scholarly journals Long-range Single Baseline RTK GNSS Positioning for Land Cadastral Survey Mapping

2019 ◽  
Vol 94 ◽  
pp. 01022 ◽  
Author(s):  
Brian Bramanto ◽  
Irwan Gumilar ◽  
Muhammad Taufik ◽  
I Made D. A. Hermawan
Keyword(s):  
Long Range ◽  
Atmospheric Correction ◽  
Critical Factor ◽  
Satellite System ◽  
High Accuracy ◽  
Short Baseline ◽  
Gnss Positioning ◽  
Positioning Method ◽  
Position Solution ◽  
Single Baseline

In Indonesia, Global Navigation Satellite System (GNSS) has become one of the important tool in survey mapping, especially for cadastral purposes like land registration by using Real Time Kinematic (RTK) GNSS positioning method. The conventional RTK GNSS positioning method ensure high accuracy GNSS position solution (within several centimeters) for baseline less than 20 kilometers. The problems of resolving high accuracy position for a greater distance (more than 50 kilometers) becomes greater challenge. In longer baseline, atmospheric delays is a critical factor that influenced the positioning accuracy. In order to reduce the error, a modified LAMBDA ambiguity resolution, atmospheric correction and modified kalman filter were used in this research. Thus, this research aims to investigate the accuracy of estimated position and area in respect with short baseline RTK and differential GNSS position solution by using NAVCOM SF-3040. The results indicate that the long-range single baseline RTK accuracy vary from several centimeters to decimeters due to unresolved biases.

scholarly journals Variability and Performance of Short to Long-Range Single Baseline RTK GNSS Positioning in Indonesia

2019 ◽  
Vol 94 ◽  
pp. 01012 ◽  
Author(s):  
Irwan Gumilar ◽  
Brian Bramanto ◽  
Fuad F. Rahman ◽  
I Made D. A. Hermawan
Keyword(s):  
Long Range ◽  
High Frequency ◽  
Carrier Phase ◽  
Satellite System ◽  
High Accuracy ◽  
Gnss Positioning ◽  
And Performance ◽  
Gnss Network ◽  
Single Baseline ◽  
Global Navigation Satellite

As the modernized Global Navigation Satellite System (GNSS) method, Real Time Kinematic (RTK) ensures high accuracy of position (within several centimeters). This method uses Ultra High Frequency (UHF) radio to transmit the correction data, however, due to gain and power issues, Networked Transport of RTCM via Internet Protocol (RTCM) is used to transmit the correction data for a longer baseline. This Research aims to investigate the performance of short to long-range single baseline RTK GNSS (Up to 80 KM) by applying modified LAMBDA method to resolve the ambiguity in carrier phase. The RTK solution then compared with the differential GNSS network solution. The results indicate that the differences are within RTK accuracy up to 80 km are several centimeter for horizontal solution and three times higher for vertical solution.

scholarly journals Real-time Precise Point Positioning with a Xiaomi MI 8 Android Smartphone

Sensors ◽  
2019 ◽  
Vol 19 (12) ◽  
pp. 2835 ◽  
Author(s):  
Bo Chen ◽  
Chengfa Gao ◽  
Yongsheng Liu ◽  
Puyu Sun
Keyword(s):  
Real Time ◽  
Mobile Phones ◽  
Precise Point Positioning ◽  
Satellite System ◽  
Dual Frequency ◽  
Gnss Positioning ◽  
Positioning Errors ◽  
Positioning Method ◽  
Point Positioning ◽  
Time Required

The Global Navigation Satellite System (GNSS) positioning technology using smartphones can be applied to many aspects of mass life, and the world’s first dual-frequency GNSS smartphone Xiaomi MI 8 represents a new trend in the development of GNSS positioning technology with mobile phones. The main purpose of this work is to explore the best real-time positioning performance that can be achieved on a smartphone without reference stations. By analyzing the GNSS raw measurements, it is found that all the three mobile phones tested have the phenomenon that the differences between pseudorange observations and carrier phase observations are not fixed, thus a PPP (precise point positioning) method is modified accordingly. Using a Xiaomi MI 8 smartphone, the modified real-time PPP positioning strategy which estimates two clock biases of smartphone was applied. The results show that using multi-GNSS systems data can effectively improve positioning performance; the average horizontal and vertical RMS positioning error are 0.81 and 1.65 m respectively (using GPS, BDS, and Galileo data); and the time required for each time period positioning errors in N and E directions to be under 1 m is less than 30s.

