摘要
A filter method that combines ensemble empirical modal decomposition(EEMD)and wavelet analysis methods was proposed to separate and correct the global navigation satellite system(GNSS)multipath error more effectively.In this method,the GNSS signal is first decomposed into several intrinsic mode functions(IMFs)and a residual through EEMD.Then,the IMFs and residual are classified into noise terms,mixed terms,and useful terms according to a combined classification criterion.Finally,the mixed term denoised by wavelet and the useful term are reconstructed to obtain the multipath error and thus enable an error correction model to be built.The measurement data provided by the Curtin GNSS Research Center were used for processing and analysis.Results show that the proposed method can separate multipath error from GNSS data to a great extent,thereby effectively addressing the defects of EEMD and wavelet methods on multipath error weakening.The error correction model established with the separated multipath error has a higher accuracy and provides a certain reference value for research on related signal processing.
为了更有效地分离与改正GNSS多路径误差,提出一种将集合经验模态分解(EEMD)和小波分析(wavelet)方法相组合的改进滤波方法.首先采用EEMD将GNSS信号分解为若干个IMF项与残余项,再采用一种组合分类准则将IMF项与残余项细分为噪声项、混合项和有用项,最后将小波降噪后的混合项与有用项重构得到GNSS多路径误差,建立误差改正模型.通过对科廷大学GNSS研究中心提供的实测数据处理分析,研究结果表明:所提方法能够更大程度地从GNSS数据中分离多路径误差,并且有效改进了EEMD与小波方法在多路径误差削弱上的不足.利用该方法分离的多路径误差建立的误差改正模型不仅精度更高,对相关信号处理的研究也具有一定的参考价值.
基金
The National Natural Science Foundation of China(No.41974030)
the Postgraduate Research&Practice Innovation Program of Jiangsu Province(No.KYCX17_0150).
