scholarly journals An Effective Approach to Improving Low-Cost GPS Positioning Accuracy in Real-Time Navigation

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Md. Rashedul Islam ◽  
Jong-Myon Kim
Keyword(s):  
Real Time ◽  
State Of The Art ◽  
Low Cost ◽  
Movement Direction ◽  
Gps Receiver ◽  
Positioning Accuracy ◽  
Global Positioning ◽  
Art Methods ◽  
Coordinate Data ◽  
Vehicle Movement

Positioning accuracy is a challenging issue for location-based applications using a low-cost global positioning system (GPS). This paper presents an effective approach to improving the positioning accuracy of a low-cost GPS receiver for real-time navigation. The proposed method precisely estimates position by combining vehicle movement direction, velocity averaging, and distance between waypoints using coordinate data (latitude, longitude, time, and velocity) of the GPS receiver. The previously estimated precious reference point, coordinate translation, and invalid data check also improve accuracy. In order to evaluate the performance of the proposed method, we conducted an experiment using a GARMIN GPS 19xHVS receiver attached to a car and used Google Maps to plot the processed data. The proposed method achieved improvement of 4–10 meters in several experiments. In addition, we compared the proposed approach with two other state-of-the-art methods: recursive averaging and ARMA interpolation. The experimental results show that the proposed approach outperforms other state-of-the-art methods in terms of positioning accuracy.

scholarly journals Indoor Positioning Method Based on Infrared Vision and UWB Fusion

2021 ◽  
Vol 2078 (1) ◽  
pp. 012070
Author(s):  
Qianrong Zhang ◽  
Yi Li
Keyword(s):  
Real Time ◽  
Indoor Localization ◽  
Low Cost ◽  
Ultra Wideband ◽  
Coverage Area ◽  
Positioning Accuracy ◽  
Mobile Vehicle ◽  
Positioning Method ◽  
Positioning Algorithm ◽  
Infrared Vision

Abstract Ultra-wideband (UWB) has broad application prospects in the field of indoor localization. In order to make up for the shortcomings of ultra-wideband that is easily affected by the environment, a positioning method based on the fusion of infrared vision and ultra-wideband is proposed. Infrared vision assists locating by identifying artificial landmarks attached to the ceiling. UWB uses an adaptive weight positioning algorithm to improve the positioning accuracy of the edge of the UWB positioning coverage area. Extended Kalman filter (EKF) is used to fuse the real-time location information of the two. Finally, the intelligent mobile vehicle-mounted platform is used to collect infrared images and UWB ranging information in the indoor environment to verify the fusion method. Experimental results show that the fusion positioning method is better than any positioning method, has the advantages of low cost, real-time performance, and robustness, and can achieve centimeter-level positioning accuracy.

Directly Georeferenced Ground Feature Points with UAV Borne Photogrammetric Platform without Ground Control

2013 ◽  
Vol 284-287 ◽  
pp. 1523-1527
Author(s):  
Meng Lun Tsai ◽  
Kai Wei Chiang ◽  
Cheng Fang Lo ◽  
Jiann Yeou Rau
Keyword(s):  
Real Time ◽  
Spatial Information ◽  
Disaster Relief ◽  
Low Cost ◽  
Control Point ◽  
Integrated System ◽  
Single Frequency ◽  
Ground Control ◽  
Differential Gps ◽  
Positioning Accuracy

In order to facilitate applications such as environment detection or disaster monitoring, developing a quickly and low cost system to collect near real time spatial information is very important. Such a rapid spatial information collection capability has become an emerging trend in the technology of remote sensing and mapping application. In this study, a fixed-wing UAV based spatial information acquisition platform is developed and evaluated. The proposed UAV based platform has a direct georeferencing module including an low cost INS/GPS integrated system, low cost digital camera as well as other general UAV modules including immediately video monitoring communication system. This direct georeferencing module is able to provide differential GPS processing with single frequency carrier phase measurements to obtain sufficient positioning accuracy. All those necessary calibration procedures including interior orientation parameters, the lever arm and boresight angle are implemented. In addition, a flight test is performed to verify the positioning accuracy in direct georeferencing mode without using any ground control point that is required for most of current UAV based photogrammetric platforms. In other word, this is one of the pilot studies concerning direct georeferenced based UAV photogrammetric platform. The preliminary results in term of positioning accuracy in direct georeferenced mode without using any GCP illustrate horizontal positioning accuracies in x and y axes are both less than 20 meters, respectively. On the contrary, the positioning accuracy of z axis is less than 50 meters with 600 meters flight height above ground. Such accuracy is good for near real time disaster relief. Therefore, it is a relatively safe and cheap platform to collect critical spatial information for urgent response such as disaster relief and assessment applications where ground control points are not available.

