scholarly journals The determination of the geoid-spheroid separation for GPS levelling and applications

1989 ◽  
Vol 20 (2) ◽  
pp. 185
Author(s):  
A.W.H. Kearsley ◽  
R.M. Eckels

The heights which are obtained from global positioning system (GPS) satellite observations are measured with respect to an earth-centred ellipsoid and are not, as a result, generally useful for surveying and engineering. In order to become useful they must be transformed into orthometric heights, that is, heights which are measured with respect to the actual level reference surface termed the geoid. The parameter which enables this transformation is N, the geoid height or geoid-ellipsoid separation.This paper reviews the capabilities of the GPS system for height measurements, describes the various methods used to evaluate N from gravimetry, and explores the suitability of these methods in the various applications in which height measurements from the GPS may be used.

2021 ◽  
pp. 1-18
Author(s):  
Mariusz Specht

Abstract Research into statistical distributions of φ, λ and two-dimensional (2D) position errors of the global positioning system (GPS) enables the evaluation of its accuracy. Based on this, the navigation applications in which the positioning system can be used are determined. However, studies of GPS accuracy indicate that the empirical φ and λ errors deviate from the typical normal distribution, significantly affecting the statistical distribution of 2D position errors. Therefore, determining the actual statistical distributions of position errors (1D and 2D) is decisive for the precision of calculating the actual accuracy of the GPS system. In this paper, based on two measurement sessions (900,000 and 237,000 fixes), the distributions of GPS position error statistics in both 1D and 2D space are analysed. Statistical distribution measures are determined using statistical tests, the hypothesis on the normal distribution of φ and λ errors is verified, and the consistency of GPS position errors with commonly used statistical distributions is assessed together with finding the best fit. Research has shown that φ and λ errors for the GPS system are normally distributed. It is proven that φ and λ errors are more concentrated around the central value than in a typical normal distribution (positive kurtosis) with a low value of asymmetry. Moreover, φ errors are clearly more concentrated than λ errors. This results in larger standard deviation values for φ errors than λ errors. The differences in both values were 25–39%. Regarding the 2D position error, it should be noted that the value of twice the distance root mean square (2DRMS) is about 10–14% greater than the value of R95. In addition, studies show that statistical distributions such as beta, gamma, lognormal and Weibull are the best fit for 2D position errors in the GPS system.


1992 ◽  
Vol 19 (14) ◽  
pp. 1487-1490 ◽  
Author(s):  
Yvonne Vigue ◽  
Stephen M. Lichten ◽  
Geoffrey Blewitt ◽  
Michael B. Heflin ◽  
Rajendra P. Malla

2009 ◽  
Vol 20 (7) ◽  
pp. 075105 ◽  
Author(s):  
Ta-Kang Yeh ◽  
Cheinway Hwang ◽  
Guochang Xu ◽  
Chuan-Sheng Wang ◽  
Chien-Chih Lee

Author(s):  
Kirstin L. Rock ◽  
Sven A. Beiker ◽  
Shad Laws ◽  
J. Christian Gerdes

The increasingly widespread use of the Global Positioning System (GPS) in determining the location of vehicles raises the possibility of using the information provided by GPS for vehicle control purposes. The use of a multi-antenna GPS system provides the ability to measure not only position and velocity, but vehicle heading and sideslip as well. This paper presents a validation of a GPS based system with an automotive grade two-axis optical sensor. The results show excellent agreement between the two sensor systems, confirming the accuracy of the GPS based system even in highly dynamic situations. Although any GPS based system is subject to dropouts from driving under trees and bridges, cornering stiffness estimates obtained when GPS is available enable construction of a vehicle state observer for use in the absence of GPS.


2004 ◽  
Vol 126 (2) ◽  
pp. 243-254 ◽  
Author(s):  
Jihan Ryu ◽  
J. Christian Gerdes

This paper demonstrates a method of estimating several key vehicle states—sideslip angle, longitudinal velocity, roll and grade—by combining automotive grade inertial sensors with a Global Positioning System (GPS) receiver. Kinematic Kalman filters that are independent of uncertain vehicle parameters integrate the inertial sensors with GPS to provide high update estimates of the vehicle states and the sensor biases. Using a two-antenna GPS system, the effects of pitch and roll on the measurements can be quantified and are demonstrated to be quite significant in sideslip angle estimation. Employing the same GPS system as an input to the estimator, this paper develops a method that compensates for roll and pitch effects to improve the accuracy of the vehicle state and sensor bias estimates. In addition, calibration procedures for the sensitivity and cross-coupling of inertial sensors are provided to further reduce measurement error. The resulting state estimates compare well to the results from calibrated models and Kalman filter predictions and are clean enough to use in vehicle dynamics control systems without additional filtering.


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