Performance Characterization of Tightly-Coupled GNSS Precise Point Positioning Inertial Navigation within a Simulation Environment

Monitoring the response of engineering structures, such as tall buildings, tower and large-scale bridges, under severe loading conditions, such as strong earthquake or wind storm, is an important requirement to verify their design and construction and to evaluate structural condition and reliability. In the last two decades, high-rate real-time or post-processed kinematic differential Global Positioning System (DGPS) has been widely used in dynamic displacement measurements of civil engineering structures. In recent years, interest has increased for Precise Point Positioning (PPP) due to its capability to generate positioning solutions as accurate as DGPS. In this study, the potential of post-processed kinematic PPP in terms of monitoring dynamic displacement response of a structure has been explored based on free damped oscillation events obtained from a model structure, which is able to vibrate in the fundamental and higher modes of vibration. A number of experiments have been carried out and five events, each of which is different character, have been selected to compare PPP results with DPGS results in the time and frequency domain. The results clearly demonstrate that the PPP method, like the DGPS method, offers great potential for the measurement of horizontal and vertical dynamic movement of structures. The impact of a short period (one minute) of observation length on the result of the kinematic PPP method was also investigated in terms of sensing the dynamic movement of a structure. Twenty selected one-minute data-sets extracted from a one-hour original data-set were processed by Canadian spatial reference system PPP and each one-minute PPP solution was compared with the corresponding segment obtained from the one-hour PPP solution. The results show that the one-minute PPP solution is able to extract the fundamental natural frequency of the oscillation in the horizontal and vertical component just like the one-hour PPP solution after the offset is removed and the lower frequency trend component is filtered out.

Precise Point Positioning (PPP) is a stand-alone precise positioning approach. As the quality of satellite orbit and clock products from analysis centers has been improved, PPP can provide more precise positioning accuracy and reliability. A combined use of Global Positioning System (GPS) and Global Orbiting Navigation Satellite System (GLONASS) in PPP is now available. In this paper, we explained about an approach for combined GPS and GLONASS PPP measurement processing, and validated the performance through the comparison with GPS-only PPP results. We also used the measurement obtained from the GRAS reference station for the performance validation. As a result, we found that the combined GPS/GLONASS PPP can yield a more precise positioning than the GPS-only PPP.

Precise Point Positioning (PPP) algorithms have been widely used in the Global Positioning System (GPS)-based applications. A PPP technique with a single receiver provides effective solutions where accurate absolute positioning is required. This paper provides the performance assessment of GPS PPP for detecting the displacements caused by an earthquake. For this purpose, the earthquake that occurred on 21 July 2017 at Kos-Bodrum with the impact of Mw 6.6 was investigated by analyzing the data of the permanent GPS stations located around the related region with the PPP technique. The location distances of these GPS stations range from 10 to 89 km to the epicenter of this earthquake. GPS data provided from seven permanent stations from the Continuously Operating Reference Stations-Turkey (CORS-TR) and local Bodrum CORS networks were processed to determine the co-seismic displacements during the earthquake. The data of these stations for days of year (DOYs) 200, 201, 202, and 203 were analyzed with post-process static PPP and kinematic PPP methods. GIPSY-OASIS II v6.4 was used for processing the data and all of the solutions were performed in the ITRF2008 reference frame. Two strategies were followed on the post-process static solutions. In the first strategy, 4-day data with 24-h observations were separately analyzed day by day. In the second strategy, the 24-h data were divided into 3-h duration, which is the minimum duration for optimum PPP solutions, and then the analyses were performed. When the displacements between DOYs 200 and 203 are considered in the 24-h data analysis, significant displacements have been observed through northwest direction in the northern stations whereas MUG1 is excluded. Moreover, there is significant displacement through the southeast direction in the station DATC located in the south of the epicenter. When the 3-h solutions are examined, displacements, especially on n and e directions, are observed starting from the solutions, which include Mw 6.6 earthquake. According to the kinematic PPP solutions, the effects of the Mw 6.6 earthquake can be seen clearly in the stations DATC, ORTA, TRKB, and YALI. Considering all outcomes, the PPP technique with both static and kinematic solutions provides effective results for detecting the displacements during the earthquake.

