Real-time Kinematic Research Articles

The Accuracy of RTK enabled Mobile Phones in RTK denied Areas

Abstract. Surveyors often encounter challenges when tasked with measuring points in regions where buildings disrupt satellite visibility. The precise surveying of points in these areas typically relies on employing total stations. This method effectively extends high precision from unaffected zones (where satellite visibility is assured) to those areas where disruption occurs due to buildings. Total stations achieve this by executing distance and angle measurements from a reference point coordinate to the location where satellite visibility is compromised. The process is notably time-consuming, thereby incurring significant costs. Moreover, the intricate nature of this surveying process necessitates specialized skills and expertise, contributing further to the overall expense. In this study, we investigate an approach based on RTK (Real-Time Kinematic) enabled mobile phones and photogrammetry to achieve the same. In principle, this approach has a similar philosophy. However, instead of working with a few points with good satellite visibility that are obtained by a GNSS (Global Navigation Satellite System) rover, the procedure works with hundreds of observations with varying accuracy. Those accuracies depend on the satellite visibility. Each observation captures an image from the mobile phone together with the GNSS signal and its accuracy. Angle and distance measurements that traditionally are observed by a total station are retrieved by photogrammetry on the total image collection.

Estimation of Surface Water Level in Coal Mining Subsidence Area with GNSS RTK and GNSS-IR

Ground subsidence caused by underground coalmining result in the formation of ponding water on the ground surface. Monitoring the surface water level is crucial for studying the hydrologic cycle in mining areas. In this paper, we propose a combined technique using Global Navigation Satellite System Real-Time Kinematic (GNSS RTK) and GNSS Interferometric Reflectometry (GNSS-IR) to estimate the surface water level in areas of ground subsidence caused by underground coal mining. GNSS RTK is used to measure the geodetic height of the GNSS antenna, which is then converted into the normal height using the local height anomaly model. GNSS-IR is employed to estimate the height from the water surface to the GNSS antenna (or, the reflector height). To enhance the accuracy of the reflector height estimation, a weighted average model has been developed. This model is based on the coefficient of determination of the signal fitted by the Lomb-Scargle spectrogram and can be utilized to combine the reflector height estimations derived from multiple GNSS system and band reflection signals. By subtracting the GNSS-IR reflector height from the GNSS RTK-based normal height, the proposed method-based surface water level estimation can be obtained. In an experimental campaign, a low-cost GNSS receiver was utilized for the collection of dual-frequency observations over a period of 60 days. The collected GNSS observations were used to test the method presented in this paper. The experimental campaign demonstrates a good agreement between the surface water level estimations derived from the method presented in this paper and the reference observations.

Sky-GVIO: Enhanced GNSS/INS/Vision Navigation with FCN-Based Sky Segmentation in Urban Canyon

Accurate, continuous, and reliable positioning is critical to achieving autonomous driving. However, in complex urban canyon environments, the vulnerability of stand-alone sensors and non-line-of-sight (NLOS) caused by high buildings, trees, and elevated structures seriously affect positioning results. To address these challenges, a sky-view image segmentation algorithm based on a fully convolutional network (FCN) is proposed for NLOS detection in global navigation satellite systems (GNSSs). Building upon this, a novel NLOS detection and mitigation algorithm (named S−NDM) uses a tightly coupled GNSS, inertial measurement units (IMUs), and a visual feature system called Sky−GVIO with the aim of achieving continuous and accurate positioning in urban canyon environments. Furthermore, the system combines single-point positioning (SPP) with real-time kinematic (RTK) methodologies to bolster its operational versatility and resilience. In urban canyon environments, the positioning performance of the S−NDM algorithm proposed in this paper is evaluated under different tightly coupled SPP−related and RTK−related models. The results exhibit that the Sky−GVIO system achieves meter-level accuracy under the SPP mode and sub-decimeter precision with RTK positioning, surpassing the performance of GNSS/INS/Vision frameworks devoid of S−NDM. Additionally, the sky-view image dataset, inclusive of training and evaluation subsets, has been made publicly accessible for scholarly exploration.

