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This study proposes a new concept of carrier-phase-based satellite augmentation system named “Compact Real-time Kinematic for Expanded Area (COREA),” which provides centimeter-level positioning services across nationwide coverage. The proposed system’s architecture is very similar to that of the satellite-based augmentation system (SBAS), a meter-level aviation safety service. While network real-time kinematic and precise-point-positioning-RTK (PPP-RTK) rely on several densely positioned reference stations, COREA provides carrier-phase-based corrections using a few reference stations with a distance of 400–1000 km. Furthermore, the COREA corrections can be transmitted by satellite signals with extremely low-speed data links of 250 bps, similar to SBAS. This study focused on the generation method for satellite code/phase clock (CPC) corrections, which is the most significant part of the system. We analyzed the user performance of the COREA system constructed in the Midwest and South of the United States with six reference stations. Consequently, satellite CPC corrections are resilient to communication failures and highly accurate in identifying user integer ambiguity. The 95% position accuracy is approximately 1.8 cm horizontally and 7.1 cm vertically, with an average convergence time of 1–3 min using only GPS triple-frequency signals. In summary, the COREA system preserves the hardware architecture of the legacy SBAS while providing centimeter-level services with fast convergence times by utilizing extremely low-speed satellite data links across the country.

Currently, Global Navigation Satellite System (GNSS) Real-Time Kinematic positioning (RTK) and Precise Point Positioning (PPP) techniques are widely employed for real-time monitoring of landslides. However, both RTK and PPP monitoring techniques have their limitations, such as limited service coverage or long convergence times. PPP-RTK technique which integrates RTK and PPP is a novel approach for monitoring landslides with the advantages of rapid convergence, high-precision, and a wide service area. This study summarizes the limitations of RTK, PPP, and PPP-RTK monitoring techniques and suggests some improved strategies. Their performances are compared and analyzed using real monitoring data. The experiment results demonstrate that RTK is the best option for small-scale (the baseline distance < 15 km) and real-time landslide monitoring without considering the cost. PPP technique converges to centimeter-level accuracy in tens of minutes, only suitable for the stability analysis of reference stations. Over a large area (the baseline distance < 100 km), PPP-RTK can provide excellent horizontal accuracy and adapt the service range in response to the demand for monitoring accuracy, as the vertical accuracy is significantly impacted by the service range and elevation difference. Finally, the characteristics of three techniques are integrated to form a comprehensive landslide monitoring technique that considers intelligence, robustness, and real-time.

The PPP–RTK method, which combines the concepts of Precise of Point Positioning (PPP) and Real-Time Kinematic (RTK), is proposed to provide a centimeter-accuracy positioning service for an unlimited number of users. Recently, the PPP–RTK technique is becoming a promising tool for emerging applications such as autonomous vehicles and unmanned logistics as it has several advantages including high precision, full flexibility, and good privacy. This paper gives a detailed review of PPP–RTK focusing on its implementation methods, recent achievements as well as challenges and opportunities. Firstly, the fundamental approach to implement PPP–RTK is described and an overview of the research on key techniques, such as Uncalibrated Phase Delay (UPD) estimation, precise atmospheric correction retrieval and modeling, and fast PPP ambiguity resolution, is given. Then, the recent efforts and progress are addressed, such as improving the performance of PPP–RTK by combining multi-GNSS and multi-frequency observations, single-frequency PPP–RTK for low-cost devices, and PPP–RTK for vehicle navigation. Also, the system construction and applications based on the PPP–RTK method are summarized. Moreover, the main issues that impact PPP–RTK performance are highlighted, including signal occlusion in complex urban areas and atmosphere modeling in extreme weather events. The new opportunities brought by the rapid development of low-cost markets, multiple sensors, and new-generation Low Earth Orbit (LEO) navigation constellation are also discussed. Finally, the paper concludes with some comments and the prospects for future research.