This paper presents an adaptive learning method for data fusion in autonomous\ndriving vehicles. The localization is based on the integration of Inertial\nMeasurement Unit (IMU) with two Real-Time Kinematic (RTK) Global Positioning\nSystem (GPS) units in an adaptive Kalman filter (KF). The observability\nanalysis reveals that $i$) integration of a single GPS with IMU does not\nconstitute an observable system; $ii$) integration of two GPS units with IMU\nresults in a locally observable system provided that the line connecting two\nGPS antennas is not parallel with the vector of the measured acceleration,\ni.e., the sum of inertial and gravitational accelerations. The latter case\nmakes it possible to compensate for the error in the estimated orientation due\nto gyro drift and its bias without needing additional instruments for absolute\norientation measurements, e.g., a magnetic compass. Moreover, in order to cope\nwith the fact that GPS systems sometimes lose their signal and receive\ninaccurate position data, the self-tuning filter estimates the covariance\nmatrix associated with the GPS measurement noise. This allows the KF to\nincorporate GPS measurements in the data fusion process heavily only when the\ninformation received by GPS becomes reliably available.\n

For precise positioning in arctic regions with Global Navigation Satellite Systems (GNSS), such as GPS and Glonass, there are a number of issues to be resolved or taken into account. The most important ones are satellite geometry, ionospheric effects and distribution of correction data. Precise Point Positioning (PPP) is currently the standard for precise offshore positioning. PPP requires a sparse global network of GNSS reference stations to estimate precise satellite orbit and clock parameters in real-time. These parameters are transmitted to users, who can compute their position with an accuracy of 0.1 m using code and carrier observations. The main disadvantage of PPP is that in general it takes a long time to converge to this accuracy, about 30–45 minutes. GNSS carrier observations are similar to pseudo ranges, but have an additional bias which needs to be estimated. Under certain conditions, these biases are integer. This property is used in what is generally referred to as Real-Time Kinematic (RTK) positioning, a technique which uses corrections generated at reference stations to make sure these ambiguities are integer. Integer Ambiguity Resolution (IAR) results in RTK accuracies of 0.01–0.03 m or better and short convergence times, ranging from instantaneous to several minutes for long inter-station distances. The disadvantage is the limited area of applicability, because RTK in general does not use precise orbits and clocks. Current research focuses on the combination of PPP and RTK techniques. The main goal is to achieve cm accuracy with a sparse network of reference stations. Another goal is to reduce convergence time. Applications are in the field of precise real-time offshore positioning in general, and subsidence monitoring and tidal estimation in particular. Results will be presented from standard PPP and PPP combined with IAR for arctic regions and from a test bed in the Gulf of Mexico. These results, although preliminary, indicate centimeter level accuracy is indeed possible, also in the arctic. We will also look at further improvements, mainly in convergence time, using all operational satellites and signals from current and future navigation systems.

Real-time kinematic (RTK) global positioning system (GPS) receivers are being marketed for applications where accurate estimates of elevation are required. Because this technology is fairly expensive, the quality of these data should be considered with respect to that of USGS digital elevation DEMs (digital elevation models) that are freely available for most of the United States at the 30-m grid scale and for some areas on 10-m grids. The objective of this study was to compare terrain attributes calculated from USGS DEMs with those calculated from DEMs developed with precision RTK GPS measurements. At two locations in central Kentucky, intensive elevation measurements were collected with RTK GPS. The USGS and RTK data for these areas were interpolated to create 4-m DEMs for comparing terrain attributes. Correlations between the attributes developed from different DEMs were substantially larger for slope and aspect than for curvature, topographic wetness index, and stream power index values. Although there were large quantitative differences in terrain attribute values, the general spatial patterns were similar for the attributes calculated from the RTK and USGS DEMs. However, landscape features defined using DEMs developed with RTK data were more similar to those observed with 10- than 30-m USGS DEMs. For some course-scale applications, 30-m USGS DEMs may be adequate for identifying important landscape characteristics. However, the resolution of many of these features will be substantially better with 10-m USGS DEMs. However, quantitative estimates of terrain attributes at a specific location may be grossly incorrect. For situations where accuracy is essential, precision elevation surveys will be required.

