High-precision Global Positioning System Research Articles

A Novel Method for Automatic Detection and Elimination of the Jumps Caused by the Instantaneous Disturbance Torque in the Maglev Gyro Signal

The signal measured by the maglev gyro sensor is sensitive to the influence of the instantaneous disturbance torque caused by the instantaneous strong wind or the ground vibration, which reduced the north-seeking accuracy of the instrument. To address this issue, we proposed a novel method combining the heuristic segmentation algorithm (HSA) and the two-sample Kolmogorov-Smirnov (KS) test (named HSA-KS method) to process the gyro signals and improve the north-seeking accuracy of the gyro. There were two key steps in the HSA-KS method: (i) all the potential change points were automatically and accurately detected by HSA, and (ii) the jumps in the signal caused by the instantaneous disturbance torque were quickly located and eliminated by the two-sample KS test. The effectiveness of our method was verified through a field experiment on a high-precision global positioning system (GPS) baseline at the 5th sub-tunnel of the Qinling water conveyance tunnel of the Hanjiang-to-Weihe River Diversion Project in Shaanxi Province, China. Our results from the autocorrelograms indicated that the jumps in the gyro signals can be automatically and accurately eliminated by the HSA-KS method. After processing, the absolute difference between the gyro and high-precision GPS north azimuths was enhanced by 53.5%, which was superior to the optimized wavelet transform and the optimized Hilbert-Huang transform.

Dual-band optoelectronic poaching detection systems

Subject of study. We present details regarding the development of dual-band optoelectronic scanning systems for surveillance and detection of poachers and poaching equipment and the inclusion of image fusion and geolocation capabilities. Aim. We present research on a dual-band optoelectronic system for scanning the surface along a quasicircular trajectory that supports overlapping of frames for efficient fusion of images made from different points of view into a single image used to detect, recognize, and geolocate poaching. Methods. We present simulation and experimental study of a prototype system including television and thermal vision channels, a Global Positioning System (GPS) antenna, and inertial navigation system modules mounted on a stabilized common platform. Main results. We propose a system design that will support simultaneous scanning of a search area in television and thermal imaging channels along a quasicircular trajectory, with the capability to expand the search area and provide 30% frame overlap for efficient image fusion. Gyroscopic sensors on the stabilized common platform for the system and global navigation system antennas will support the requisite accuracy of the surveillance platform and target geolocation. The change in system viewing angle per unit time that would enable the resulting image to be obtained without missing any lines was determined. The primary components of the error in the coordinates of the surveillance platform when surveilling an object were also determined. The combination of field-of-view scanning and use of geolocation equipment supports the recognition of poachers and poaching equipment and the determination of their coordinates within a global coordinate system. An integrated high-precision GPS receiver (ProPak-V3-424) with an inertial system and data processing technology using Tightly Coupled IMU algorithms (Inertial Explorer) was found to be capable of determining the horizontal coordinates of a surveillance platform to within 12 m at a probability of 95% or better. Practical significance. A prototype of the proposed design increased the maximum reliable detection and recognition range for poachers and poaching equipment (cars and trucks) in a forest through the fusion of data obtained in the visible and infrared spectral bands.

Evaluating Vertical Accuracies of Open-Source Digital Elevation Models over Multiple Sites in China Using GPS Control Points

