Reducing multipath effect of low-cost GNSS receivers for monitoring by considering temporal correlations

Abstract

Abstract The investigations on low-cost single frequency GNSS receivers at the Institute of Engineering Geodesy (IIGS) show that u-blox GNSS receivers combined with low-cost antennas and self-constructed L1-optimized choke rings can reach an accuracy which almost meets the requirements of geodetic applications (see Zhang and Schwieger [25]). However, the quality (accuracy and reliability) of low-cost GNSS receiver data should still be improved, particularly in environments with obstructions. The multipath effects are a major error source for the short baselines. The ground plate or the choke ring ground plane can reduce the multipath signals from the horizontal reflector (e. g. ground). However, the shieldings cannot reduce the multipath signals from the vertical reflectors (e. g. walls). Because multipath effects are spatially and temporally correlated, an algorithm is developed for reducing the multipath effect by considering the spatial correlations of the adjoined stations (see Zhang and Schwieger [24]). In this paper, an algorithm based on the temporal correlations will be introduced. The developed algorithm is based on the periodic behavior of the estimated coordinates and not on carrier phase raw data, which is easy to use. Because, for the users, coordinates are more accessible than the raw data. The multipath effect can cause periodic oscillations but the periods change over time. Besides this, the multipath effect’s influence on the coordinates is a mixture of different multipath signals from different satellites and different reflectors. These two properties will be used to reduce the multipath effect. The algorithm runs in two steps and iteratively. Test measurements were carried out in a multipath intensive environment; the accuracies of the measurements are improved by about 50 % and the results can be delivered in near-real-time (in ca. 30 minutes), therefore the algorithm is suitable for structural health monitoring applications.