Since Global Positioning System (GPS) has been routinely conducted in many engineering projects, it is also effectively applied to the assessment and preventing of forest and natural resources. Depending on the GPS survey method preferred in the applications performed around the forest environments, different level point positioning accuracy can be achieved. Traditionally, for many precise positioning applications, relative static positioning has been used. The data obtained have been analyzed with high-cost scientific and commercial software, which are required a good knowledge of processing procedures. However, in recent years, web based online services that use Precise Point Positioning (PPP) technique, developed as a special type of relative positioning, that enables to process and analyze the static data easily, have become a significant alternative for users. These developments on GPS based surveyings that significantly make contributions to the studies applied around the forest environment, in terms of time, cost, accuracy and labour are preferred in many engineering facilities. In this study, it is aimed to research performance of GPS PPP technique and web based online services in positioning applications especially performed around the forest environments. For this purpose, two test stations have been established in different locations around the forest area, located in Campus of Davutpasa, Yildiz Technical University, Istanbul, and stations have been observed repeatedly in static GPS surveying mode for 3 days and per day with 3-hours observation duration. The observations have been computed by commercial software as using final GPS ephemerides products so called TopconTools v8.2 and also by web based online services namely OPUS, AUSPOS, CSRS-PPP, GAPS and APPS. From the results, when 3D positioning differences have been examined, it is seen that the positional accuracy is range from 0.024 m to 0.251 m for TP01 and from 0.078 m to 1.033 m for TP02 with respect to both relative solution and PPP solution, which is used by web based online services. When the results have been examined for only CSRS-PPP, APPS and GAPS services, which are used PPP solution, it is seen that the positional accuracy for 3D positioning differences is range from 0.024 m to 0.251 m for TP01 and from 0.078 m to 0.859 m for TP02. The results show that since the static GPS data is collected for duration of 3-hours and more, PPP technique and the web based online services using this technique for precise positioning applications around the forest environment give effective solutions to the users and at the same time decrease the survey cost with respect to equipment and software.

Various corrector surface models are proposed to mitigate systematic height errors to fit the orthometric heights determined by combining the Tainan City real-time kinematic (RTK) global positioning system (GPS) network and the local geoid model data to the published orthometric heights. Several data sets for Tainan City were tested and analyzed. Two geometric geoid models and one gravimetric-geometric geoid model were generated using the GPS and leveling data. Consequently, three types of orthometric heights were determined (Models I, II, and III). The selection of the optimal corrector surface model for different models was based on a series of statistical tests. The test results show that (1) the selection of the optimal corrector surface model is highly related to the geoid model generating method, hence the optimal corrector surface models are a fifth-degree polynomial for Models I and II and a seven-parameter similarity transformation for Model III; and (2) the determined orthometric height ...

In this paper, we present a complete set of solutions to detect the location of the autonomous horticulture rover used for precision agriculture purposes during the early growth stage of the crops. The horticulture rover autonomously traverses the furrow by aligning itself with the centerline using the dynamic inversion navigation algorithm. The navigation algorithm takes the cross-track error and heading error of the rover deviating from the centerline as the location input, and outputs the desired left and right track speeds to the control system to correct the rover course. The rover has been using the real time kinematic (RTK) -based global position system (GPS) as the sensor to detect the location of the rover, but satellite signals can suffer from sporadic loss, and the geographical characteristics of the environment need to be accurately mapped beforehand. These limits of RTK GPS drastically increase the work load of the operators and decrease the location detection accuracy of the rover. The proposed easy-to-implement machine-vision based location detection solution set accepts the raw pictures taken by the camera mounted on the rover as input and calculate the cross-track and heading errors of the rover as outputs. It neither requires the usage of GPS, nor acquisition of environmental geographical information beforehand. Our test results indicate that the proposed machine-vision based solution set is able to outperform the RTK GPS by providing the cross-track location and heading information of the rover with an error less than 20% of that achieved by a RTK GPS, when the rover is within the furrow during the early growth stage.

Abstract. In the fields of mapping, surveying, and three-dimensional (3D) modeling, unmanned aerial vehicle (UAV) systems have become essential equipment in recent times. UAVs are increasingly widely used, especially in the field of photogrammetry. The integration of technologies such as digital cameras, inertial measurement unit (IMU), and Global Navigation Satellite System (GNSS) has improved the quality and accuracy of photogrammetric products. In comparison to conventional methodologies, UAVs present a cost-effective alternative to traditional aerial photogrammetry. Recent advancements in technology substantiate their efficacy across a variety of applications. The utilization of direct georeferencing minimizes the reliance on ground control points (GCP). With the advancements in positioning techniques, the accuracy of the products is concurrently improving. Real-Time Kinematic (RTK) and Post-Processed Kinematic (PPK) techniques play a critical role in enhancing the accuracy of UAV-based photogrammetry. Both techniques are widely used in UAV-based photogrammetry. However, relative positioning poses limitations to the study in terms of infrastructure and cost. PPP (Precise Point Positioning), a specific form of absolute positioning, is utilized effectively across various applications. The PPP method, used globally with a single GNSS receiver, is more cost-effective than relative methods. In this study, the performance of the PPP-AR technique as an alternative to the relative methods RTK and PPK is evaluated. Thus, the applicability of the PPP technique, which has improved accuracy and precision with ambiguity resolution, in UAV-based photogrammetry is examined. RTK and PPK techniques achieve Root Mean Square Error (RMSE) values of less than 10 centimeters. In contrast, RMSE values at the decimeter level are observed in the PPP-AR technique.