Digital elevation models (DEMs) are widely used across a range of fields. Several open-source global DEMs have been released, including the advanced land observing satellite world 3D 30 m DEM (AW3D30DEM), advanced spaceborne thermal emission and reflection radiometer global DEM (ASTER GDEM), shuttle radar topography mission DEM (SRTMDEM), and TerraSAR-X for digital elevation measurement (TanDEM-X). ASTER and SRTM are the most widely used DEMs, while the newer models AW3D30DEM and TanDEM-X are becoming increasingly popular. Many studies have evaluated the qualities of these DEMs; however, few multi-regional studies have been conducted in China. To comprehensively and systematically evaluate the qualities of these DEMs in China, the vertical accuracies of AW3D, ASTER, STRM (all 30 m), and TanDEM-X (90 m) were tested across 16 regions in China. Using high-precision global positioning system control points for reference, error values were determined by subtracting these reference values from corresponding global DEM elevation values. As the study only covered flat areas (slope < 5°), slope was treated as a controlled variable. After assessing the impacts of the slope aspect and land cover type, variations in vertical accuracy were examined with respect to longitude and latitude. Overall, TanDEM-X exhibited the highest stability and accuracy, AW3D30 and SRTM also performed well, while ASTER exhibited the worst accuracy. The DEMs showed relationships with the slope aspect and land cover type, assuming that slope had no influence on vertical accuracy. In general, vertical accuracy in high latitudes was slightly better than that in low latitudes, and no evident variations were observed with respect to longitude. This study is the first to conduct DEM analysis across many regions in China from open sources. Since most of the users rely on public domain DEM datasets, this work contributes to their analysis in academic and engineering fields.

Validation of GPS-Based Monitoring and Remote Sensing of Ice-Shelf and Ice-Sheet Movement Changes.

The north and south poles of the earth (hereinafter referred to as the polar regions) are important components of the earth system. Changes in the material balance and movement of the polar ice shelf reflect the influence of the polar regions on global climate change and are also a response to global climate change. Through a comprehensive investigation of ice-shelf kinematics, with sufficient accuracy, it is possible to obtain ice-shelf elevation, movement-state data, ice-shelf material balance state, and the ice-shelf movement dynamics mechanism. Due to the extremely harsh environment in polar regions, remote sensing is currently widely used. Manual and equipment monitoring methods show insufficient accuracy or discontinuous time series. There is an urgent need to obtain continuous real-time ice-shelf kinematics-related parameters on the ground to verify the reliability of the parameters obtained by satellite remote sensing. These parameters should be combined with remote sensing monitoring to provide data support. In this paper, a monitoring system for the movement of polar ice and shelf ice cover is developed, and it is proposed that various data can be acquired by integrating high-precision GPS (global positioning system) and other sensors. Solutions to the problem of low-temperature power supply in the polar regions, data acquisition and storage strategies, and remote communication methods are proposed. Testing and remote sensing validation verified that the developed acquisition system can fulfill the requirements for monitoring the movement of the polar unmanned ice shelves and ice sheets.

A Comparative Study on the Solar Radiation Pressure Modeling in GPS Precise Orbit Determination

For Global Positioning System (GPS) precise orbit determination (POD), the solar radiation pressure (SRP) is the dominant nongravitational perturbation force. Among the current SRP models, the ECOM and box-wing models are widely used in the International GNSS Service (IGS) community. However, the performance of different models varies over different GPS satellites. In this study, we investigate the performances of different SRP models, including the box-wing and adjustable box-wing as a priori models, and ECOM1 and ECOM2 as parameterization models, in the GPS POD solution from 2017 to 2019. Moreover, we pay special attention to the handling of the shadow factor in the SRP modeling for eclipsing satellites, which is critical to achieve high-precision POD solutions but has not yet been fully investigated. We demonstrate that, as an a priori SRP model, the adjustable box-wing has better performance than the box-wing model by up to 5 mm in the orbit day boundary discontinuity (DBD) statistics, with the largest improvement observed on the BLOCK IIR satellites using the ECOM1 as a parameterization SRP model. The box-wing model shows an insignificant orbit improvement serving as the a priori SRP model. For the eclipsing satellites, the three-dimensional (3D) root mean square (RMS) values of orbit DBD are improved when the shadow factor is applied only in the D direction (pointing toward to Sun) than that in the three directions (D, Y, and B) in the satellite frame. Different SRP models have comparable performance in terms of the Earth rotation parameter (ERP) agreement with the IERS EOP 14C04 product, whereas the magnitude of the length of day (LoD) annual signal is reduced when the shadow factor is applied in the D direction than in the three directions. This study clarifies how the shadow factor should be applied in the GPS POD solution and demonstrates that the a priori adjustable box-wing model combined with ECOM1 is more suitable for high-precision GPS POD solutions, which is useful for the further GNSS data analysis.