Determination of global positioning system (GPS) receiver clock errors: impact on positioning accuracy

2009 ◽  
Vol 20 (7) ◽  
pp. 075105 ◽  
Author(s):  
Ta-Kang Yeh ◽  
Cheinway Hwang ◽  
Guochang Xu ◽  
Chuan-Sheng Wang ◽  
Chien-Chih Lee
Keyword(s):  
Global Positioning System ◽  
Positioning System ◽  
Gps Receiver ◽  
Positioning Accuracy ◽  
Global Positioning ◽  
Receiver Clock

scholarly journals Estimating Vehicle Movement Direction from Smartphone Accelerometers Using Deep Neural Networks

Sensors ◽  
2018 ◽  
Vol 18 (8) ◽  
pp. 2624 ◽  
Author(s):  
Sara Hernández Sánchez ◽  
Rubén Fernández Pozo ◽  
Luis Hernández Gómez
Keyword(s):  
Global Positioning System ◽  
Driving Forces ◽  
Movement Direction ◽  
Motion Sensors ◽  
Forward Movement ◽  
Significant Acceleration ◽  
Global Positioning ◽  
Vehicle Movement

Characterization of driving maneuvers or driving styles through motion sensors has become a field of great interest. Before now, this characterization used to be carried out with signals coming from extra equipment installed inside the vehicle, such as On-Board Diagnostic (OBD) devices or sensors in pedals. Nowadays, with the evolution and scope of smartphones, these have become the devices for recording mobile signals in many driving characterization applications. Normally multiple available sensors are used, such as accelerometers, gyroscopes, magnetometers or the Global Positioning System (GPS). However, using sensors such as GPS increase significantly battery consumption and, additionally, many current phones do not include gyroscopes. Therefore, we propose the characterization of driving style through only the use of smartphone accelerometers. We propose a deep neural network (DNN) architecture that combines convolutional and recurrent networks to estimate the vehicle movement direction (VMD), which is the forward movement directional vector captured in a phone’s coordinates. Once VMD is obtained, multiple applications such as characterizing driving styles or detecting dangerous events can be developed. In the development of the proposed DNN architecture, two different methods are compared. The first one is based on the detection and classification of significant acceleration driving forces, while the second one relies on longitudinal and transversal signals derived from the raw accelerometers. The final success rate of VMD estimation for the best method is of 90.07%.

scholarly journals A Detailed Study on GPS and GIS Enabled Agricultural Equipment Field Position Monitoring system for Smart Farming

2021 ◽  
Vol 22 (2) ◽  
Author(s):  
Jianbo Nie ◽  
Bin Yang
Keyword(s):  
Real Time ◽  
Monitoring System ◽  
Gis Technology ◽  
Positioning Accuracy ◽  
Static Test ◽  
Electronic Map ◽  
Gps Technology ◽  
Proposed Model ◽  
Smart Farming ◽  
Global Positioning

To develop refined agriculture and improve Agricultural productivity, a new monitoring system has been proposed in this paper. Based on the actual situation of early agriculture and the actual national conditions of China, Geographic Information System (GIS) technology and Global Positioning System (GPS) technology have been combined. Based on the combination of GIS technology and GPS technology, the results show that the position of field vehicles can be displayed in the electronic MAP in real time within 5% error. On this basis, Agricultural production and cultivation can be realized, and the monitoring system can realize the real-time display of vehicle location in the field on electronic MAP to guide production and cultivation. The static test shows that the positioning accuracy of the four GPS receivers is the worst, and the positioning accuracy of MAP330 receiver and GPS25 receiver is better. However, the positioning accuracy of AGl32 receiver is the highest with the 0.37m error when compared with the error of 1.2m of other machines. Using GPS to measure the area, the error of farmland area and farmland side length is less than 5%, and the precision AGl32 receiver for precision Agricultural measurement is also improved with the proposed model.

scholarly journals Positioning Accuracy Comparison of GNSS Receivers Used for Mapping and Guidance of Agricultural Machines

Agronomy ◽  
2020 ◽  
Vol 10 (7) ◽  
pp. 924 ◽  
Author(s):  
Pietro Catania ◽  
Antonio Comparetti ◽  
Pierluigi Febo ◽  
Giuseppe Morello ◽  
Santo Orlando ◽  
...  
Keyword(s):  
Real Time ◽  
Precision Agriculture ◽  
Low Cost ◽  
Global Navigation Satellite Systems ◽  
Reference Trajectory ◽  
Positioning Error ◽  
Differential Correction ◽  
Positioning Accuracy ◽  
Real Time Kinematic ◽  
Gnss Receivers

