3D Visualization of Indoor GPS L5Q Baseband Signal and Its Long-Coherent De-noising Using Graph Fourier Transform
Graph signal processing(GSP)has been hotly debated in many research fields at present times.The GSP minimizes the irregular errors of the interfered input signals.An accurate time-of-arrival estimation from a weak and multipath channel is an extremely challenging case in the field of global navigation satellite systems(GNSSs).To recover the contaminated signal power,the GSP is a promising tool to construct an optimal filter,and,then,differentiate the line-of-sight(LOS)signal power and the other irregular noise power.In this work,a three-dimension(3D)visualized graph is firstly presented with the cross-ambiguity function(CAF)between the incoming GPS L5Q signal and its replica.Then,the long coherent integration is used to reduce the multipath effect on the correlation amplitude.After that,the graph Fourier transform(GFT)is used to further de-noise the proposed baseband graph.The intermediate frequency(IF)L5Q signal is collected in a real-world indoor situation and it is used to implement the experiments.The correlation amplitude and the s-curve distribution demonstrate the performance of the proposed algorithm.
cross-ambiguity function graph Fourier transform indoor GPS L5 long coherent integration GNSS baseband de-noising
Yiran Luo Naser El-Sheimy
Department of Geomatics Engineering,University of Calgary,Calgary T2N1N4,Canada
国内会议
北京
英文
1-11
2022-12-01（万方平台首次上网日期，不代表论文的发表时间）