Abstract
It is well known that multipath is one of the main sources of errors in GPS static high precision positioning of short baselines. Most algorithms for reducing multipath manipulate the GPS double difference (DD) observation residuals as input signal in GPS signal processing. In the traditional multipath mitigation methods, applying the wavelet transform (WT) to decompose the GPS DD observation residuals for identifying the multipath disturbance cannot effectively filter out the white noise of the high frequency part of the signal, and it is prone to edge effect. In this paper, for extracting multipath, a wavelet packet algorithm based on two-dimensional moving weighted average processing (WP-TD) is proposed. This algorithm can not only effectively filter out the white noise of the high frequency part of the signal, but also weaken the influence of the edge effect. Furthermore, considering the repeatability of multipath error in static positioning, we propose a method for determining the level of wavelet packet decomposition layers which make multipath extraction more effectively. The experimental results show that the corrected positioning accuracy is 14.14% higher than that of the traditional wavelet transform when applying the obtained multipath to DD coordinate sequences for position correction.
Highlights
In GPS static high-precision positioning of short baselines, errors such as ionospheric delay, tropospheric delay, satellite orbit error, receiver clock error, and satellite clock error can be eliminated or attenuated by differential techniques while multipath disturbance are not correlated at both ends of the baseline which make it impossible to be eliminated by differential techniques and become the main source of error affecting the positioning accuracy [1,2].GPS multipath disturbance occurs when GPS signals travel from a satellite to a receiver via several paths due to reflection or diffraction of signals by nearby obstacles [3]
Considering the repeatability of multipath error in static positioning, we propose a method for determining the level of wavelet packet decomposition layers which make multipath extraction more effectively
Lawrence Lau (2017) proposed a generic and robust three-level wavelet packets based denoising method for repeat-time-based carrier phase multipath filtering in relative positioning; the results show that the wavelet packets based method is better than the DWT-based method in the repeat time-based multipath filtering [19]
Summary
In GPS static high-precision positioning of short baselines, errors such as ionospheric delay, tropospheric delay, satellite orbit error, receiver clock error, and satellite clock error can be eliminated or attenuated by differential techniques while multipath disturbance are not correlated at both ends of the baseline which make it impossible to be eliminated by differential techniques and become the main source of error affecting the positioning accuracy [1,2]. P. Zhong et al (2008) proposed a method based on the technique of cross-validation for automatically identifying wavelet signal layers is developed and used for separating noise from signals in data series, and applied to mitigate GPS multipath effects [3]. WPT effectively mitigates the defects in wavelet transform of low resolution in high frequency regions by decomposing both the scale space and wavelet space [21] This means we can further subdivide the high frequency portion of signal and extract multipath more effectively. We propose a new method named wavelet packet algorithm based on two-dimensional moving weighted average processing (TDMWA), compared with the traditional wavelet algorithm, which can more effectively mitigate the multipath of the DD coordinate residual sequences, and effectively weaken the influence of the edge effect.
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