scholarly journals Assessment of Positioning Accuracy based on Medium- and Long-range GPS L1 Relative Positioning using Regional Ionospheric Grid Model

2012 ◽  
Vol 30 (5) ◽  
pp. 459-466
Author(s):  
Eun-Seong Son ◽  
Jihye Won ◽  
Kwan-Dong Park
Keyword(s):  
Long Range ◽  
Relative Positioning ◽  
Positioning Accuracy ◽  
Grid Model ◽  
Ionospheric Grid

Multi-resolution Visual Positioning and Navigation Technique for Unmanned Aerial System Landing Assistance

2017 ◽  
Vol 70 (6) ◽  
pp. 1276-1292
Author(s):  
Chong Yu ◽  
Jiyuan Cai ◽  
Qingyu Chen
Keyword(s):  
Real World ◽  
State Of The Art ◽  
Unmanned Aerial System ◽  
Detection Accuracy ◽  
Relative Positioning ◽  
Positioning Accuracy ◽  
Visual Positioning ◽  
Positioning Technique ◽  
Technique Comparison ◽  
Resolution Simulation

To achieve more accurate navigation performance in the landing process, a multi-resolution visual positioning technique is proposed for landing assistance of an Unmanned Aerial System (UAS). This technique uses a captured image of an artificial landmark (e.g. barcode) to provide relative positioning information in the X, Y and Z axes, and yaw, roll and pitch orientations. A multi-resolution coding algorithm is designed to ensure the UAS will not lose the detection of the landing target due to limited visual angles or camera resolution. Simulation and real world experiments prove the performance of the proposed technique in positioning accuracy, detection accuracy, and navigation effect. Two types of UAS are used to verify the generalisation of the proposed technique. Comparison experiments to state-of-the-art techniques are also included with the results analysis.

scholarly journals THE QUALITY OF OPENSTREETMAP IN MALAYSIA: A PRELIMINARY ASSESSMENT

2018 ◽  
Vol XLII-4/W9 ◽  
pp. 291-298 ◽  
Author(s):  
S. N. R. M. Husen ◽  
N. H. Idris ◽  
M. H. I. Ishak
Keyword(s):  
Relative Positioning ◽  
Reference Dataset ◽  
Preliminary Assessment ◽  
Positioning Accuracy ◽  
Open Platform ◽  
Collaborative Mapping ◽  
Mexico Earthquake ◽  
Thematic Accuracy ◽  
Hurricane Irma

<p><strong>Abstract.</strong> Over recent years, the phenomena, Web 2.0 has led to the growth of volunteered geographic information (VGI). The emergence of VGI has played an important role in providing timely data when the costs and its availability is a major concern particularly during emergency and humanitarian efforts. The worldwide crowdsourcing efforts through OpenStreetMap (OSM), the most successful open platform for collaborative mapping have managed to assist authorities such as during the 2017 Mexico earthquake and Hurricane Irma and Maria that impacted several countries in America continent. However, there are lots of arguments on the quality of VGI, particularly in regard to OpenStreetMap (OSM). Therefore, this study was carried out to assess the quality of OSM against authoritative sources using a dataset of Putrajaya, Malaysia. This study assessed the quality of OSM, including completeness, positional and thematic accuracy. From the preliminary assessment, the results showed that the OSM data was good in terms of relative positioning accuracy, particularly in road feature, but still poor in terms of completeness and thematic correctness against the reference dataset. This study is significant with an expected contribution to the assessment of quality of VGI in developing countries that commonly facing slow-paced progress in mapping the OSM. The findings could be used as a basis for various parties that plan to use OSM in Malaysia, particularly Putrajaya as a supplementary data to authoritative sources, including data supplied by the professional surveyors.</p>

scholarly journals Performance of Selected Ionospheric Models in Multi-Global Navigation Satellite System Single-Frequency Positioning over China

2019 ◽  
Vol 11 (17) ◽  
pp. 2070 ◽  
Author(s):  
Wang ◽  
Chen ◽  
Zhang ◽  
Meng ◽  
Wang
Keyword(s):  
Global Navigation Satellite System ◽  
Satellite System ◽  
Ionospheric Delay ◽  
Single Frequency ◽  
Navigation Satellite ◽  
Ionospheric Model ◽  
Positioning Accuracy ◽  
Grid Model ◽  
Ionospheric Models ◽  
Global Navigation Satellite

Ionospheric delay as the major error source needs to be properly handled in multi-GNSS (Global Navigation Satellite System) single-frequency positioning and the different ionospheric models exhibit apparent performance difference. In this study, two single-frequency positioning solutions with different ionospheric corrections are utilized to comprehensively analyze the ionospheric delay effects on multi-frequency and multi-constellation positioning performance, including standard point positioning (SPP) and ionosphere-constrained precise point positioning (PPP). The four ionospheric models studied are the GPS broadcast ionospheric model (GPS-Klo), the BDS (BeiDou Navigation Satellite System) broadcast ionospheric model (BDS-Klo), the BDS ionospheric grid model (BDS-Grid) and the Global Ionosphere Maps (GIM) model. Datasets are collected from 10 stations over one month in 2019. The solar remained calm and the ionosphere was stable during the test period. The experimental results show that for single-frequency SPP, the GIM model achieves the best accuracy, and the positioning accuracy of the BDS-Klo and BDS-Grid model is much better than the solution with GPS-Klo model in the N and U components. For the single-frequency PPP performance, the average convergence time of the ionosphere-constrained PPP is much reduced compared with the traditional PPP approach, where the improvements are of 11.2%, 11.9%, 21.3% and 39.6% in the GPS-Klo-, BDS-Klo-, BDS-Grid- and GIM-constrained GPS + GLONASS + BDS single-frequency PPP solutions, respectively. Furthermore, the positioning accuracy of the BDS-Grid- and GIM-constrained PPP is generally the same as the ionosphere-free combined single-frequency PPP. Through the combination of GPS, GLONASS and BDS, the positioning accuracy and convergence performance for all single-system single-frequency SPP/PPP solutions can be effectively improved.