Mitigating ionospheric scintillation effects on RTK-based long-span bridge deformation monitoring

Ionospheric scintillation presents significant challenges to the application of Global Navigation Satellite System (GNSS) for positioning and bridge deformation monitoring in low-latitude region. This study aims to develop a GNSS positioning model to improve long-span bridge deformation monitoring performance under ionospheric scintillation. We propose a new Rate of Total Electron Content (ROT) calculation method using undifferenced estimated ionosphere delays for identifying ionospheric scintillation. Then, we construct an undifferenced and uncombined (UDUC) ionosphere-refined Real-time Kinematic (RTK) model by replacing ionospheric spatial constraints with temporal constraints to mitigate the impact of ionospheric scintillation. RTK experiments are conducted on the South China Sea Bridge (SCSB), spanning 55 km. The results indicate that the new ROT calculation method can effectively identify observations affected by ionospheric scintillation, and the ionosphere-refined RTK model shows superior performance compared to ionosphere-float and ionosphere-weighted RTK model in terms of convergence time, Time to First Fix (TTFF), and positioning accuracy.

EMSA-IK: a real-time evolutionary multi-objective semi-analytical inverse kinematics algorithm for redundant manipulators

Purpose This paper aims to propose a real-time evolutionary multi-objective semi-analytical inverse kinematics (IK) algorithm (EMSA-IK) for solving the multi-objective IK of redundant manipulators. Design/methodology/approach Within EMSA-IK, the parameterization method is applied to reduce the number of optimization variables of the evolutionary algorithm and calculate semi-analytical solutions that meet high target pose accuracy. The original evolutionary algorithm is improved with the proposed adaptive search sub-space strategy so that the improved evolutionary algorithm can be used to efficiently perform global search within the parametric joint space to obtain the global optimal parametric joint angles that satisfy multi-objective constraints. Findings Ablation experiments show the effectiveness of the improved strategy used for evolutionary algorithms. Comparative experiments on different manipulators demonstrate the advantages of EMSA-IK in terms of generalizability and balancing multiple objectives, for example, motion continuity, joint limits and obstacle avoidance. Real-world experiments further validate the effectiveness of the proposed algorithm for real-time application. Originality/value The semi-analytical IK solution that simultaneously satisfies high target pose accuracy and multi-objective constraints can be obtained in real time. Compared to existing semi-analytical IK algorithms, the proposed algorithm achieves obstacle avoidance for the first time. The proposed algorithm demonstrates superior generalizability, applicable to not only redundant manipulators with revolute joints but also those with prismatic joints.

Remote marine precise point positioning with baseline length and troposphere-constrained models of the receivers for the oceanographic research vessel

ABSTRACT Research vessels are typically equipped with multiple receivers for positioning and attitude measurement; however, there is no data interaction or model fusion to implement the Precise Point Positioning (PPP) for these receivers. Therefore, a Constrained PPP (CPPP) is established by using the baseline length and tropospheric constraints of two receivers to improve the vessel’s remote marine positioning performance. Based on two integrated Real-Time Kinematic (RTK) receivers, marine experiments are conducted at a distance of 300–600 km from land. Compared to the ground environment, the Root Mean Square error (RMS) of the multipath and the STandard Deviation (STD) of the carrier-to-noise ratio in the marine environment are increased by 2.87 and 2.6 times, respectively. The length constraints reduce the RMS of positioning in the East, North, and Up (ENU) directions by about 0.053 (67%), 0.020 (34%), and 0.054 m (34%), respectively, and also rapidly recover positioning after interruptions, achieving positioning with errors in the ENU-directions of 10, 15, and 20 cm, respectively, within 3 minutes. When the baseline length and tropospheric constraints are combined, with or without the addition of the Zenith Wet Delay bias (dZWD), the average STD can be reduced by about 0.060 m (43%) and the accuracy of the up-positioning can be significantly improved. The correlation of dZWD to the up-positioning deviation of du=−2.161*dZWD is obtained by simulation. Since the acquisition of dZWD depends on the PPP accuracy, it is recommended that dZWD be set to compensate for unmodeled receiver errors when the STD of the up-positioning is superior to 0.06 m.

