS) data is of vital importance to ensure the accuracy and reliability of positioning, enabling scientific research to yield trustworthy and informed results. Therefore, this study is conducted to investigate the precision of single/multi-system solutions, factors affecting these precisions due to spurious periodic signals, and the mitigation of these signal powers in the frequency domain after fusing multi-GNSS data. For this purpose, the multi-GNSS data from 46 globally distributed International GNSS Service (IGS) stations spanning from January 1st, 2020 to August 31st, 2022, were processed using PRIDE-PPPAR v2.2 software in Precise Point Positioning (PPP) mode for GPS-, GLONASS-, Galileo-, and BeiDou-only solutions, as well as all possible combinations with GPS. The coordinates in the time domain were then converted into the frequency domain utilizing the Lomb-Scargle algorithm. The results of this experiment indicated that the GPS-only solutions have the best coordinate precision among the other satellite systems. The GLONASS, Galileo, and BeiDou systems exhibit orbital resonance up to the 3rd, 4th, and 3rd harmonics, respectively, whereas the GPS system, with a half of a sidereal day orbital period, exhibits no resonant effects due to the Nyquist frequency in the daily sampled time series. Enhanced coordinate precision for the multi-GNSS solutions was achieved with the GPS + GLONASS + Galileo + BeiDou combination (with only 0.1 mm deterioration in the east component), as well as the GPS + GLONASS + Galileo and GPS + Galileo combinations. The power spectra, particularly for the quadruple multi-GNSS combination, revealed that the system-specific periodic signals for GLONASS, Galileo, and BeiDou lost, on average, 85%, 55%, and 75% of their power in all components, respectively. Omitting the BeiDou and GLONASS systems from the quadruple and triple combinations slightly altered the power reductions of the Galileo systems. In other words, power reductions for orbital artifacts decreased as the number of satellite systems in the combination decreased. Interestingly, omitting specific systems did not significantly affect the fortnightly signals in multi-GNSS solutions. [ABSTRACT FROM AUTHOR]

Sea ice, a significant component in polar regions, plays a crucial role in climate change through its varying conditions. In Global Navigation Satellite System-Reflectometry (GNSS-R) studies, the observed surface reflectivity Γ serves as a tool to examine the physical characteristics of sea ice covers. This facilitates the large-scale estimation of first-year ice thickness using a two-layer sea ice-seawater medium model. However, it is important to note that when Sea Ice Thickness (SIT) becomes thicker, the accuracy of SIT retrieval via this two-layer model begins to decline. In this paper, we present a novel application of a spaceborne GNSS-R technique to retrieve SIT based on a three-layer model using the data from Fengyun-3E (FY-3E). Soil Moisture Ocean Salinity (SMOS) data are treated as the reference. The performance of the proposed three-layer model is evaluated against a previously established two-layer model for SIT retrieval. The analysis used the sea ice data from 2022 and 2023 with SITs less than 1.1 m. By comparing the retrieved SITs against reference values, the three-layer model achieved a Root Mean Square Error (RMSE) of 0.149 m and Correlation Coefficient (r) of 0.830, while the two-layer model reported the RMSE of 0.162 m and r value of 0.789. A scheme incorporating both models yielded superior results than either individual model, with the RMSE of 0.137 m and r reaching up to 0.852. This study is the first application of FY-3E for GNSS-R SIT retrieval, combining the advantages of a two-layer model and a three-layer model and extending the precision of GNSS-R retrieval for SIT to within 1.1 m. This provides a good reference for the future studies on GNSS-R SIT retrieval. [ABSTRACT FROM AUTHOR]

A multi-band antenna design by surface current reshaping of higher-order modes is presented. This method utilizes characteristic mode analysis to modify the conventional circular patch antenna in accordance with the surface current distribution of higher-order modes at the L5, S, and L1 bands using CMA. The antenna is evaluated up to four modes inducing fundamental mode. The S and L1 bands are obtained by exciting reshaped higher-order modes, while the L5 lower band is obtained by exciting the fundamental mode using full-wave analysis with 50 Ω coaxial feed. The measurement results are very similar to simulated antenna results. The measured operating frequencies of the proposed antenna are 1177.00 MHz (L5-band), 1575.00 (L1-band) MHz, and 2497.50 (S-band) MHz with associated impedance bandwidth (S11 ≤ −10 dB) are 25.30 MHz (1164.40–1189.70 MHz), 65.30 MHz (1535.50–1600.80 MHz), and 48.60 MHz (2464.10–2512.70 MHz) having desired gain with hemispherical radiation characteristics. These bands are used in Global Positioning Services (GPS) and in Indian Regional Navigation Satellite System (IRNSS) applications. [ABSTRACT FROM AUTHOR]

