A Novel Method for Mitigating the GPS Multipath Effect Based on a Multi-Point Hemispherical Grid Model

Abstract

The multipath effect is a crucial error source caused by the environment around the station and cannot be eliminated or mitigated by differential algorithms. Theoretically, the maximum value for the carrier phase is a quarter the wavelength, i.e., about 4.8 cm for the GPS L1 signal. Considering the increasing demands of high-precision applications, the multipath error has become a major factor affecting the accuracy and reliability of GPS millimeter-level data processing. This paper proposes a multi-point hemispherical grid model (MHGM) to mitigate the multipath effect. In this method, the hemisphere centered on each station is divided into a grid, and the multipath error at the station is estimated based on the parameterization of the grid points. The double-differenced (DD) observed-minus-calculated (OMC) values on some previous days are treated as the observation values to model the present multipath error. Contrary to the present methods which rely much on the platform of data collection and processing, MHGM can be potentially applied to GPS data processing with the existing hardware and software. Experiments in high-multipath and low-multipath environments are designed by mounting a baffle or not. The experimental results show that MHGM is effective in mitigating the multipath effect. When using data from the previous day, an average improvement of about 63.3% in the RMS of DD OMC can be made compared with that without correction, and this is basically consistent with the sidereal filtering (SF) method which is 63.0%. Furthermore, the effectiveness of the above two methods is better than that of the empirical site model (ESM). The kinematic positioning results are also basically consistent with the statistical results of the RMS values of DD OMC. Historical data from more than one day can more explicitly and effectively model the MHGM. Furthermore, compared with the SF method, the MHGM can be used not only to mitigate the multipath error, but also to orientate the sources of the multipath error around the station, and give guidance in the physical elimination of these sources.

Multipath Error Fusion Modeling Methods for Multi-GNSS

“…The residuals of the double-differenced carrier phase observations in the ambiguity-fixed period were used as the input information. Then, a multi-point hemispherical grid model at each station was established and finally the model of each station could be obtained after the grid points of each model were parameterized and solved by the estimator [26]. First, the hemisphere was established with the antenna phase center of each station as the origin and was divided into grids according to the elevation angle and azimuth angle.…”

“…Supposing the parameters of the four grid points involved in the grid point of the satellite are Q s p1 , Q s p2 , Q s p3 and Q s p4 , there is a case involving three grid point parameters when the elevation angle is greater than E 1 . Then, v s p could be express by the parameters of the grid points, as follows [26]:…”

GNSS Carrier-Phase Multipath Modeling and Correction: A Review and Prospect of Data Processing Methods

“…Aiming to obtain the multipath error characteristics of satellites with different elevation values, Zheng et al [84] proposed an improved MHM, which reduces the influence of multipath errors on precise point positioning under static conditions. Wang et al [85] proposed a multi-point hemispherical grid model (MHGM) to directly model the double-difference residual, which can be applied to common receiver hardware equipment. Zhang et al [86] presented the MHM_V model based on variational mode decomposition (VMD) and MHM.…”