Thermal Infrared Orthophoto Geometry Correction Using RGB Orthophoto for Unmanned Aerial Vehicle

The geometric correction of thermal infrared (TIR) orthophotos generated by unmanned aerial vehicles (UAVs) presents significant challenges due to low resolution and the difficulty of identifying ground control points (GCPs). This study addresses the limitations of real-time kinematic (RTK) UAV data acquisition, such as network instability and the inability to detect GCPs in TIR images, by proposing a method that utilizes RGB orthophotos as a reference for geometric correction. The accelerated-KAZE (AKAZE) method was applied to extract feature points between RGB and TIR orthophotos, integrating binary descriptors and absolute coordinate-based matching techniques. Geometric correction results demonstrated a significant improvement in regions with stable and changing environmental conditions. Invariant regions exhibited an accuracy of 0.7~2 px (0.01~0.04), while areas with temporal and spatial changes saw corrections within 5~7 px (0.10~0.14 m). This method reduces reliance on GCP measurements and provides an effective supplementary technique for cases where GCP detection is limited or unavailable. Additionally, this approach enhances time and economic efficiency, offering a reliable alternative for precise orthophoto generation across various sensor data.

Are Modern Market-Available Multi-Rotor Drones Ready to Automatically Inspect Industrial Facilities?

Industrial inspection is a well-known application area for unmanned aerial vehicles (UAVs), but are modern market-available drones fully suitable for inspections of larger-scale industrial facilities? This review summarizes the pros and cons of aerial large-scale facility inspection, distinguishing it from other inspection scenarios implemented with drones. Moreover, based on paper analysis and additionally performed experimental studies, it reveals specific issues related to modern commercial drone software and demonstrates that market-available UAVs (including DJI and Autel Robotics) more or less suffer from the same problems. The discovered issues include a Global Navigation Satellite System (GNSS) Real Time Kinematic (RTK) shift, an identification of multiple images captured from the same point, limitations of custom mission generation with external tools and mission length, an incorrect flight time prediction, an unpredictable time of reaching a waypoint with a small radius, deviation from the pre-planned route line between two waypoints, a high pitch angle during acceleration/deceleration, an automatic landing cancellation in a strong wind, and flight monitoring issues related to ground station software. Finally, on the basis of the paper review, we propose solutions to these issues, which helped us overcome them during the first autonomous inspection of a 2400 megawatts thermal power plant.

Performance Evaluation of Real-Time Kinematic Global Navigation Satellite System with Survey-Grade Receivers and Short Observation Times in Forested Areas

The Real-Time Kinematic (RTK) method is currently the most widely used method for positioning using Global Navigation Satellite Systems (GNSSs) due to its accuracy, efficiency and ease of use. In forestry, position is a critical factor for numerous applications, with GNSS currently being the preferred solution for obtaining such data. However, the decreased performance of GNSS observations in challenging environments, such as under the forest canopy, must be considered. This paper analyzes the performance of a survey-grade GNSS receiver under coniferous/deciduous tree cover. Unlike most previous research concerning this topic, the focus here is on employing a methodology that is as close as possible to real working conditions in the field of forestry. To achieve this, short observation times of 30 s were used, with corrections received directly in the field from a Continuously Operating Reference Station (CORS) of the national RTK network in Romania. In total, 84 test points were determined, randomly distributed under the canopy, with reference data collected by topographical surveys using total station equipment. In terms of the overall horizontal accuracy, an RMSE of 2.03 m and MAE of 1.63 m are found. Meanwhile, the overall vertical accuracy is lower, as expected, with an RMSE of 4.85 m and MAE of 4.01 m. The variation in GNSS performance under the different forest compositions was found to be statistically significant, while GNSS-specific factors such as DOP values only influenced the precision and not the accuracy of observations. We established that this methodology offers sufficient accuracy, which is application-dependent, even if the majority of GNSS solutions were code-based, rather than carrier-phase-based, due to strong interference from the vegetation.