Simple Methodology for the Development and Analysis of Local Driving Cycles Applied in the Study of Cars and Motorcycles in Recife, Brazil

Standard driving cycles are usually used to compare vehicles from distinct regions, and local driving cycles reproduce more realistic conditions in specific regions. In this article, we employed a simple methodology for developing local driving cycles and subsequently performed a kinematic and energy analysis. As an application, we employed the methodology for cars and motorcycles in Recife, Brazil. The speed profile was collected using a smartphone (1 Hz) validated against a high precision global positioning system (10 Hz), presenting a mean absolute error of 3 km/h. The driving cycles were thus developed using the micro-trip method. The kinematic analysis indicated that motorcycles had a higher average speed and acceleration (32.5 km/h, 0.84 m/s2) than cars (22.6 km/h, 0.55 m/s2). As a result of the energy analysis, it was found that inertia is responsible for most of the fuel consumption for both cars (59%) and motorcycles (41%), but for motorcycles the aerodynamic drag is also relevant (36%). With regards to fuel consumption, it was found that the standard driving cycle used in Brazil (FTP-75; 2.47 MJ/km for cars and 0.84 MJ/km for motorcycles) adequately represents the driving profile for cars (2.46 MJ/km), and to a lesser extent motorcycles (0.91 MJ/km) in off-peak conditions. Finally, we evaluated the influence of the vehicle category on energy consumption, obtaining a maximum difference of 38% between a 2.0 L sports utility vehicle and a 1.0 L hatchback.

Editorial for the Special Issue: “High-Precision GNSS: Methods, Open Problems and Geoscience Applications”

In the past two decades, the high-precision Global Positioning System (GPS) has significantly increased the range of geoscience applications and their precision [...]

Inter-Vehicle Distance Estimation Method Based on Monocular Vision Using 3D Detection

Most autonomous vehicles build their perception systems on expensive sensors, such as LIDAR, RADAR, and high-precision Global Positioning System (GPS). However, cameras can provide richer sensing at a considerably lower cost, this makes them a more appealing alternative. A driving assistance system (DAS) based on monocular vision has gradually become a research hotspot, and inter-vehicle distance estimation based on monocular vision is an important technology in DAS. There are still constrains in the existing methods for estimating the inter-vehicle distance based on monocular vision, such as low accuracy when distance is larger, unstable accuracy for different types vehicles, and significantly poor performance on distance estimation for severely occluded vehicles. To improve the accuracy and robustness of ranging results, this study proposes a monocular vision end-to-end inter-vehicle distance estimation method based on 3D detection. The actual area of the rare view of the vehicle and the corresponding projection area in the image are obtained by 3D detection method. An area-distance geometric model is then established on the basis of the camera projection principle to recover distance. Our method shows its potential in complex traffic scenarios by testing the test set data provided on the real-world computer vision benchmark, KITTI. The experimental results have superior performance than the existing published methods. Moreover, the accuracy of occluded vehicle ranging results can reach approximately $98\%$, while the accuracy deviation between vehicles with different visual angles is less than $2\%$.

Stabilization and Validation of 3D Object Position Using Multimodal Sensor Fusion and Semantic Segmentation.

The stabilization and validation process of the measured position of objects is an important step for high-level perception functions and for the correct processing of sensory data. The goal of this process is to detect and handle inconsistencies between different sensor measurements, which result from the perception system. The aggregation of the detections from different sensors consists in the combination of the sensorial data in one common reference frame for each identified object, leading to the creation of a super-sensor. The result of the data aggregation may end up with errors such as false detections, misplaced object cuboids or an incorrect number of objects in the scene. The stabilization and validation process is focused on mitigating these problems. The current paper proposes four contributions for solving the stabilization and validation task, for autonomous vehicles, using the following sensors: trifocal camera, fisheye camera, long-range RADAR (Radio detection and ranging), and 4-layer and 16-layer LIDARs (Light Detection and Ranging). We propose two original data association methods used in the sensor fusion and tracking processes. The first data association algorithm is created for tracking LIDAR objects and combines multiple appearance and motion features in order to exploit the available information for road objects. The second novel data association algorithm is designed for trifocal camera objects and has the objective of finding measurement correspondences to sensor fused objects such that the super-sensor data are enriched by adding the semantic class information. The implemented trifocal object association solution uses a novel polar association scheme combined with a decision tree to find the best hypothesis–measurement correlations. Another contribution we propose for stabilizing object position and unpredictable behavior of road objects, provided by multiple types of complementary sensors, is the use of a fusion approach based on the Unscented Kalman Filter and a single-layer perceptron. The last novel contribution is related to the validation of the 3D object position, which is solved using a fuzzy logic technique combined with a semantic segmentation image. The proposed algorithms have a real-time performance, achieving a cumulative running time of 90 ms, and have been evaluated using ground truth data extracted from a high-precision GPS (global positioning system) with 2 cm accuracy, obtaining an average error of 0.8 m.

