Ionosphere-corrected range estimation in dual-frequency GNSS receivers
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Details
| Original language | English |
|---|---|
| Pages (from-to) | 215-224 |
| Journal | IET RADAR SONAR AND NAVIGATION |
| Volume | 5 |
| Issue number | 3 |
| DOIs | |
| Publication status | Published - 2011 |
| Publication type | A1 Journal article-refereed |
Abstract
In Global Navigation Satellite Systems (GNSSs), the measurement of the satellite-receiver pseudorange requires the estimation of signal’s total delay. Because the accuracy of the latter affects significantly the accuracy of the final position, it is essential to consider the effect of various error sources. Ionosphere is commonly regarded as one of the most influential sources due to the fact that it can significantly delay the signal; therefore, it is of paramount importance to mitigate its effects.
In single-frequency GNSS receivers, the ionospheric delay is typically found with the use of mathematical models. Because their accuracy is usually determined by their complexity, mass-market receivers employ relatively computationally simple models at the expense of limited accuracy. On the other hand, in dual-frequency receivers, we can virtually eliminate the ionospheric effects if higher order effects are ignored [1, 2]. While such an advantage has been widely recognised in the literature, the effect of the tracking error in the ionospheric correction and inherently on the range estimation is yet to be studied.
In this paper, we investigate the effect of tracking error on the ionosphere-corrected range in dual-frequency receivers. We statistically analyse the performance of Least Square (LS) method and we compare it with the simulation-based. Moreover, we compare the performance of the traditional approach with LS and Constrained LS methods, as well as with a new method for range estimation, proposed by the authors. The results showed that the traditional and LS methods perform well only under the restriction of zero tracking error, while our method has the best average performance.
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Field of science, Statistics Finland
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