Real-time GPS receiver bias estimation

In this paper, we present the new method for real-time GPS receiver bias estimation by using Lagrange interpolation, which is also compared to the two current methods, polynomial and minimization of standard deviation. The estimated method is proposed to reduce the complexity and time of the GPS receiver bias estimation. Lagrange interpolation is the method to find the derivatives and integrals of discrete functions in GPS receiver bias data. The test site is located on Chumphon station, Thailand. The test period of data method is during the year 2004-2019. In the quiet and disturbed days, the polynomial method gives the highest value of the GPS receiver bias at 5.75 ns and -4.25 ns, respectively, but the Lagrange interpolation shows the lowest value of GPS receiver bias at -6.85 ns and 5.25 ns, in order. The results and comparisons among the polynomial GPS receiver bias method, the minimization of standard deviation of GPS receiver bias method, and Lagrange interpolation method show that the calculated time for Lagrange interpolation is shorter compared to other methods and it can be given more time points for finding GPS receiver biases than others. (C) 2021 COSPAR. Published by Elsevier B.V. All rights reserved.

Automated summary

This paper presents a new method for real-time GPS receiver bias estimation using Lagrange interpolation, compared with polynomial and minimization of standard deviation methods. The results show that Lagrange interpolation can reduce the complexity and time for GPS receiver bias estimation, providing more time points for finding biases compared to other methods.