RTK GPS mapping of transplanted row crops

Being accessible and processible of the raw GNSS data of smartphones has been an innovation for low-cost GNSS positioning studies. With the release of world’s first smartphone with dual frequency GNSS chipset Mi8 by Xiaomi in May 2018, studies on smartphone-based positioning for engineering applications have gained great momentum. Considering these development dynamics, in this study, repeatedly collected Xiaomi Mi8 dual frequency static GNSS observations for two days in two-hour time span were processed using GipsyX and RTKLIB software with epoch by epoch kinematic Precise Point Positioning (PPP) method at different satellite elevation angles, and horizontal positioning accuracies were calculated. The PPP performance of dual frequency GNSS observations collected by Xiaomi Mi8 was investigated at different satellite elevation angles. The process outputs were compared with results analyzed by relative positioning method collected simultaneously with Topcon Hiper SR geodetic receiver by considering as a reference solution. According to the results, it was noted that the horizontal positioning accuracy of RTKLIB outputs has directly inverse relationship with increasing satellite elevation angles whereas GipsyX outputs have differences in this context. In the processing of Xiaomi Mi8 dual frequency observations with PPP method, it was concluded that GipsyX produced higher horizontal positioning accuracy than RTKLIB.

The Global Positioning system (GPS) is used for navigation and associated tasks in wide variety of applications. One of the primary modes of GPS operation is differential GPS. Differential GPS allows more accurate positioning than stand-alone GPS. Many new applications are possible because of the increased accuracy obtained through differential GPS. In this paper the techniques and methods of differential GPS along with the algorithms are discussed which are providing more accurate and precise positioning in recent trends of communication. The purpose of the paper is to introduce the principles of differential GPS theory, and to provide a background for more advanced material.

Autonomous driving is essential for the automation of agricultural systems, and current research primarily relies on using global positioning system (GPS) signals. However, in environments where GPS signals are unstable or denied, such as canopies and smart farms, GPS-based autonomous driving systems face limitations. Therefore, this study proposes an unmanned aerial vehicle autonomous driving system using three-dimensional light detection and ranging simultaneous localization and mapping (3D LiDAR SLAM). The proposed algorithm follows three steps: (1) A map is generated using 3D LiDAR. Because it targets an environment with height restrictions, lightweight and ground-optimized LiDAR odometry and mapping (LeGO-LOAM), which has the characteristic of extracting the ground, is used as a 3D LiDAR SLAM algorithm. (2) Noise is removed through post-processing. (3) A path is generated using the A* algorithm. To evaluate the performance of the proposed system, field evaluations were conducted in an outdoor canopy orchard using GPS and real time kinematic (RTK) GPS data as references. The experimental results verified the limitations of existing GPS- and RTK GPS-based methods and demonstrated the good performance and effectiveness of autonomous driving using 3D LiDAR SLAM. These findings suggest the feasibility of automated operations in environments where GPS is unstable or denied, and efficient agricultural automation may be achieved in conjunction with future harvesting and pollination operations.

GNSS observation outage occurs inevitably in various situations, e.g., automobile driving in urban environments. Although the ambiguity resolution (AR) significantly shortens the initialization time of precise point positioning (PPP), frequent re-initialization of PPP AR may be needed due to outages. The inertial navigation system (INS) can be used for acquiring highly accurate position information during GNSS outages. In the previous studies, the GPS PPP/INS with the ambiguity resolution model is proposed, and the experimental results confirm that the INS could facilitate the re-fixing of the interrupted GNSS ambiguity. Multiple GNSS can also be used to shorten the PPP convergence time. We compare the contribution of multi-GNSS and the INS to the ambiguity re-fixing during GNSS outage. Results show that the multi-GNSS, e.g., Galileo, GLONASS and BDS, without ambiguity resolution has little contribution to the re-fixing of GPS ambiguity in PPP/INS, while INS can provide highly accurate positioning results during the GNSS outages. The higher the accuracy of the predicted INS positioning, the lower the contribution of multi-GNSS to the re-fixing of the ambiguity in the PPP/INS. The finding is verified by a theoretical analysis, carborne experiment and shipborne experiment. Experiment results show that the re-fixing time is 43 s for GPS PPP and MEMS-grade INS coupled system in GNSS outage of 1 s. The re-fixing time of GPS is slightly changed when adding the multi-GNSS, e.g., Galileo, GLONASS and BDS, without the ambiguity resolution. However, by performing ambiguity resolution to the added GNSS system, the re-fixing time of PPP/INS is significantly reduced from 43 to 4 s. The reason is that, although the multi-GNSS provides little improvement on the accuracy of the ambiguity, it enlarges the number of the ambiguity parameter. The possibility of ambiguity resolution is increased due to the large candidate set of the ambiguity, which reduces re-fixing time.