Method for determining weight matrix for resolving three-dimensional surface deformation using Multi-LOS D-InSAR technology

Three-dimensional surface deformation is resolved using deformations obtained from multiple line of sight differential interferometry synthetic aperture radar (multi-LOS D-InSAR). However, the random model is susceptible to both accidental errors (such as errors due to noises) and system errors (such as orbital errors and topographic errors). To solve this problem, we present a weight-determining method based on high-precision global positioning system (GPS) observations. Specifically, the precision of multi-LOS D-InSAR deformation observations is evaluated based on high-precision GPS deformation observations from the same period. Then, by considering the influence of system errors and accidental errors on the deformation of a pixel observed by multi-LOS D-InSAR, a combined fitting model associated with the positions and elevations of a pixel is built. Finally, the precision of deformations from multi-LOS D-InSAR is evaluated pixel-by-pixel by using the built model. As a result, the weights of observations in the model for resolving three-dimensional surface deformation using multi-LOS D-InSAR can be determined. We verify the feasibility and precision of the weight-determining method through a simulation experiment and a real data experiment, respectively. The verification results show that the proposed weight-determining method based on high-precision GPS observations provides higher reliability for the resolved three-dimensional surface deformation.

Vertical land motion and relative sea level changes along the coastline of Brest (France) from combined space-borne geodetic methods

In spite of the recent advances and the current perspectives of satellite radar altimetry to reach the coastline and monitor coastal sea level changes, this space-borne technology remains geocentric by essence. In contrast, the quantity that matters for coastal management and society is relative sea level. That is, the sea level relative to the land, as measured by conventional tide gauges. However, two important issues are associated with the use of tide gauges. First, supplemental information is required to separate vertical land motion from ocean climate signals in tide gauge records, and hence to understand the causes of future coastal sea level changes and their relative importance. This can be provided by space-borne geodetic techniques, for instance installing a permanent Global Positioning System (GPS) antenna at the tide gauge. Second, vertical land motion can show local spatial patterns, which limits the spatial validity of the point-wise information at the GPS station. Using Interferometry Synthetic Aperture Radar (InSAR) and high-precision GPS data, the above-mentioned limitations were addressed in the case study of Brest (France). Our findings show that, over the past decades, Brest and its surroundings are overall stable, in agreement with the geological setting, except for the embankment areas of the commercial and military harbours. The GPS-calibrated InSAR results were then further combined with geocentric satellite radar altimetry data to obtain relative sea level trends along the Brest coastline with an unprecedented high-spatial resolution of 200 m. Our approach is applicable beyond the case study of Brest, especially in coastal areas where tide gauge data are not available, provided satellite data are.

Study of travel time variability using two-wheeler probe data – an Indian experience

The objective of this study is to examine travel time reliability under the heterogeneous traffic conditions prevailing in developing countries such as India. The study is carried out using a motorised two-wheeler, which is a dominant vehicular type in conditions such as are found in India on urban arterial roads. Eight runs are conducted during morning peak hours by driving a motorised two-wheeler mounted with a performance box (equipped with high-precision global positioning system) with the traffic stream on the test route between Athwa and Piplod, in Surat city, Gujarat, situated in the western part of India. One of the major outcomes of the study is to propose the most suitable relationships between buffer time index (BTI) and volume-demand-to-capacity (V/C) ratio, as well as between planning time index (PTI) and V/C ratio. From the results, it is found that a polynomial function-based model can predict BTI as well as PTI for the given V/C ratio more accurately. The study also highlights the development of a methodology to define the level of service of a roadway facility based on travel time reliability measures. Furthermore, this research work discusses potential reliability measures for capturing travel time variations more appropriately.

