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Coded aperture X-ray computed tomography (CAXCT) measures coded X-ray projections to reconstruct the inner structure of an object. Coded apertures, which determine the point spread function, can be designed to improve the reconstruction quality, but most approaches are computationally expensive, leading to very small images. In this paper, a sparse covariance matrix estimation approach is introduced to minimize the information loss sensed by projections corresponding to large tomographic images. The covariance matrix representing the map of the overlapping information of the projections is obtained by using block matrix multiplication and sparse estimation. A heuristic variant algorithm with a noise factor is presented to search the combinations of projections leading to maximum non-overlapping information acquisition, where is the number of unblocking elements on the coded apertures. Numerical experiments with simulated datasets show that the optimization performance of the proposed method is comparable to that of state-of-the-art methods with small images. Further, for the analyzed cases, coded aperture optimization was performed with 512 × 512 images by analyzing coefficients smaller than 0.02% in the covariance matrix.

Traditional high-precision satellite orbits rely on globally dense and evenly distributed ground tracking stations, while the accuracy of precise orbit determination (POD) based on a regional network cannot compare with that of a global network. Low Earth orbit (LEO) satellites can serve as space-based monitoring stations to compensate for this. In response to the current regional integrated POD that only resolves the ambiguities of ground stations, this paper proposes an ambiguity resolution (AR) strategy related to LEO satellites to enhance GPS orbit accuracy. A joint observation network is established using seven International GNSS Service (IGS) stations within China and 10 LEO satellites, including GRACE-C/D, LuTan1-A/B, SWARM-A/B/C, Sentinel-3A/B, and Sentinel-6A. Experiments are conducted and analyzed from three aspects: independent baseline selection, the common view time, and the wide-lane (WL) threshold of double-differenced ambiguity. The ambiguity fixing strategy is determined to be a combination of inter-satellite and satellite–ground baselines, a common view time of 5 min, and a WL ambiguity threshold of 0.2 cycles. Taking the final products released by the IGS as the reference, the GPS orbit accuracy in the along-track, cross-track, radial, and 1D RMS is 3.23, 2.74, 2.36, and 2.89 cm, respectively, which represents improvements of 9.3%, 12.5%, 10.9%, and 10.8% compared with the solution that only fixes the ambiguities of ground stations. This result demonstrates that, in regional integrated POD, further implementation of LEO satellite-related ambiguity fixing significantly improves GPS orbit accuracy. Given the limitation that most LEO satellites can only receive GPS satellite signals, in the future, as more LEO satellites gain access to GNSS observations, the ambiguity fixing strategy presented in this paper can provide an effective and feasible approach.

Precise point positioning ambiguity resolution (PPP-AR) is a key technique for high-precision global navigation satellite system (GNSS) observations, with phase bias products playing a critical role in its implementation. The multi-GNSS experiment analysis center at Wuhan University (WUM) has adopted the undifferenced ambiguity resolution (UDAR) approach to generate high-precision orbit, clock, and observable-specific bias (OSB) products to support PPP-AR since day 162 of 2023. This study presents the analysis strategy employed and assesses the impact of the transition to ambiguity resolution on the orbit precision, using metrics such as orbit boundary discontinuities (OBD) and satellite laser ranging (SLR) validation. Additionally, the stability of the OSB products and the overall performance of PPP-AR solutions are evaluated. The OBD demonstrates specific improvements of 7.1% and 9.5% for GPS and Galileo, respectively, when UDAR is applied. Notably, BDS-3 medium Earth orbit satellites show a remarkable 15.2% improvement compared to the double-differenced results. However, for the remaining constellations, the improvements are either minimal or result in degradation. Using GPS and GLONASS solutions from the International GNSS Service (IGS) and other solutions from the European Space Agency (ESA) as references, the orbit differences of WUM solutions based on UDAR exhibit a significant reduction. However, the improvements in SLR validation are limited, as the radial orbit precision is primarily influenced by the dynamic model. The narrow-lane ambiguity fixing rate for static PPP-AR, based on data from approximately 430 globally distributed stations, reaches 99.2%, 99.2%, 88.8%, and 98.6% for GPS, Galileo, BDS-2, and BDS-3, respectively. The daily repeatability of station coordinates is approximately 1.4 mm, 1.9 mm, and 3.9 mm in the east, north, and up directions, respectively. Overall, these results demonstrate the effectiveness and potential of WUM’s undifferenced ambiguity resolution approach in enhancing GNSS data processing and facilitating PPP-AR applications.