scholarly journals RESEARCH OF POSITIONING ACCURACY BASED ON PHOTOGRAMMETRY

2020 ◽  
pp. 73-79
Author(s):  
Yu.M. Salamatina ◽  
S.I. Kuzikov
Keyword(s):  
Space Geodesy ◽  
Digital Model ◽  
Relative Positioning ◽  
Positioning Accuracy ◽  
3D Digital Model

The methods of ground and space geodesy allow to determine with millimeter accuracy the position of separate geodetic points on the Earth's surface. The hardware and software of the photogrammetry method make it possible to build a 3D digital model of the observed geodetic area. The purpose of this work is to compare and evaluate the accuracy of relative positioning using geodesy and photogrammetry methods within the Bishkek geodynamic area.

scholarly journals Mobile robot positioning algorithm based on Kalman filtering method in network environment

2020 ◽  
Vol 327 ◽  
pp. 03005
Author(s):  
Shuang Zhang
Keyword(s):  
Mobile Robot ◽  
Navigation System ◽  
Inertial Navigation System ◽  
Inertial Navigation ◽  
Measurement Unit ◽  
Relative Positioning ◽  
Positioning Accuracy ◽  
Reference Information ◽  
Absolute Positioning ◽  
Positioning Method

Positioning is the basic link in a multi-mobile robot control system, and is also a problem that must be solved before completing a specified task. The positioning method can be generally divided into relative positioning and absolute positioning. Absolute positioning method refers to that the robot calculates its current position by acquiring the reference information of some known positions in the outside world, calculating the relationship between itself and the reference information. Absolute positioning generally adopts methods based on beacons, environment map matching, and visual positioning. The relative positioning method mainly uses the inertial navigation system INS. The inertial navigation system directly fixes the inertial measurement unit composed of the gyroscope and the accelerometer to the target device, and uses the inertial devices such as the gyroscope and the accelerometer to measure the triaxial angular velocity and The three-axis acceleration information is measured and integrated, and the mobile robot coordinates are updated in real time. Combined with the initial inertial information of the target device, navigation information such as the attitude, speed, and position of the target device is obtained through integral operation [1-2]. The inertial navigation system does not depend on external information when it is working, and is not easily damaged by interference. As an autonomous navigation system, it has the advantages of high data update rate and high short-term positioning accuracy [3]. However, under the long-term operation of inertial navigation, due to the cumulative error of integration, the positioning accuracy is seriously degraded, so it is necessary to seek an external positioning method to correct its position information [4]

scholarly journals An Improved Long-Period Precise Time-Relative Positioning Method Based on RTS Data

Sensors ◽  
2020 ◽  
Vol 21 (1) ◽  
pp. 53
Author(s):  
Yangwei Lu ◽  
Shengyue Ji ◽  
Rui Tu ◽  
Duojie Weng ◽  
Xiaochun Lu ◽  
...  
Keyword(s):  
High Precision ◽  
Reference Station ◽  
Positioning Error ◽  
Relative Positioning ◽  
Precision Positioning ◽  
Positioning Accuracy ◽  
Long Period ◽  
Short Period ◽  
Positioning Method ◽  
Positioning Algorithm

The high precision positioning can be easily achieved by using real-time kinematic (RTK) and precise point positioning (PPP) or their augmented techniques, such as network RTK (NRTK) and PPP-RTK, even if they also have their own shortfalls. A reference station and datalink are required for RTK or NRTK. Though the PPP technique can provide high accuracy position data, it needs an initialisation time of 10–30 min. The time-relative positioning method estimates the difference between positions at two epochs by means of a single receiver, which can overcome these issues within short period to some degree. The positioning error significantly increases for long-period precise positioning as consequence of the variation of various errors in GNSS (Global Navigation Satellite System) measurements over time. Furthermore, the accuracy of traditional time-relative positioning is very sensitive to the initial positioning error. In order to overcome these issues, an improved time-relative positioning algorithm is proposed in this paper. The improved time-relative positioning method employs PPP model to estimate the parameters of current epoch including position vector, float ionosphere-free (IF) ambiguities, so that these estimated float IF ambiguities are used as a constraint of the base epoch. Thus, the position of the base epoch can be estimated by means of a robust Kalman filter, so that the position of the current epoch with reference to the base epoch can be obtained by differencing the position vectors between the base epoch and the current one. The numerical results obtained during static and dynamic tests show that the proposed positioning algorithm can achieve a positioning accuracy of a few centimetres in one hour. As expected, the positioning accuracy is highly improved by combining GPS, BeiDou and Galileo as a consequence of a higher amount of used satellites and a more uniform geometrical distribution of the satellites themselves. Furthermore, the positioning accuracy achieved by using the positioning algorithm here described is not affected by the initial positioning error, because there is no approximation similar to that of the traditional time-relative positioning. The improved time-relative positioning method can be used to provide long-period high precision positioning by using a single dual-frequency (L1/L2) satellite receiver.

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