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A New Method for Multipath Filtering in GPS Static High-Precision Positioning

机译:GPS静态高精度定位中多径滤波的新方法

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摘要

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.
机译:众所周知,MultiPath是短基线GPS静态高精度定位的GPS静态高精度定位的主要误差源之一。用于减少多径的大多数算法操纵GPS双差(DD)观察残留为GPS信号处理中的输入信号。在传统的多径缓解方法中,应用小波变换(WT)来分解用于识别多径干扰的GPS DD观察残余,不能有效地滤除信号的高频部分的白噪声,并且它容易发生边缘效应。在本文中,为了提取多径,提出了一种基于二维运动加权平均处理(WP-TD)的小波分组算法。该算法不仅可以有效地滤除信号的高频部分的白噪声,而且还削弱了边缘效应的影响。此外,考虑到静态定位中多径误差的可重复性,我们提出了一种确定小波分组分解层的水平,其更有效地使多径提取。实验结果表明,当将获得的多径施加到DD坐标序列以进行定位校正时,校正定位精度比传统小波变换的定位精度高度为14.14%。

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