With an increase in the intensity and frequency of extreme rainfall events, there is a pressing need for accurate rainfall nowcasting applications. In recent years, precipitable water vapor (PWV) data obtained from GNSS observations have been widely used in rainfall prediction. Unlike previous studies mainly focusing on rainfall occurrences, this study proposes a transformer-based model for hourly rainfall prediction, integrating the GNSS PWV and ERA5 meteorological data. The proposed model employs the ProbSparse self-attention to efficiently capture long-range dependencies in time series data, crucial for correlating historical PWV variations with rainfall events. Additionally, the adoption of the DILATE loss function better captures the structural and timing aspects of rainfall prediction. Furthermore, traditional rainfall prediction models are typically trained on datasets specific to one region, which limits their generalization ability due to regional meteorological differences and the scarcity of data in certain areas. Therefore, we adopt a pre-training and fine-tuning strategy using global datasets to mitigate data scarcity in newly deployed GNSS stations, enhancing model adaptability to local conditions. The evaluation results demonstrate satisfactory performance over other methods, with the fine-tuned model achieving an MSE = 3.954, DTW = 0.232, and TDI = 0.101. This approach shows great potential for real-time rainfall nowcasting in a local area, especially with limited data.

Chinese Beidou satellite navigation system constellation currently consists of eight Beidou satellites and can provide prelimi- nary service of navigation and positioning in the Asia-Pacific Region. Based on the self-developed software Position And Navigation Data Analysis（PANDA） and Beidou Experimental Tracking Stations （BETS）, which are built by Wuhan University, the study of Beidou precise orbit determination, static precise point positioning （PPP）, and high precision relative positioning, and differential positioning are carried out comprehensively. Results show that the radial precision of the Beidou satellite orbit determination is better than 10 centimeters. The RMS of static PPP can reach several centimeters to even millimeters for base- line relative positioning. The precision of kinematic pseudo-range differential positioning and RTK mode positioning are 2-4 m and 5-10 cm respectively, which are close to the level of GPS precise positioning. Research in this paper verifies that, with support of ground reference station network, Beidou satellite navigation system can provide precise positioning from several decimeters to meters in the wide area and several centimeters in the regional area. These promising results would be helpful for the implementation and applications of Beidou satellite navigation system.

Ionosphere research using the Global Navigation Satellite Systems (GNSS) techniques is a hot topic, with their unprecedented high temporal and spatial sampling rate. We introduced a new GNSS Ionosphere Monitoring and Analysis Software (GIMAS) in order to model the global ionosphere vertical total electron content (VTEC) maps and to estimate the GPS and GLObalnaya NAvigatsionnaya Sputnikovaya Sistema (GLONASS) satellite and receiver differential code biases (DCBs). The GIMAS-based Global Ionosphere Map (GIM) products during low (day of year from 202 to 231, in 2008) and high (day of year from 050 to 079, in 2014) solar activity periods were investigated and assessed. The results showed that the biases of the GIMAS-based VTEC maps relative to the International GNSS Service (IGS) Ionosphere Associate Analysis Centers (IAACs) VTEC maps ranged from −3.0 to 1.0 TECU (TEC unit) (1 TECU = 1 × 1016 electrons/m2). The standard deviations (STDs) ranged from 0.7 to 1.9 TECU in 2008, and from 2.0 to 8.0 TECU in 2014. The STDs at a low latitude were significantly larger than those at middle and high latitudes, as a result of the ionospheric latitudinal gradients. When compared with the Jason-2 VTEC measurements, the GIMAS-based VTEC maps showed a negative systematic bias of about −1.8 TECU in 2008, and a positive systematic bias of about +2.2 TECU in 2014. The STDs were about 2.0 TECU in 2008, and ranged from 2.2 to 8.5 TECU in 2014. Furthermore, the aforementioned characteristics were strongly related to the conditions of the ionosphere variation and the geographic latitude. The GPS and GLONASS satellite and receiver P1-P2 DCBs were compared with the IAACs DCBs. The root mean squares (RMSs) were 0.16–0.20 ns in 2008 and 0.13–0.25 ns in 2014 for the GPS satellites and 0.26–0.31 ns in 2014 for the GLONASS satellites. The RMSs of receiver DCBs were 0.21–0.42 ns in 2008 and 0.33–1.47 ns in 2014 for GPS and 0.67–0.96 ns in 2014 for GLONASS. The monthly stability of the GPS satellite DCBs was about 0.04 ns (0.07 ns) in 2008 (2014) and that for the GLONASS satellite DCBs was about 0.09 ns in 2014. The receiver DCBs were less stable than the satellite DCBs, with a mean value of about 0.16 ns (0.47 ns) in 2008 (2014) for GPS, and 0.48 ns in 2014 for GLONASS. It can be demonstrated that the GIMAS software had a high accuracy and reliability for the global ionosphere monitoring and analysis.