Aerial photogrammetry by Unmanned Aerial Vehicles (UAVs) is a widespread method to perform mapping tasks with high-resolution to reconstruct three-dimensional (3D) building and façade models. However, the survey of Ground Control Points (GCPs) represents a time-consuming task, while the use of Real-Time Kinematic (RTK) drones allows for one to collect camera locations with an accuracy of a few centimeters. DJI Phantom 4 RTK (DJI-P4RTK) combines this with the possibility to acquire oblique images in stationary conditions and it currently represents a versatile drone widely used from professional users together with commercial Structure-from-Motion software, such as Agisoft Metashape. In this work, we analyze the architectural application of this drone to the photogrammetric modeling of a building with particular regard to metric survey specifications for cultural heritage for 1:20, 1:50, 1:100, and 1:200 scales. In particular, we designed an accuracy assessment test signalizing 109 points, surveying them with total station and adjusting the measurements through a network approach in order to achieve millimeter-level accuracy. Image datasets with a designed Ground Sample Distance (GSD) of 2 mm were acquired in Network RTK (NRTK) and RTK modes in manual piloting and processed both as single façades (S–F) and as an overall block (4–F). Subsequently, we compared the results of photogrammetric models generated in Agisoft Metashape to the Signalized Point (SP) coordinates. The results highlight the importance of processing an overall photogrammetric block, especially whenever part of camera locations exhibited a poorer accuracy due to multipath effects. No significant differences were found between the results of network real-time kinematic (NRTK) and real-time kinematic (RTK) datasets. Horizontal residuals were generally comparable to GNSS accuracy in NRTK/RTK mode, while vertical residuals were found to be affected by an offset of about 5 cm. We introduced an external GCP or used one SP per façade as GCP, assuming a poorer camera location accuracy at the same time, in order to fix this issue and comply with metric survey specifications for the widest architectural scale range. Finally, both S–F and 4–F projects satisfied the metric survey requirements of a scale of 1:50 in at least one of the approaches tested.

This paper presents and reviews the main existing open specifications for PPP/PPP‐RTK services, including satellite navigation providers (QZSS, Galileo, BeiDou, GLONASS) and other industrial or scientific initiatives (RTCM, SAPCORDA, 3GPP, IGS). To structure the comparison, we adapted PPP/PPP‐RTK services to the well‐known OSI model and defined them according to their properties in the OSI communication layers. We show how the proposed formats relate to the current standards, mainly RTCM SSR and CSSR, and what their differences and similarities are in terms of transmitted corrections and bandwidth. We compare the efficiency of the existing formats in two scenarios: a global PPP scenario with multi‐GNSS corrections, and a regional PPP‐RTK scenario, also multi‐GNSS and including ionospheric corrections. We propose an interoperable format that can be an extension to CSSR and allows efficient transmission of corrections for both global‐scale MEO‐based PPP as well as nationwide IGSO/GEO‐based PPP‐RTK.

Glioblastomas represent the most prevalent primary brain tumors in adults. Due to their highly malignant biological behavior, they are classified as grade 4 according to the World Health Organization (WHO) classification of brain tumors. Despite the progress in understanding the molecular pathogenesis of these tumors, no curative therapy has been developed for patients with glioblastoma. In this study, an integrated comparative analysis of chromosomal deletion was performed on 45 glioblastomas, representing the most frequent molecular subtypes of glioblastomas, receptor tyrosine kinase (RTK) I (n=13), RTK II (n=15), and the mesenchymal subtype (MES) (n=17). The analysis of copy number variation (CNV) profiles was conducted on losses. Subsequent statistical analysis was then applied to correlate the collected data with molecular glioblastoma epigenotypes. Loss of was found 44% (20/45) of all glioblastomas, thereby, in 46% (6/13) of RTK I, 67% (10/15) RTK II, and 24% (4/17) of MES. Statistical analysis showed that loss of is significant (p < 0.01) in RTK II compared with MES. Even though does not per se function as a molecular target, there is great potential for enhancing treatment outcomes through the restoration of the tumor-suppressing capabilities of . This strategy can be employed in therapeutic interventions and is a promising avenue for research. This efficacy of this approach demonstrates high potential, as evidenced by its efficacy in other tumors, including melanoma.

In terms of quality control of ambiguity estimation, the common partial ambiguity fixation algorithm is improved, and the SC-PAR (Single frequency Combined Partial Ambiguity Resolution) algorithm is proposed. After the algorithm fails to fix the full ambiguity, it filters the ambiguity subset step by step according to the number of continuous satellite lock epochs, satellite elevation angle, satellite signal-to-noise ratio, geometric precision factor, ambiguity variance and ambiguity precision attenuation factor, and searches Optimal ambiguity subset. According to the R-ratio value and the success rate index, the search results are jointly tested, and the remaining subsets are corrected with the subsets that pass the test. The results show that compared with the FAR and conventional PAR algorithms, the fixed rate of the SC-PAR algorithm is increased by 65.01% and 27.97%, respectively, and the accuracy is also significantly improved.