Intra- and interlimb effects of gait retraining in individuals with knee hyperextension

BackgroundGait retraining, which typically focuses on the most severely affected limb or joint, has shown promising results in treating faulty running and walking patterns. The closed-chain nature of gait during the stance phase may influence kinematic changes in the adjacent joints of the trained leg. In addition, the coupled nature of the lower extremity motion of gait suggests that changes in one leg may transfer to the other. This study aimed to assess the intra- and inter-limb transfer of kinematic changes following gait retraining to reduce knee extension in individuals with hyperextension walking patterns. MethodsSeventeen women with knee hyperextension gait patterns participated in six treadmill retraining sessions. All participants received verbal and real-time visual kinematic feedback in the form of knowledge of results. This intervention study took place at the Gait Analysis Laboratory at the University of Iowa. Mean peak sagittal-plane lower extremity joint kinematics during overground walking at pretraining, post-training, and 1- and 8-month follow-ups were calculated for analysis and comparisons. FindingsThe post-training changes in ankle range of motion returned to baseline values by the 8-month follow-up. There was a significant transfer effect of kinematic changes to the untrained knee following gait retraining. InterpretationTraining one knee did not result in long-term compensatory kinematic changes in the other joints. In addition, the improvements in knee extension range of motion were transferred to the untrained knee and retained at the 8-month follow-up. This study supports the use of gait retraining as an effective clinical intervention.

Accuracy assessment of UAV-based documentation of archaeological site: Kültepe-Kaneš

High quality 2D/3D metric documentation of archaeological sites is used in many different applications such as archaeological-heritage management, digital archaeological excavation planning, orthophotographic documentation, and ancient Digital Surfaces Models (DSM) research. Structure-from-Motion based photogrammetry (SfM) is an indirect geodesic measurement technique based on multiple view image processing using high-level automation techniques. Using SfM to generate the high accuracy 2D/3D data needed for digital documentation of archaeological cultural heritage is relatively practical, economical, and fast. Factors such as the number of ground control points and their distribution to the study area, the robustness of the camera system model parameters, and the analytical model of the photogrammetric triangulation method used affect the accuracy of the data produced using SfM-photogrammetry. Kültepe-Kaneš, the center of the ancient Kingdom of Kaneš, which is located in central-Anatolia, was an Assyrian Trade Colony active between ca. 2000 BC and 1700 BC. The site, which was the center of the Old Assyrian trade colonies in Anatolia and one of the most important sites in ancient history, has been under excavation for the last 75 years. In this paper, high accuracy digital documentation of the Kültepe-Kaneš archaeological excavation area was made using different SfM methods. Statistical analysis revealed no significant difference in accuracy between Real-Time Kinematic (RTK) and Post-Process Kinematic (PPK) methods for the study area. This suggests that either PPK, RTK, or aerial triangulation with Ground Control Points (GCPs) can be employed to generate orthophotos and DSMs for archaeological sites with relatively flat surface areas, as long as a sufficient number of uniformly distributed GCPs are used.

Development of a Robotic Platform with Autonomous Navigation System for Agriculture

The development of autonomous agricultural robots using a global navigation satellite system aided by real-time kinematics and an inertial measurement unit for position and orientation determination must address the accuracy, reliability, and cost of these components. This study aims to develop and evaluate a robotic platform with autonomous navigation using low-cost components. A navigation algorithm was developed based on the kinematics of a differential vehicle, combined with a proportional and integral steering controller that followed a point-to-point route until the desired route was completed. Two route mapping methods were tested. The performance of the platform control algorithm was evaluated by following a predefined route and calculating metrics such as the maximum cross-track error, mean absolute error, standard deviation of the error, and root mean squared error. The strategy of planning routes with closer waypoints reduces cross-track errors. The results showed that when adopting waypoints every 3 m, better performance was obtained compared to waypoints only at the vertices, with maximum cross-track error being 44.4% lower, MAE 64.1% lower, SD 39.4% lower, and RMSE 52.5% lower. This study demonstrates the feasibility of developing autonomous agricultural robots with low-cost components and highlights the importance of careful route planning to optimize navigation accuracy.

Study of Global Navigation Satellite System Receivers' Accuracy for Unmanned Vehicles.