Currently, the Global Navigation Satellite System (GNSS) mainly uses the satellites in Medium Earth Orbit (MEO) to provide position, navigation, and timing (PNT) service. The weak navigation signals limit its usage in deep attenuation environments, and make it easy to interference and counterfeit by jammers or spoofers. Moreover, being far away to the Earth results in relatively slow motion of the satellites in the sky and geometric change, making long time needed for achieved centimeter positioning accuracy. By using the satellites in Lower Earth Orbit (LEO) as the navigation satellites, these disadvantages can be addressed. In this contribution, the advantages of navigation from LEO constellation has been investigated and analyzed theoretically. The space segment of global Chinese BeiDou Navigation Satellite System consisting of three GEO, three IGSO, and 24 MEO satellites has been simulated with a LEO constellation with 120 satellites in 10 orbit planes with inclination of 55 degrees in a nearly circular orbit (eccentricity about 0.000001) at an approximate altitude of 975 km. With simulated data, the performance of LEO constellation to augment the global Chinese BeiDou Navigation Satellite System (BeiDou-3) has been assessed, as one of the example to show the promising of using LEO as navigation system. The results demonstrate that the satellite visibility and position dilution of precision have been significantly improved, particularly in mid-latitude region of Asia-Pacific region, once the LEO data were combined with BeiDou-3 for navigation. Most importantly, the convergence time for Precise Point Positioning (PPP) can be shorted from about 30 min to 1 min, which is essential and promising for real-time PPP application. Considering there are a plenty of commercial LEO communication constellation with hundreds or thousands of satellites, navigation from LEO will be an economic and promising way to change the heavily relay on GNSS systems.

X-ray tomosynthesis technique can reconstruct three-dimensional object of interest from two-dimensional projection measurements. This paper proposes a compressive X-ray tomosynthesis imaging method to inspect the moving object on the conveyor. Coding masks are used to modulate the intensity distribution of X-ray sources and reduce the radiation dose. Low-cost uniform linear array detector is used to collect measurement data. Considering the rigid motion of the object, the proposed method uses a dynamic imaging model and a reconstruction framework based on the variation of the sensing geometry. Subsequently, an optimization method is proposed to design the exposure sequence of X-ray sources based on the genetic algorithm. Optimizing the exposure sequence can ameliorate the condition of the ill-posed inverse reconstruction problem. Simulations show that the optimized exposure sequence can effectively improve the reconstruction performance of the compressive X-ray tomosynthesis.

The ionosphere is a crucial factor affecting Global Navigation Satellite System positioning. The Global Ionosphere Map (GIM) or the International Reference Ionosphere (IRI) model can be used for regional ionospheric correction. Since southern China is located near the electron density equatorial anomaly, this study evaluates the performance of the Wuhan University GIM (WHU‐GIM) and the IRI‐2020 from 2008 to 2020 over the China region. The comparison indicates that the Total Electron Content (TEC) from IRI‐2020 is lower than that from WHU‐GIM overall, the discrepancy is more obvious in high solar conditions and low‐latitude regions. The differential Slant TEC (dSTEC) during a phase‐arc with about 0.1 TECU accuracy derived from Global Positioning System (GPS) observations is used for model validation, the results show that the accuracies of WHU‐GIM and IRI‐2020 are 3.14 and 4.57 TECU, respectively. The dSTEC error is larger at low latitudes and decreases with increasing latitude. GPS‐derived TEC is taken for reference to evaluate the model reliability. Results show that both models can reproduce the diurnal TEC variations, but IRI‐2020 is more influenced by geomagnetic activities. The TEC correction percentage for IRI‐2020 is about 60%–80% under different ionospheric conditions, while for WHU‐GIM is 80%–90%. The Single‐Frequency Precise Point Positioning is performed with the ionosphere delay corrected by the two models, respectively. The positioning errors show that using IRI‐2020 has a lower accuracy, and the TEC discrepancy of the IRI‐2020 can cause a large bias in the up direction, especially at low‐latitude regions.

Since the first pair of BeiDou satellites was deployed in 2000, China has made continuous efforts to establish its own independent BeiDou Navigation Satellite System (BDS) to provide the regional radio determination satellite service as well as regional and global radio navigation satellite services, which rely on the high quality of orbit and clock products. This article summarizes the achievements in the precise orbit determination (POD) of BDS satellites in the past decade with the focus on observation and orbit dynamic models. First, the disclosed metadata of BDS satellites is presented and the contribution to BDS POD is addressed. The complete optical properties of the satellite bus as well as solar panels are derived based on the absorbed parameters as well the material properties. Secondly, the status and tracking capabilities of the L-band data from accessible ground networks are presented, while some low earth orbiter satellites with onboard BDS tracking capability are listed. The topological structure and measurement scheme of BDS Inter-Satellite-Link (ISL) data are described. After highlighting the progress on observation models as well as orbit perturbations for BDS, e.g., phase center corrections, satellite attitude, and solar radiation pressure, different POD strategies used for BDS are summarized. In addition, the urgent requirement for error modeling of the ISL data is emphasized based on the analysis of the observation noises, and the incompatible characteristics of orbit and clock derived with L-band and ISL data are illuminated and discussed. The further researches on the improvement of phase center calibration and orbit dynamic models, the refinement of ISL observation models, and the potential contribution of BDS to the estimation of geodetic parameters based on L-band or ISL data are identified. With this, it is promising that BDS can achieve better performance and provides vital contributions to the geodesy and navigation.