scholarly journals On the performance of GNSS levelling over steep slopes

2012 ◽  
Vol 18 (4) ◽  
pp. 645-660 ◽  
Author(s):  
R. Cuneyt Erenoglu ◽  
Mehmet Ali Yucel ◽  
Atinc Pirti ◽  
D. Ugur Sanli
Keyword(s):  
Satellite System ◽  
High Accuracy ◽  
Short Baseline ◽  
Solution Strategies ◽  
Baseline Solution ◽  
3D Positioning ◽  
3D Information ◽  
Global Navigation Satellite ◽  
Steep Slopes ◽  
New Strategies

In geodetic applications variety, one of the main current focuses is recently to determine the heights of ground stations with high accuracy. Specially the possibility of acquiring 3D information of the point positioning with high accuracy is opening up new strategies of investigating the heighting. Global Navigation Satellite System (GNSS) for 3D positioning is undergoing rapid developments and GNSS heighting can be an alternative to terrestrial techniques of height measurements. This paper presents a research study on the use of GNSS heighting in the case of steep slopes and multipath issue. Short baseline solution strategies were performed by using Bernese Software v. 5.0. The analysis results are also compared to the results of techniques of the terrestrial levelling. The results show that GNSS can be used as an practical surveying method to the terrestrial levelling with comparable accuracies. Furthermore, one can save up to 1 hour using GNSS instead of geometric levelling over a steep slope of a 100 m. On the other hand, as usual multipath is the primary error source decreasing the efficiency of GNSS, and it has been studied experimentally in this paper.

A Computation Effective Range-Based 3D Mapping Aided GNSS with NLOS Correction Method

2020 ◽  
Vol 73 (6) ◽  
pp. 1202-1222 ◽  
Author(s):  
Hoi-Fung Ng ◽  
Guohao Zhang ◽  
Li-Ta Hsu
Keyword(s):  
Ray Tracing ◽  
Urban Areas ◽  
Low Cost ◽  
Three Dimensional ◽  
Correction Method ◽  
Satellite System ◽  
Urban Environments ◽  
3D Mapping ◽  
Gnss Positioning ◽  
Positioning Method

Global navigation satellite system (GNSS) positioning in dense urban areas remains a challenge due to the signal reflection by buildings, namely multipath and non-line-of-sight (NLOS) reception. These effects degrade the performance of low-cost GNSS receivers such as in those smartphones. An effective three-dimensional (3D) mapping aided GNSS positioning method is proposed to correct the NLOS error. Instead of applying ray-tracing simulation, the signal reflection points are detected based on a skyplot with the surrounding building boundaries. The measurements of the direct and reflected signals can thus be simulated and further used to determine the user's position based on the measurement likelihood between real measurements. Verified with real experiments, the proposed algorithm is able to reduce the computational load greatly while maintaining a positioning accuracy within 10 metres of error in dense urban environments, compared with the conventional method of ray-tracing based NLOS corrected positioning.

Vehicle Localization Based on Global Navigation Satellite System Aided by Three-Dimensional Map

2017 ◽  
Vol 2621 (1) ◽  
pp. 55-61 ◽  
Author(s):  
Yanlei Gu ◽  
Li-Ta Hsu ◽  
Shunsuke Kamijo
Keyword(s):  
Inertial Sensors ◽  
Three Dimensional ◽  
Satellite System ◽  
Navigation Satellite ◽  
Positioning Accuracy ◽  
Vehicle Localization ◽  
Localization System ◽  
Gnss Positioning ◽  
Positioning Method ◽  
Global Navigation Satellite

