GNSS multipath effect suppression method based on EMD iteration threshold value smoothing

Abstract

The invention discloses a GNSS multipath effect suppression method based on EMD iteration threshold value smoothing. EMD is performed on measuring errors to obtain N intrinsic mode function components, multipath errors are often concentrated in a high-order IMF and a remainder item, on one hand, singular spectrum analysis is used for performing noise estimation on N IMFs after EMD, and according to estimation results, first M IMFs are selected for noise auxiliary data analysis, so that EMD results of the measuring errors are obtained; on the other hand, the mode that first IMF data are sampled randomly is adopted, multiple sequences which are the same as an original signal in signal-to-noise ratio are constructed, mode unit threshold value smoothing is adopted for removing noise of the sequences, multiple results after noise removal are averaged to obtain the GNSS multipath errors through separation, and the GNSS multipath errors are used for compensating GNSS measuring results to achieve multipath effect suppression in the measuring process. According to the GNSS multipath effect suppression method, EMD precision is improved, and influences of noise are reduced.

Description

technical field [0001] The invention relates to a global satellite navigation system, in particular to a GNSS multipath effect suppression method based on EMD iterative threshold filtering. Background technique [0002] GNSS refers to satellite navigation systems in general, including global, regional and enhanced satellite navigation, such as GPS in the United States, Glonass in Russia, Galileo in Europe, and Beidou satellite navigation system in China. The GNSS software receiver realizes positioning by receiving the broadcast ephemeris signal of the satellite, measuring the transmission delay of the signal, and calculating the distance between the receiver and the satellite in combination with the propagation speed of the signal. Because there may be reflectors around the receiver, the signal it receives is a mixed signal of the satellite signal and its reflected signal, and the signal reflection increases the transmission delay of the satellite signal, so the distance cal...

AI Technical Summary

Problems solved by technology

Based on the time-varying characteristics of multipath error, that is, its statistical characteristics change with time, the traditional fixed-structure filter cannot be used, so many adaptive filtering methods are introduced into the suppression process of multipath error, such as based on wavelet transform Adaptive filtering based on variable structure, finite impulse response (FIR) filtering based on variable structure and conventional adaptive filtering based on EMD. The above methods have achieved good results under certain conditions. Closely related, the design of adaptive filtering in dynamic environments is complex, and its applicability needs to be further studied

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