The global community, with coordination from the United Nations, is energized to pursue the Sustainable Development Goals (SDGs), a list of 17 important aspirations that summarize the key challenges of our era. The SDGs apply to every nation and represent an international effort to eliminate extreme poverty, ensure access to safe drinking water, strengthen food security, and produce clean and reliable energy, among other pursuits. Space technology is already being used around the world to advance progress toward the SDGs and monitor their related Indicators. This paper explores how six technologies related to space—satellite Earth observation, satellite communication, satellite navigation and positioning, human spaceflight and microgravity research, space technology transfer, and basic scientific research—are being used to realize the vision that the SDGs represent. The paper also discusses the obstacles that limit the application of these technologies for the SDGs and provides an overview of potential paths to overcome these barriers. The paper finally studies the historical and potential roles that four distinct types of entities involved in global sustainable development—governments, non- and inter-governmental organizations, entrepreneurial companies, and universities— have played or may play in the application of space technologies towards the SDGs. • Six space technology areas are shown to support the U.N. Sustainable Development Goals. • Examples of space projects that support the SDGs are found in many sectors. • New designs for technology are needed to improve effectiveness of space applications for the SDGS. [ABSTRACT FROM AUTHOR]

Lunisolar resonances shape the dynamics in the MEO region and have the effect of increasing an object's eccentricity possibly up to a value so high that the orbit's perigee reaches the atmosphere and friction determines the re-entry. The focus of this paper is the eccentricity growth phenomenon observed for navigation satellites. In particular, starting from a secular Hamiltonian model, analytical estimates for the maximum eccentricity reachable along an inclination-only dependent lunisolar resonance are derived as a function of the initial inclination. Also, trajectories that minimize an object's lifetime are studied, and analytical estimates for such a minimum lifetime are provided as a function of the initial eccentricity of the object. In addition, lifetime cartography maps are presented in the plane of the argument of perigee and the longitude of the ascending node. • Analytical estimates for the maximum eccentricity along lunisolar resonances. • Analytic formulae of minimum satellite lifetime at GPS and Galileo altitudes. • Litetime maps at GPS and Galileo altitudes in (ω)-(Ω) plane. [ABSTRACT FROM AUTHOR]

This paper aims to develop a theoretical interpretation of how satellite navigation transforms drivers' experience of automotive spaces. The use of satellite navigation has, so far, been predominantly studied from a cognitivist perspective based on the computer model of cognition and the theory of spatial disengagement. Experimental studies have concluded that over-reliance on digital navigation tools diminishes spatial orientation and spatial memory. According to the dominant interpretation, satellite navigation causes disengagement from space. After addressing these approaches, the paper introduces an embodied perspective of satellite navigation. This is accomplished by applying the phenomenology of perception of Maurice Merleau-Ponty, whose notions, such as perception, body schema, motor habit, and virtual body, illuminate otherwise undertheorized dimensions of drivers' spaces. By using digital tools for wayfinding, drivers' body schema, virtual body, and perception of space are modified, thereby enabling an engagement with convoluted 'mesh spaces.' This new term is integral to the interpretation of drivers' spaces, as well as being distinct from that of 'hybrid space,' although both aim to conceptualize spaces, including physical objects and their visual representations. Conclusions will be drawn against the broader context of the mediatization of everyday life. [ABSTRACT FROM AUTHOR]

Along with regular position-related applications, observations from navigation satellite constellations can also be utilised for atmospheric studies. The present study deals with the 3D water vapour tomography carried out for the first time using Indian GPS stations set up in the Himalayan region. A voxel-based approach is applied to retrieve the vertical profile of precipitable water vapour (PWV). Horizontal 4×4 grids have been formed between 29°–31° latitude and 77.5°–79.5° longitude with 0.5° spatial resolution. To construct a tomography model, voxels are formed over these grids up to 10 km with 0.5 km vertical resolution. Water vapour density (WVD) is estimated for different days to observe its variations under different atmospheric conditions. The results show that the estimated vertical variation of water vapour closely matches the AIRS WVD profile. To compare the results, AIRS WVD observations are interpolated at the same altitude where the tomographic estimations are available. The average root mean square (RMS) error, standard deviation (SD), and mean absolute error (MAE) between estimated water vapour density and AIRS WVD are observed to be 1.52, 1.32 and 2.02 g/m3, respectively. The coefficient of determination (R2) value is observed to be close to 0.9, reflecting an excellent linearity between estimated and observed values. The results also show that the WVD is high up to the 5 km voxel and it is between 0 and 5 g/m3 above 5 km altitude. A good estimation of vertical water vapour profile has been obtained using CORS observations and can be used for further atmospheric analyses in this region. [ABSTRACT FROM AUTHOR]