The development of unmanned ground vehicles and unmanned aerial vehicles requires high-precision navigation due to the autonomous motion and higher traffic intensity. The existing L1 band GNSS receivers are a good and cheap decision for smartphones, vehicle navigation, fleet management systems, etc., but their accuracy is not good enough for many civilian purposes. At the same time, real-time kinematic (RTK) navigation allows for position precision in a sub-centimeter range, but the system cost significantly narrows this navigation to a very limited area of applications, such as geodesy. A practical solution includes the integration of dual-band GNSS receivers and inertial sensors to solve high-precision navigation tasks, but GNSS position accuracy may significantly affect IMU performance due to having a great impact on Kalman filter performance in unmanned vehicles. The estimation of dilution-of-precision (DOP) parameters is essential for the filter performance as the optimality of the estimation in the filter is closely connected to the quality of a priori information about the noise covariance matrix and measurement noise covariance. In this regard, the current paper analyzes the DOP parameters of the latest generation dual-band GNSS receivers and compares the results with the L1 ones. The study was accomplished using two types of antennas-L1/L5 band patch and wideband helix antennas, which were designed and assembled by the authors. In addition, the study is extended with a comparison of GNSS receivers from different generations but sold on the market by one of the world's leading GNSS manufacturers. The analyses of dilution-of-precision (DOP) parameters show that the introduction of dual-band receivers may significantly increase the navigation precision in a sub-meter range, in addition to multi-constellation signal reception. The fast advances in the performance of the integrated CPU in GNSS receivers allow the number of correlations and tracking satellites to be increased from 8-10 to 24-30, which also significantly improves the position accuracy even of L1-band receivers.

Decimeter-Level Accuracy for Smartphone Real-Time Kinematic Positioning Implementing a Robust Kalman Filter Approach and Inertial Navigation System Infusion in Complex Urban Environments.

New smartphones provide real-time access to GNSS pseudorange, Doppler, or carrier-phase measurement data at 1 Hz. Simultaneously, they can receive corrections broadcast by GNSS reference stations to perform real-time kinematic (RTK) positioning. This study aims at the real-time positioning capabilities of smartphones using raw GNSS measurements as a conventional method and proposes an improvement to the positioning through the integration of Inertial Navigation System (INS) measurements. A U-Blox GNSS receiver, model ZED-F9R, was used as a benchmark for comparison. We propose an enhanced ambiguity resolution algorithm that integrates the traditional LAMBDA method with an adaptive thresholding mechanism based on real-time quality metrics. The RTK/INS fusion method integrates RTK and INS measurements using an extended Kalman filter (EKF), where the state vector x includes the position, velocity, orientation, and their respective biases. The innovation here is the inclusion of a real-time weighting scheme that adjusts the contribution of the RTK and INS measurements based on their current estimated accuracy. Also, we use the tightly coupled (TC) RTK/INS fusion framework. By leveraging INS data, the system can maintain accurate positioning even when the GNSS data are unreliable, allowing for the detection and exclusion of abnormal GNSS measurements. However, in complex urban areas such as Qazvin City in Iran, the fusion method achieved positioning accuracies of approximately 0.380 m and 0.415 m for the Xiaomi Mi 8 and Samsung Galaxy S21 Ultra smartphones, respectively. The subsequent detailed analysis across different urban streets emphasized the significance of choosing the right positioning method based on the environmental conditions. In most cases, RTK positioning outperformed Single-Point Positioning (SPP), offering decimeter-level precision, while the fusion method bridged the gap between the two, showcasing improved stability accuracy. The comparative performance between the Samsung Galaxy S21 Ultra and Xiaomi Mi 8 revealed minor differences, likely attributed to variations in the hardware design and software algorithms. The fusion method emerged as a valuable alternative when the RTK signals were unavailable or impractical. This demonstrates the potential of integrating RTK and INS measurements for enhanced real-time smartphone positioning, particularly in challenging urban environments.

Continuous High-Precision Positioning in Smartphones by FGO-Based Fusion of GNSS-PPK and PDR.