Accurate vehicle localization technologies are significant for current onboard navigation systems and future autonomous vehicles. More specifically, positioning accuracy is expected at the submeter level. This paper presents an accurate vehicle self-localization system and evaluates the proposed system in different classes of urban environments. The developed system adopts an innovative global navigation satellite system (GNSS) positioning method as the key technique. The GNSS positioning method can improve the positioning error by reducing the effects of multipath interference and non-line-of-sight errors with the aid of a three-dimensional map. To improve positioning accuracy further, the vehicle localization system integrates the GNSS positioning technique with inertial sensors and vision sensors by considering the characteristics of each sensor. The inertial sensors represent vehicle movement with heading direction and vehicle speed. The vision sensor is used to recognize the position change relative to lane markings on the road surface. Those techniques and sensors collaborate to provide an accurate position in the global coordinate system. To verify the effectiveness and stability of the proposed system, a series of tests was conducted in one of the most challenging urban cities, Tokyo. The experiment results demonstrate that the proposed system can achieve submeter accuracy for the positioning error mean and has a 90% correct lane rate in the localization.

scholarly journals Real-Time Multipath Mitigation in Multi-GNSS Short Baseline Positioning via CNN-LSTM Method

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Yuan Tao ◽  
Chao Liu ◽  
Tianyang Chen ◽  
Xingwang Zhao ◽  
Chunyang Liu ◽  
...  
Keyword(s):  
Real Time ◽  
Short Term Memory ◽  
Satellite System ◽  
Multipath Mitigation ◽  
Short Baseline ◽  
Gnss Positioning ◽  
Positioning Errors ◽  
Large Matrix ◽  
Long Short Term Memory ◽  
Global Navigation Satellite

Multipath is the main systematic error of the Global Navigation Satellite System (GNSS) short baseline positioning. Multipath cannot be eliminated by the double-differenced technique and is difficult to parameterize, which severely restrict the high-precision GNSS positioning application. Based on the spatiotemporal repeatability of multipath, the sidereal filtering in coordinate-domain (SF-CD), the sidereal filtering in observation-domain (SF-OD), and the multipath hemispherical map (MHM) can be used to mitigate the multipath in real-time. However, the multipath model with large matrix for multi-GNSS multipath mitigation is difficult to achieve lightweight calculation and the SF-CD cannot be applied to mitigate the multi-GNSS multipath. In this paper, we propose a new multipath mitigation strategy in the coordinate-domain that shakes off the formation mechanism of multipath, a CNN (convolutional neural network)-LSTM (long short-term memory) method is used to mine the deep multipath features in GNSS coordinate series. Furthermore, multipath will be mitigated in real-time by constantly predicting the value of the next epoch. The experimental results show that the CNN-LSTM effectively mitigates the multi-GNSS multipath. The method can reduce the average RMS (root-mean square) of multi-GNSS positioning errors in the east, north, and vertical directions by 62.3%, 70.8%, and 66.0%. Moreover, comparing with the SF-CD, SF-OD, and MHM, CNN-LSTM can more effectively mitigate the effects of the GPS multipath, and the ability of multipath mitigation is almost not affected over time.

scholarly journals Instantaneous, Dual-Frequency, Multi-GNSS Precise RTK Positioning Using Google Pixel 4 and Samsung Galaxy S20 Smartphones for Zero and Short Baselines

Sensors ◽  
2021 ◽  
Vol 21 (24) ◽  
pp. 8318
Author(s):  
ChienZheng Yong ◽  
Robert Odolinski ◽  
Safoora Zaminpardaz ◽  
Michael Moore ◽  
Eldar Rubinov ◽  
...  
Keyword(s):  
Satellite System ◽  
Navigation Satellite ◽  
Dual Frequency ◽  
Short Baseline ◽  
Integer Least Squares ◽  
Short Baselines ◽  
Zero Baseline ◽  
Single Baseline ◽  
Global Navigation Satellite ◽  
Lying Down

The recent development of the smartphone Global Navigation Satellite System (GNSS) chipsets, such as Broadcom BCM47755 and Qualcomm Snapdragon 855 embedded, makes instantaneous and cm level real-time kinematic (RTK) positioning possible with Android-based smartphones. In this contribution we investigate the instantaneous single-baseline RTK performance of Samsung Galaxy S20 and Google Pixel 4 (GP4) smartphones with such chipsets, while making use of dual-frequency L1 + L5 Global Positioning System (GPS), E1 + E5a Galileo, L1 + L5 Quasi-Zenith Satellite System (QZSS) and B1 BeiDou Navigation Satellite System (BDS) code and phase observations in Dunedin, New Zealand. The effects of locating the smartphones in an upright and lying down position were evaluated, and we show that the choice of smartphone configuration can affect the positioning performance even in a zero-baseline setup. In particular, we found non-zero mean and linear trends in the double-differenced carrier-phase residuals for one of the smartphone models when lying down, which become absent when in an upright position. This implies that the two assessed smartphones have different antenna gain pattern and antenna sensitivity to interferences. Finally, we demonstrate, for the first time, a near hundred percent (98.7% to 99.9%) instantaneous RTK integer least-squares success rate for one of the smartphone models and cm level positioning precision while using short-baseline experiments with internal and external antennas, respectively.