There is a situation on railway lines where there is no network coverage in some sections. When the train restarts due to a fault in said sections and there is no network available, it is unable to communicate with trackside equipment to obtain line data, which aff ects operational efficiency. This paper mainly studies the method of train fault recovery in sections without network coverage, using Regional Short Message Communication (RSMC) technology of BeiDou Navigation Satellite System to solve the problem of train restart due to faults and recovery in these sections. [ABSTRACT FROM AUTHOR]

Satellites experience a variety of electromagnetic environments, from launch to orbital operation, making it is necessary to verify that satellites can properly operate in these environments. Currently, many satellites. such as optical satellites, radar satellites, communication satellites, and navigation satellites. are being developed in Korea, and based on this development trend, electromagnetic environment verification technology for satellite systems is becoming increasingly important. In this study, we describe a method for verifying the electromagnetic environment at the satellite system level. The purpose, requirements, methods, and considerations of each item are introduced for the EMC test, RF auto-compatibility test, LV RF compatibility test, and electrostatic discharge analysis. It is expected that the proposed method for verifying the electromagnetic environment at the satellite system level can be used in the verification of satellites under development in Korea. [ABSTRACT FROM AUTHOR]

The Moon is the closest celestial body to the Earth. Its rich unique resources are an important supplement to the Earth's resources and have a profound impact on the sustainable development of human society. As large-scale exploration missions gradually progress, demands for communication, navigation, surveying and other services of lunar-space probes have significantly increased. Constellation navigation and orbit determination technology will become an indispensable part of future lunar exploration infrastructure. This article systematically analyzes the current status of lunar relay navigation satellite networks at home and abroad, summarizes the technical principles of single-satellite and constellation navigation and orbit determination, discusses the technical difficulties in lunar navigation constellation orbit determination and navigation, and analyzes possible solutions. Finally, the development trend of research on high-precision orbit determination and navigation methods for lunar navigation constellations is proposed. [ABSTRACT FROM AUTHOR]

Optimizing the correlation properties of spreading codes is critical for minimizing inter-channel interference in satellite navigation systems. By improving the codes' correlation sidelobes, we can enhance navigation performance while minimizing the required spreading code lengths. In the case of low-earth orbit (LEO) satellite navigation, shorter code lengths (on the order of a hundred) are preferred due to their ability to achieve fast signal acquisition. Additionally, the relatively high signal-to-noise ratio in LEO systems reduces the need for longer spreading codes to mitigate inter-channel interference. In this work, we propose a two-stage block coordinate descent (BCD) method which optimizes the codes' correlation properties while enforcing the autocorrelation sidelobe zero property. In each iteration of the BCD method, we solve a mixed-integer convex program over a block of 25 binary variables. Our method is applicable to spreading code families of arbitrary sizes and lengths, and we demonstrate its effectiveness for a problem with 66 length-127 codes and a problem with 130 length-257 codes. [ABSTRACT FROM AUTHOR]

The system time of the four major navigation satellite systems is mainly maintained by multiple high-performance atomic clocks at ground stations. This operational mode relies heavily on the support of ground stations. To enhance the high-precision autonomous timing capability of next-generation navigation satellites, it is necessary to autonomously generate a comprehensive space-based time scale on orbit and make long-term, high-precision predictions for the clock error of this time scale. In order to solve these two problems, this paper proposed a two-level satellite timing system, and used multiple time-keeping node satellites to generate a more stable space-based time scale. Then this paper used the sparse sampling Long Short-Term Memory (LSTM) algorithm to improve the accuracy of clock error long-term prediction on space-based time scale. After simulation, at sampling times of 300 s, 8.64 × 104 s, and 1 × 106 s, the frequency stabilities of the spaceborne timescale reach 1.35 × 10–15, 3.37 × 10–16, and 2.81 × 10–16, respectively. When applying the improved clock error prediction algorithm, the ten-day prediction error is 3.16 × 10–10 s. Compared with those of the continuous sampling LSTM, Kalman filter, polynomial and quadratic polynomial models, the corresponding prediction accuracies are 1.72, 1.56, 1.83 and 1.36 times greater, respectively. [ABSTRACT FROM AUTHOR]