The availability of raw Global Navigation Satellites System (GNSS) measurements in Android smartphones fosters advancements in high-precision positioning for mass-market devices. However, challenges like inconsistent pseudo-range and carrier phase observations, limited dual-frequency data integrity, and unidentified hardware biases on the receiver side prevent the ambiguity resolution of smartphone GNSS. Consequently, relying solely on GNSS for high-precision positioning may result in frequent cycle slips in complex conditions such as deep urban canyons, underpasses, forests, and indoor areas due to non-line-of-sight (NLOS) and multipath conditions. Inertial/GNSS fusion is the traditional common solution to tackle these challenges because of their complementary capabilities. For pedestrians and smartphones with low-cost inertial sensors, the usual architecture is Pedestrian Dead Reckoning (PDR)+ GNSS. In addition to this, different GNSS processing techniques like Precise Point Positioning (PPP) and Real-Time Kinematic (RTK) have also been integrated with INS. However, integration with PDR has been limited and only with Kalman Filter (KF) and its variants being the main fusion techniques. Recently, Factor Graph Optimization (FGO) has started to be used as a fusion technique due to its superior accuracy. To the best of our knowledge, on the one hand, no work has tested the fusion of GNSS Post-Processed Kinematics (PPK) and PDR on smartphones. And, on the other hand, the works that have evaluated the fusion of GNSS and PDR employing FGO have always performed it using the GNSS Single-Point Positioning (SPP) technique. Therefore, this work aims to combine the use of the GNSS PPK technique and the FGO fusion technique to evaluate the improvement in accuracy that can be obtained on a smartphone compared with the usual GNSS SPP and KF fusion strategies. We improved the Google Pixel 4 smartphone GNSS using Post-Processed Kinematics (PPK) with the open-source RTKLIB 2.4.3 software, then fused it with PDR via KF and FGO for comparison in offline mode. Our findings indicate that FGO-based PDR+GNSS-PPK improves accuracy by 22.5% compared with FGO-based PDR+GNSS-SPP, which shows smartphones obtain high-precision positioning with the implementation of GNSS-PPK via FGO.

Research on Satellite Navigation Control of Six‐Crawler Machinery Based on Fuzzy PID Algorithm

ABSTRACTThe six‐crawler driving mechanism plays a crucial role in the operation of large machines such as bucket‐wheel excavators, dumping machines, and mobile crushing stations, as it serves functions like bearing, movement and steering. The driving characteristics of this mechanism directly influence the safety and efficiency of these machinery systems. To enhance the design methodology for multi‐crawler machinery, improve path controllability, and achieve adaptive driving, a satellite navigation control system for six‐crawler machinery was developed based on the principles of real‐time kinematic (RTK) satellite positioning. This system utilizes the distance deviation and heading angle deviation between the actual path and the predetermined path of the six‐crawler machinery as inputs to a fuzzy proportion integration differentiation (fuzzy PID) controller. This controller regulates the deviation angle of the steering crawler and the driving speeds of each track, thereby ensuring precise path tracking control. To evaluate the path tracking control performance under both straight and curved driving conditions, a virtual prototype model of the six‐crawler mechanical system was established, and co‐simulation analysis was conducted. In addition, an experimental platform for path tracking control of six‐crawler machinery was established to validate the efficacy of the satellite navigation system. The actual tracking data obtained from various driving conditions and initial deviations demonstrated that the RTK satellite navigation path tracking control system exhibited excellent control performance.

Statistical analysis and effects of radio frequency interference in GPS signal quality in Thailand