The emerging GNSSs make single-frequency (SF) RTK positioning possible. In this contribution two different types of low-cost (few hundred USDs) RTK receivers are analyzed, which can track L1 GPS, B1 BDS, E1 Galileo and L1 QZSS, or any combinations thereof, for a location in Dunedin, New Zealand. These SF RTK receivers can potentially give competitive ambiguity resolution and positioning performance to that of more expensive (thousands USDs) dual-frequency (DF) GPS receivers. A smartphone implementation of one of these SF receiver types is also evaluated. The least-squares variance component estimation (LS-VCE) procedure is first used to formulate a realistic stochastic model, which assures that our receivers at hand can achieve the best possible ambiguity resolution and RTK positioning performance. The best performing low-cost SF RTK receiver types are then assessed against DF GPS receivers and survey-grade antennas. Real data with ionospheric disturbances at low, medium and high levels are analyzed, while making use of the ionosphere-weighted model. It will be demonstrated that when the presence of the residual ionospheric delays increases, instantaneous RTK positioning is not possible for any of the receivers, and a multi-epoch model is necessary to use. It is finally shown that the low-cost SF RTK performance can remain competitive to that of more expensive DF GPS receivers even when the ionospheric disturbance level reaches a Kp-index of 7−, i.e. for a strong geomagnetic storm, for the baseline at hand.

Real-Time Kinematic Precise Point Positioning (PPP–RTK) is inextricably linked to external ionospheric information. The PPP–RTK performances vary much with the accuracy of ionospheric information, which is derived from different network scales, given different prior variances, and obtained under different disturbed ionospheric conditions. This study investigates the relationships between the PPP–RTK performances, in terms of precision and convergence time, and the accuracy of external ionospheric information. The statistical results show that The Time to First Fix (TTFF) for the PPP–RTK constrained by Global Ionosphere Map (PPP–RTK-GIM) is about 8–10 min, improved by 20%–50% as compared with that for PPP Ambiguity Resolution (PPP-AR) whose TTFF is about 13–16 min. Additionally, the TTFF of PPP–RTK is 4.4 min, 5.2 min, and 6.8 min, respectively, when constrained by the external ionospheric information derived from different network scales, e.g. small-, medium-, and large-scale networks, respectively. To analyze the influences of the optimal prior variances of external ionospheric delay on the PPP–RTK results, the errors of 0.5 Total Electron Content Unit (TECU), 1 TECU, 3 TECU, and 5 TECU are added to the initial ionospheric delays, respectively. The corresponding convergence time of PPP–RTK is less than 1 min, about 3, 5, and 6 min, respectively. After adding the errors, the ionospheric information with a small variance leads to a long convergence time and that with a larger variance leads to the same convergence time as that of PPP-AR. Only when an optimal prior variance is determined for the ionospheric delay in PPP–RTK model, the convergence time for PPP–RTK can be shorten greatly. The impact of Travelling Ionospheric Disturbance (TID) on the PPP–RTK performances is further studied with simulation. It is found that the TIDs increase the errors of ionospheric corrections, thus affecting the convergence time, positioning accuracy, and reliability of PPP–RTK.

High-precision positioning is essential for emerging mass-market applications such as autonomous driving, unmanned aerial vehicles and intelligent transportation in complex urban canyons. Without global navigation satellite system (GNSS) reference stations, the real-time kinematic precise point positioning (PPP-RTK) technique is widely used in these fields because of its fast and accurate absolute positioning capability. However, in complex urban canyons, the performance of PPP-RTK deteriorates dramatically due to the satellite signal obstruction and interference. In contrast, inertial navigation system (INS) and visual navigation can provide precise relative pose estimation, but they suffer from serious error accumulation. Therefore, there is a strong complementary advantage between GNSS and INS/Vision navigation and positioning. In this study, a tightly coupled PPP-RTK/INS/Vision integration model is developed, aiming at improving the performance of PPP-RTK in terms of precision and availability to achieve robust positioning in complex urban canyons. Vehicle-borne experiments with different typical urban scenarios were carried out. We found that the positioning precision, availability and the ambiguity fixing rate of PPP-RTK can be significantly improved by tightly coupling with INS and Vision. The positioning precision of tightly coupled micro-electro-mechanical system (MEMS)-based PPP-RTK/INS/Vision is 6 cm, 5 cm and 10 cm in the east, north and up components, respectively, with an ambiguity fixing rate of 83.6% in typical urban environments, which are comparable to the statistics of a tactical-based PPP-RTK/INS tight integration. Even in complex urban canyons, the positioning precision of tightly coupled MEMS-based PPP-RTK/INS/Vision solution can still reach 11 cm, 7 cm and 13 cm in the east, north and up components, respectively, exhibiting improvements of over 90% compared to GNSS-only PPP-RTK. These results indicate that PPP-RTK tightly coupled with low-cost MEMS-IMU and monocular vision can provide high-precision and high-reliability navigation and positioning solutions even in complex urban environments.