Crustal deformation and strain analysis in Nepal from GPS time-series measurement and modeling by ARMA method

High-precision Global Positioning System (GPS) measurements from 2002 to 2017 in Nepal has been analyzed and modeled with Autoregressive Moving Average (ARMA) method. The measured velocities of the GPS sites in ITRF-2014 indicate ~ 6–12 mm/year N–S convergence inside the Nepal between India and Tibet. This convergence occurs in the southern and western border of Nepal, but it is negligible to the eastern border of Nepal. ARMA-modeled result of India-fixed velocities is able to successfully model (within ~ 0.5 mm/year) the current measured velocities in Nepal. Synthetic or modeled velocities using ARMA method and measured velocity have difference ~ 2 mm/year at some sites. This indicates the possibility of very small level of a ductile deformation. In the present best-fit ARMA model, the modeled velocities ~ 8–10 mm/year convergence taken up from northern to southern boundaries of Nepal indicates slip along active Main Himalayan Thrust (MHT) which is the cause of change in tectonic strain and may be able to trigger earthquakes inside the country. Dislocation modeling of active MHT is also carried out in the study using GPS vertical displacement. The geometric model of the MHT is characterized by a rectangular plane with dip angle of 9.5° and the reverse kinematics with a slip of 19 mm/year. The thrust is located at a depth of 20 km. In addition, the regional deformation of the Nepal has been checked by baseline measurement and coordinate stability of GPS sites for the different zones. The baseline divergence and convergence of nearest GPS sites have been tested using triangular sites. The summary of regional deformation implies N–S convergence only and rules out any type of E–W convergence. Finally, the investigation of observed and modeled strain confirms that there is no significant strain accumulation due to localized regional deformation or earthquakes specific to the active dislocations and faults. This suggests that the convergence from northern to southern boundaries of Nepal is associated with the slip along the MHT only.

Late Quaternary tectonic activity and shortening rate of the Beiluntai fault zone in the South Tianshan, Xinjiang, NW China

The Beiluntai fault is a Holocene active fault and is the boundary fault between the South Tianshan and Tarim Basin. Since the Late Quaternary, the continuous activities of the Beiluntai fault have caused dislocation, deformation, and fold uplift of multi-phase alluvial geomorphologic surfaces. Using a high-precision differential global positioning system, we measured the fault scarp morphology of multi-phase geomorphologic surfaces in the Akeaiken and Zhuanchang sections of the Beiluntai fault. Via large-scale active fault mapping, we found that the Akeaiken section is dominated by thrusting, while the Zhuanchang section is dominated by fold uplift. We obtained the ages of the different phases of the geomorphologic surfaces (Fan4, Fan3b, Fan3c, and Fan2) using the optically stimulated luminescence dating method. We found that since the formation of the Fan4 geomorphologic surface, the crustal shortening rate (approximately 2.4 mm/a) of the Akeaiken section has remained basically constant. However, the crustal shortening rate of the Zhuanchang section in the south–north direction (1.43–1.81 mm/a) during the Late Quaternary was significantly less than that in the Akeaiken section, suggesting that the crustal shortening rate in the south–north direction of the Beiluntai fault zone decreases from west to east. A comprehensive comparison of the South Tianshan piedmont thrust-and-fold belt system also showed that the crustal shortening rate decreases from west to east.

