Name
Abstract | ||
|---|---|---|
The key to performing successful multi-GNSS (Global Navigation Satellite System) precise point positioning is calibrating ISB (inter-system bias) in different systems. We can use the method of modeling to eliminate the ISB error. However, the ISB series are commonly discontinuous, as they contain jumps and outliers caused by day boundaries, gaps, or outliers in the precise clock products, which will break the ability of modeling. Thus, before modeling the ISB, we must remove outliers and repair jumps to improve the ISB continuity and achieve a continuous and smooth ISB series. Preprocessing on precise clock products is focused on in this study for the detection of ISB jumps and their repair. From the results, a positive correlation is revealed within the residuals of satellite clock offset and ISB differences between adjacent days. This finding implies ISB continuity can be improved through the preprocessing of precise clock products. It is also found that the exact reason for the occurrence of ISB jumps is the presence of extrema (i.e., maximum or minimum points) in the frequency domain. From the clock data in the frequency domain, larger extrema are identified directly. Meanwhile, for the detection of smaller extrema, a robust estimation method based on the median filter was applied. Then, all smaller extrema were classified into three types. Different preprocessing methods were applied for every type. After that, a new preprocessed precise clock product was obtained. With this preprocessed satellite clock product, the ISB continuity was substantially improved, and the improvement in the ISB continuity can reach 85.1%, on the average. These results indicate that for detecting and repairing ISB jumps, the proposed preprocessing method on satellite clock products is very effective. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.3390/rs12050850 | REMOTE SENSING |
Keywords | DocType | Volume |
inter-system bias,robust estimation,median filter,correlation analysis,ISB continuity | Journal | 12 |
Issue | Citations | PageRank |
5 | 0 | 0.34 |
References | Authors | |
0 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Nan Jiang | 1 | 0 | 1.35 |
| Tianhe Xu | 2 | 18 | 9.82 |
| Yan Xu | 3 | 0 | 1.35 |
| Guochang Xu | 4 | 6 | 7.11 |
| Harald Schuh | 5 | 35 | 20.68 |