Global Navigation Satellite Systems (GNSS) allow the determination of the 3D position of a point on the Earth’s surface by measuring the distance from the receiver antenna to the orbital position of at least four satellites. Selecting and buying a GNSS receiver, depending on farm needs, is the first step for implementing precision agriculture. The aim of this work is to compare the positioning accuracy of four GNSS receivers, different for technical features and working modes: L1/L2 frequency survey-grade Real-Time Kinematic (RTK)-capable Stonex S7-G (S7); L1 frequency RTK-capable Stonex S5 (S5); L1 frequency Thales MobileMapper Pro (TMMP); low-cost L1 frequency Quanum GPS Logger V2 (QLV2). In order to evaluate the positioning accuracy of these receivers, i.e., the distance of the determined points from a reference trajectory, different tests, distinguished by the use or not of Real-Time Kinematic (RTK) differential correction data and/or an external antenna, were carried out. The results show that all satellite receivers tested carried out with the external antenna had an improvement in positioning accuracy. The Thales MobileMapper Pro satellite receiver showed the worst positioning accuracy. The low-cost Quanum GPS Logger V2 receiver surprisingly showed an average positioning error of only 0.550 m. The positioning accuracy of the above-mentioned receiver was slightly worse than that obtained using Stonex S7-G without the external antenna and differential correction (maximum positioning error 0.749 m). However, this accuracy was even better than that recorded using Stonex S5 without differential correction, both with and without the external antenna (average positioning error of 0.962 m and 1.368 m).

GPSIM: A Personal Computer-Based GPS Simulator System

1999 ◽  
Vol 52 (1) ◽  
pp. 126-135 ◽  
Author(s):  
D. Ibrahim
Keyword(s):  
Real Time ◽  
Personal Computer ◽  
Electronic System ◽  
Route Guidance ◽  
Gps Receiver ◽  
Positioning Systems ◽  
Global Positioning ◽  
Computer Based ◽  
Marine Navigation ◽  
Positional Data

Global Positioning Systems (GPS) are now in use in many applications, ranging from GIS to route guidance, automatic vehicle location (AVL), air, land, and marine navigation, and many other transportation and geographical based applications. In many applications, the GPS receiver is connected to some form of intelligent electronic system which receives the positional data from the GPS unit and then performs the required operation. When developing and testing GPS-based systems, one of the problems is that it is usually necessary to create GPS-compatible geographical data to simulate a GPS operation in real time. This paper provides the details of a Personal Computer (PC)-based GPS simulator system called GPSIM. The system receives user way-points and routes from Windows-based screen forms and then simulates a GPS operation in real time by generating most of the commonly used GPS sentences. The user-specified waypoints are divided into a number of small segments, each segment specifying a small distance in the direction of the original waypoint. The GPS sentence corresponding to the geographical coordinates of each segment is then sent out of the PC serial port. The system described is an invaluable testing tool for GPS-based system developers and also for people training to learn to use GPS-based products.

scholarly journals Low cost and state of the art methods to measure nitrous oxide emissions

2013 ◽  
Vol 8 (2) ◽  
pp. 025022 ◽  
Author(s):  
Arjan Hensen ◽  
Ute Skiba ◽  
Daniela Famulari
Keyword(s):  
Nitrous Oxide ◽  
State Of The Art ◽  
Low Cost ◽  
Nitrous Oxide Emissions ◽  
Art Methods

scholarly journals An SVM Based Weight Scheme for Improving Kinematic GNSS Positioning Accuracy with Low-Cost GNSS Receiver in Urban Environments

Sensors ◽  
2020 ◽  
Vol 20 (24) ◽  
pp. 7265
Author(s):  
Zhitao Lyu ◽  
Yang Gao
Keyword(s):  
Real Time ◽  
Low Cost ◽  
Urban Environments ◽  
Least Square ◽  
Single Frequency ◽  
Line Of Sight ◽  
Support Vector ◽  
Positioning Accuracy ◽  
Gnss Receiver ◽  
Gnss Positioning

High-precision positioning with low-cost global navigation satellite systems (GNSS) in urban environments remains a significant challenge due to the significant multipath effects, non-line-of-sight (NLOS) errors, as well as poor satellite visibility and geometry. A GNSS system is typically implemented with a least-square (LS) or a Kalman-filter (KF) estimator, and a proper weight scheme is vital for achieving reliable navigation solutions. The traditional weight schemes are based on the signal-in-space ranging errors (SISRE), elevation and C/N0 values, which would be less effective in urban environments since the observation quality cannot be fully manifested by those values. In this paper, we propose a new multi-feature support vector machine (SVM) signal classifier-based weight scheme for GNSS measurements to improve the kinematic GNSS positioning accuracy in urban environments. The proposed new weight scheme is based on the identification of important features in GNSS data in urban environments and intelligent classification of line-of-sight (LOS) and NLOS signals. To validate the performance of the newly proposed weight scheme, we have implemented it into a real-time single-frequency precise point positioning (SFPPP) system. The dynamic vehicle-based tests with a low-cost single-frequency u-blox M8T GNSS receiver demonstrate that the positioning accuracy using the new weight scheme outperforms the traditional C/N0 based weight model by 65.4% and 85.0% in the horizontal and up direction, and most position error spikes at overcrossing and short tunnels can be eliminated by the new weight scheme compared to the traditional method. It also surpasses the built-in satellite-based augmentation systems (SBAS) solutions of the u-blox M8T and is even better than the built-in real-time-kinematic (RTK) solutions of multi-frequency receivers like the u-blox F9P and Trimble BD982.

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