scholarly journals Single-Baseline RTK Positioning Using Dual-Frequency GNSS Receivers Inside Smartphones

Sensors ◽  
2019 ◽  
Vol 19 (19) ◽  
pp. 4302 ◽  
Author(s):  
Paolo Dabove ◽  
Vincenzo Di Pietra
Keyword(s):  
Satellite System ◽  
Smart Devices ◽  
Dual Frequency ◽  
Cooperative Positioning ◽  
Gnss Positioning ◽  
Gnss Receivers ◽  
Master Station ◽  
Single Baseline ◽  
Gnss Measurements ◽  
Global Navigation Satellite

Global Navigation Satellite System (GNSS) positioning is currently a common practice thanks to the development of mobile devices such as smartphones and tablets. The possibility to obtain raw GNSS measurements, such as pseudoranges and carrier-phase, from these instruments has opened new windows towards precise positioning using smart devices. This work aims to demonstrate the positioning performances in the case of a typical single-base Real-Time Kinematic (RTK) positioning while considering two different kinds of multi-frequency and multi-constellation master stations: a typical geodetic receiver and a smartphone device. The results have shown impressive performances in terms of precision in both cases: with a geodetic receiver as the master station, the reachable precisions are several mm for all 3D components while if a smartphone is used as the master station, the best results can be obtained considering the GPS+Galileo constellations, with a precision of about 2 cm both for 2D and Up components in the case of L1+L5 frequencies, or 3 cm for 2D components and 2 cm for the Up, in the case of an L1 frequency. Moreover, it has been demonstrated that it is not feasible to reach the phase ambiguities fixing: despite this, the precisions are still good and also the obtained 3D accuracies of positioning solutions are less than 1 m. So, it is possible to affirm that these results are very promising in the direction of cooperative positioning using smartphone devices.

GPS-BDS-Galileo double-differenced stochastic model refinement based on least-squares variance component estimation

2021 ◽  
pp. 1-16
Author(s):  
Hong Hu ◽  
Xuefeng Xie ◽  
Jingxiang Gao ◽  
Shuanggen Jin ◽  
Peng Jiang
Keyword(s):  
Stochastic Model ◽  
Least Squares ◽  
Stochastic Models ◽  
Variance Component ◽  
Satellite System ◽  
Variance Component Estimation ◽  
Short Baseline ◽  
Component Estimation ◽  
Zero Baseline ◽  
Global Navigation Satellite

Abstract Stochastic models are essential for precise navigation and positioning of the global navigation satellite system (GNSS). A stochastic model can influence the resolution of ambiguity, which is a key step in GNSS positioning. Most of the existing multi-GNSS stochastic models are based on the GPS empirical model, while differences in the precision of observations among different systems are not considered. In this paper, three refined stochastic models, namely the variance components between systems (RSM1), the variances of different types of observations (RSM2) and the variances of observations for each satellite (RSM3) are proposed based on the least-squares variance component estimation (LS-VCE). Zero-baseline and short-baseline GNSS experimental data were used to verify the proposed three refined stochastic models. The results show that, compared with the traditional elevation-dependent model (EDM), though the proposed models do not significantly improve the ambiguity resolution success rate, the positioning precision of the three proposed models has been improved. RSM3, which is more realistic for the data itself, performs the best, and the precision at elevation mask angles 20°, 30°, 40°, 50° can be improved by 4⋅6%, 7⋅6%, 13⋅2%, 73⋅0% for L1-B1-E1 and 1⋅1%, 4⋅8%, 16⋅3%, 64⋅5% for L2-B2-E5a, respectively.

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