Metrology Assessment of the Accuracy of Precipitable Water Vapor Estimates from GPS Data Acquisition in Tropical Areas: The Tahiti Case

High precision Global Positioning System (GPS) receivers, with the advantages of all-weather work and low cost, are now widely used to routinely monitor precipitable water (PW) vapor. They are so successful that the progressive phasing out of the costly and sparse in situ radio soundings (RS) is now a certainty. Nevertheless, the sub-daily to annual monitoring of high levels of the PW by GPS receivers in the tropics and the equatorial area still needs to be asserted in terms of metrology accuracy. This is the subject of this paper, which focuses on a tropical site located in mid-ocean (Tahiti). The metrology assessment was divided into two steps. Firstly, a GPS internal assessment, with an in-house processing based on the Bernese GNSS Software Version 5.2 and a comparison with the Center for Orbit Determination in Europe (CODE) products. Secondly, an external assessment, with a comparison with RS PW estimates. In contrast with previous works that only used PW estimates from the Integrated Global Radiosonde Archive (IGRA) website, we estimated the RS PW from the balloon raw data. This is especially important in tropical areas, where IGRA estimates only consider balloon measurements taken below approximately 5500 m. We show that, in our case, this threshold is one of the main sources of bias between GPS and RS estimates, and that the formula used to translate the GPS zenith wet delays (ZWD) to PW estimates also needs to be revisited for high level water vapor contents in the atmosphere.

Multimodal sensor-based semantic 3D mapping for a large-scale environment

Semantic 3D mapping is one of the most important fields in robotics, and has been used in many applications, such as robot navigation, surveillance, and virtual reality. In general, semantic 3D mapping is mainly composed of 3D reconstruction and semantic segmentation. As these technologies evolve, there has been great progress in semantic 3D mapping in recent years. Furthermore, the number of robotic applications requiring semantic information in 3D mapping to perform high-level tasks has increased, and many studies on semantic 3D mapping have been published. Existing methods use a camera for both 3D reconstruction and semantic segmentation. However, this is not suitable for large-scale environments and has the disadvantage of high computational complexity. To address this problem, we propose a multimodal sensor-based semantic 3D mapping system using a 3D Lidar combined with a camera. In this study, the odometry is obtained by high-precision global positioning system (GPS) and inertial measurement unit (IMU), and it is estimated by iterative closest point (ICP) when a GPS signal is weak. Then, we use the latest 2D convolutional neural network (CNN) for semantic segmentation. To build a semantic 3D map, we integrate the 3D map with semantic information by using coordinate transformation and Bayes’ update scheme. In order to improve the semantic 3D map, we propose a 3D refinement process to correct wrongly segmented voxels and remove traces of moving vehicles in the 3D map. Through experiments on challenging sequences, we demonstrate that our method outperforms state-of-the-art methods in terms of accuracy and intersection over union (IoU). Thus, our method can be used for various applications that require semantic information in 3D map.

Vertical Accuracy Effect Verification for Satellite Imagery With Different GCPs

This letter expands the block adjustment method by, respectively, adopting high-precision global positioning system (GPS) points, geoscience laser altimeter system (GLAS) data, and Shuttle Radar Topography Mission (SRTM)-digital elevation model (DEM) as vertical control data. Block adjustment experiments were conducted with these control data, with 388 ZY-3 satellite stereo image pairs across over 18600 km2 of land in Hubei province of China utilized as experimental images and 180 GPS points as checkpoints. The experimental results obtained show that, with the adoption of 23 GPS points as control points, the horizontal root-mean-square error (RMSE) and vertical RMSE of the ZY-3 image improved from 10.97 to 5.72 m and from 7.12 to 1.65 m, respectively. Furthermore, with the adoption of 326 GLAS data points as vertical control points, the vertical RMSE of the ZY-3 images of the flat terrain areas and mountain terrain areas improved to 1.69 and 3.62 m, respectively. Through block adjustment constrained by SRTM-DEM, the vertical RMSE of the ZY-3 images was 1.44 m for flat terrain areas and 3.05 m for mountain terrain areas, respectively. The vertical accuracy of the satellite images was significantly enhanced, especially on the flat terrain area, when GLAS and STRM-DEM were used for vertical control block adjustment, which is similar to the vertical accuracy of block adjustments adopting GPS points as control.

Investigation into the Effect of Atmospheric Particulate Matter (PM2.5 and PM10) Concentrations on GPS Signals.