The radio frequency interference (RFI) in global navigation satellite system (GNSS) signals has recently received much attention in the GNSS community because of frequent jamming issues. The carrier-to-noise density ratio (C/N0) is one of the common parameters to indicate the signal quality. In this work, we propose a real-time RFI analysis based on windowing and normalization of C/N0 observations. Specifically, the percentage of RFI values are analyzed based on the modified RFI detection. The steps to analyze the RFI levels (low, medium, high) are highlighted. In addition, we analyzed the occurrences of local RFI effects in areas surrounding the Suvarnabhumi International Airport as well as remote areas. We validate the modified RFI detection by using the GNSS reference stations at the urban, suburban, and outside the capital city in Thailand. The user positioning errors with the high (severe) RFI levels are investigated based on the single point positioning (SPP) and real-time kinematics (RTK). From the experimental simulations, the high RFI levels at the urban are higher than those at the suburban. As expected, the statistical analysis covering COVID-19 (2019 to 2023) shows that the high RFI levels in June 2023 (post COVID-19) are more than those in June 2020 and 2021 (lockdown COVID-19) by about twofold. Additionally, the SPP positioning errors with the medium/high RFI levels are clearly seen. There are more floating solutions in the RTK system in the year with more RFI presence.

Comparison between aerial imagery and conventional cadastral mapping methods in Ekiti State Nigeria; towards a fit-for-purpose approach

Towards achieving Fit-for-Purpose (FFP) cadastral mapping, this study compares conventional cadastral mapping methods of theodolite traverse, total station and Real Time Kinematic Global Navigation Satellite System (RTK GNSS) with high-resolution aerial imagery in Ekiti State, Nigeria. Evaluating time, cost, accuracy, and coverage, it finds that high-resolution aerial imagery can achieve results comparable to conventional instruments with wider coverage, thereby expediting land registration and fostering sustainable development. However, challenges in obtaining high-resolution imagery necessitate regulatory reform for UAV use. The study recommends adoption of innovative solutions to improve the spatial, legal, and institutional frameworks in the state and enhance land governance.

A New Precise Point Positioning with Ambiguity Resolution (PPP-AR) Approach for Ground Control Point Positioning for Photogrammetric Generation with Unmanned Aerial Vehicles

Unmanned aerial vehicles (UAVs) are now widely preferred systems that are capable of rapid mapping and generating topographic models with relatively high positional accuracy. Since the integrated GNSS receivers of UAVs do not allow for sufficiently accurate outcomes either horizontally or vertically, a conventional method is to use ground control points (GCPs) to perform bundle block adjustment (BBA) of the outcomes. Since the number of GCPs to be installed limits the process in UAV operations, there is an important research question whether the precise point positioning (PPP) method can be an alternative when the real-time kinematic (RTK), network RTK, and post-process kinematic (PPK) techniques cannot be used to measure GCPs. This study introduces a novel approach using precise point positioning with ambiguity resolution (PPP-AR) for ground control point (GCP) positioning in UAV photogrammetry. For this purpose, the results are evaluated by comparing the horizontal and vertical coordinates obtained from the 24 h GNSS sessions of six calibration pillars in the field and the horizontal length differences obtained by electronic distance measurement (EDM). Bartlett’s test is applied to statistically determine the accuracy of the results. The results indicate that the coordinates obtained from a two-hour PPP-AR session show no significant difference from those acquired in a 30 min session, demonstrating PPP-AR to be a viable alternative for GCP positioning. Therefore, the PPP technique can be used for the BBA of GCPs to be established for UAVs in large-scale map generation. However, the number of GCPs to be selected should be four or more, which should be homogeneously distributed over the study area.

Accuracy and reliability improved GNSS partial ambiguity resolution assisted by a MEMS inertial measurement unit

Traditional partial ambiguity resolution (PAR) methods based on integer least-squares (ILS-PAR) assume that the ambiguity terms are unbiased integers, which is seldomly true in challenging environments of the Global Navigation Satellite System (GNSS). The bias will lead to unreliable positioning solutions. This study proposes a reliable PAR method based on the tightly coupling of GNSS and inertial navigation system (INS) and the solution separation with external solution (SSE) statistical testing algorithm. First, the inertial measurement unit (IMU) mechanization results are compensated using the latest fixed real-time kinematic (RTK) solutions, thus high-accuracy INS predictions are obtainable at the current GNSS epoch. Second, the SSE method based on double-differenced (DD) carrier-phase measurements are applied to select and validate the ambiguity subset and perform the GNSS/INS integration. A dynamic vehicular experiment with a low-cost microelectromechanical systems (MEMS) device has been conducted and the results indicate that the proposed method can ensure good performance of both accuracy and reliability.