A New Weighting Approach with Application to Ionospheric Delay Constraint for GPS/GALILEO Real-Time Precise Point Positioning

Abstract

The real-time precise point positioning (RT PPP) technique has attracted increasing attention due to its high-accuracy and real-time performance. However, a considerable initialization time, normally a few hours, is required in order to achieve the proper convergence of the real-valued ambiguities and other estimate parameters. The RT PPP convergence time may be reduced by combining quad-constellation global navigation satellite system (GNSS), or by using RT ionospheric products to constrain the ionosphere delay. But to improve the performance of convergence and achieve the best positioning solutions in the whole data processing, proper and precise variances of the observations and ionospheric constraints are important, since they involve the processing of measurements of different types and with different accuracy. To address this issue, a weighting approach is proposed by a combination of the weight factors searching algorithm and a moving-window average filter. In this approach, the variances of ionospheric constraints are adjusted dynamically according to the principle that the sum of the quadratic forms of weighted residuals is the minimum, and the filter is applied to combine all epoch-by-epoch weight factors within a time window. To evaluate the proposed approach, datasets from 31 Multi-GNSS Experiment (MGEX) stations during the period of DOY (day of year) 023-054 in 2018 are analyzed with different positioning modes and different data processing methods. Experimental results show that the new weighting approach can significantly improve the convergence performance, and that the maximum improvement rate reaches 35.9% in comparison to the traditional method of priori variance in the static dual-frequency positioning mode. In terms of the RMS (Root Mean Square) statistics of positioning errors calculated by the new method after filter convergence, the same accuracy level as that of RT PPP without constraints can be achieved.

Regiomontan: A Regional High Precision Ionosphere Delay Model and Its Application in Precise Point Positioning

“…Therefore, the parameters σ 2 iono,0 , t end , and σ 2 iono,end define the strength of the ionospheric constraint and how fast it is released. Another strategy can be found in [42] where the variances of the ionospheric constraint are adjusted according to the sum of the quadratic forms of weighted residuals.…”

Special Issue on Machine Learning Techniques Applied to Geoscience Information System and Remote Sensing

“…Liu et al [7] in their paper titled "A New Weighting Approach with Application to Ionospheric Delay Constraint for GPS/GALILEO Real-Time Precise Point Positioning" adopted a weighting approach in the precise point positioning with integer and zero-difference ambiguity resolution demonstrator (PPP-WIZARD). The weighting method integrates a weight factor searching method with a moving-window average filter.…”

“…(3) Application of machine learning techniques to Global Positioning System (GPS); (4) Spatial analysis and geocomputation based on machine learning techniques; (5) Spatial prediction using machine learning techniques; (6) Data processing of geoinformation using machine learning techniques; (7) Comparison analysis among several machine learning techniques applied to GIS and RS; (8) Application of machine learning techniques on geosciences, environments, natural hazards, and natural resources as case studies.…”

Bidirectional Sliding Window for Boundary Recognition of Pavement Construction Area Using GPS-RTK

“…Many documents propose using GPS trajectories to extract and update road data, which generally involves using clustering [6][7][8], kernel density estimation [9,10], trajectory merging [11,12] and geometric modelling [13,14]. However, these methods extract road boundaries by analyzing and processing a large number of GPS trajectories, which are generally of meter-level accuracy [15]. According to actual construction requirements, the length of Pavement Construction Area (PCA) boundaries is generally only about 50 m and the width is only 10 to 20 m, but the positioning needs to be accurate to 1 decimeter.…”