The Global Positioning System (GPS) has been widely used in navigation, surveying, geophysical and geodynamic studies, machine guidance, etc. High-precision GPS applications such as geodetic surveying need millimeter and centimeter level accuracy. Since GPS signals are affected by atmospheric effects, methods of correcting or eliminating ionospheric and tropospheric bias are needed in GPS data processing. Relative positioning can be used to mitigate the atmospheric effect, but its efficiency depends on the baseline lengths. Air pollution is a serious problem globally, especially in developing countries that causes health problems to humans and damage to the ecosystem. Respirable suspended particles are coarse particles with a diameter of 10 micrometers or less, also known as PM10. Moreover, fine particles with a diameter of 2.5 micrometers or less are known as PM2.5. GPS signals travel through the atmosphere before arriving at receivers on the Earth’s surface, and the research question posed in this paper is: are GPS signals affected by the increased concentration of the PM2.5/PM10 particles? There is no standard model of the effect of PM2.5/PM10 particles on GPS signals in GPS data processing, although an approximate generic model of non-gaseous atmospheric constituents (<1 mm) can be found in the literature. This paper investigates the effect of the concentration of PM2.5/PM10 particles on GPS signals and validates the aforementioned approximate model with a carrier-to-noise ratio (CNR)-based empirical method. Both the approximate model and the empirical results show that the atmospheric PM2.5/PM10 particles and their concentrations have a negligible effect on GPS signals and the effect is comparable with the noise level of GPS measurements.

Study of the effects on GPS coordinate time series caused by higher-order ionospheric corrections calculated using the DIPOLE model

As one of the main error sources in high-precision Global Positioning System (GPS) data processing, higher-order ionospheric (HOI) delays cause significant effects on coordinate time series that cannot be ignored in analyses of long time series. Typically two geomagnetic models, DIPOLE model and International Geomagnetic Reference Field (IGRF) model, are used for calculating HOI corrections. This paper investigates the effects of HOI correction caused by the DIPOLE model on coordinate time series. GPS data from 104 globally distributed International GNSS Service (IGS) stations spanning from January, 1999 to December, 2003 were reprocessed following up-to-date processing strategies utilizing GAMIT and GLOBK software. Two coordinate time series solutions before and after applying HOI corrections using the DIPOLE model were derived for studying the effects in terms of seasonal variations and noise amplitudes. The results show that after applying the HOI corrections calculated with DIPOLE, the noise amplitudes of the coordinate time series increased, especially in the north and east directions, and the increased amplitudes of the flicker noise were larger than those of the white noise. Furthermore, spurious periodic signals that were probably introduced by the HOI corrections from the DIPOLE model were also found. Moreover, an apparent increase was confirmed for the power spectra of most of the stations, especially in the north direction, and the amplitudes of both the annual and semi-annual signals also increased in the north and east directions. It can be inferred that the quality of the external data sources such as the geomagnetic model might be the key factors that lead to the above results. The results also suggest that we should be very careful when the DIPOLE model is used for HOI corrections.

GPS RTK定位技术在驾考系统中的应用

全球定位系统(GPS)因其高精度三维定位测速及定时的功能在精密工程测量中得到迅速广泛的应用。利用高精度GPS载波相位实时动态差分(RTK)定位技术的特点，在机动车驾驶技能考试中，可精确地计算考车的轮廓位置点，解决了考车行驶过程中的距离测量问题。根据RTK技术在考车上架设的双GPS天线和具体考试项目里车线之间距离的检测方法，并结合考场电子地图各项目的特征点和各项目的评判规则，华众设计的全自动智能驾考系统，可实现精确评判。 Global positioning system (GPS) has been widely used in precision engineering measurement be-cause of its high precision three dimensional positioning velocity test and timing function. Using the characteristics of high precision GPS real-time kinematic (RTK) positioning technology in the motor vehicle driving skills test can accurately calculate the contour points of the test vehicle, this solves the problem of distance measurement in the course of test vehicle. Based on RTK Technology in the test vehicle mounted dual GPS antenna and the detection method of the distance between the test vehicle and the line in the examination of specific project, and combined with the examination of electronic map the feature points and the purposes of evaluation rules, Huazhong design the automatic intelligence of the driving test system , which can realize accurate judgment.