Code multipath analysis of Galileo FOC satellites by time-frequency representation

被引:16
|
作者
Robustelli, Umberto [1 ]
Pugliano, Giovanni [1 ]
机构
[1] Parthenope Univ Naples, Dept Engn, Naples, Italy
关键词
Galileo FOC satellites; Time-frequency analysis; Scalogram; Continuous wavelet transform; Multipath; Code-minus-carrier; Pseudorange multipath observable; GPS; PERFORMANCE; MITIGATION; SINGLE;
D O I
10.1007/s12518-018-0241-3
中图分类号
TP7 [遥感技术];
学科分类号
081102 ; 0816 ; 081602 ; 083002 ; 1404 ;
摘要
Galileo is currently in full operational capability (FOC) phase with 18 FOC satellites. The purpose of this paper is to investigate the multipath performance of Galileo FOC signals E1, E5a, E5b, and E5. With the advent of FOC satellites, assessing the multipath behavior of Galileo FOC signals is becoming one of the greatest interests for the user's community. In fact, the reduction of multipath has been one of the main criteria on which the Galileo signals have been designed. We analyzed data over three different days from six International GNSS Service (IGS) stations located at different latitudes, for all visible Galileo satellites. This is one of the first studies to present experimental results for the multipath of Galileo signals transmitted by FOC satellites since they started to operate in 2015. Code multipath was estimated using code-minus-carrier (CMC) and pseudorange multipath (MP) methods. The study involves a comparison with the GPS signals, showing results of multipath performance as function of satellite elevation. A time-frequency representation, based on the use of continuous wavelet transform (CWT), was performed to rigorously account for the presence of multipath. The expectations of FOC satellites to lead to a multipath reduction have been verified: the E5 signal shows the highest suppression of multipath as compared to the other Galileo and GPS signals and it is almost independent from the satellite elevation. An assigned FOC satellite showed a lower frequency multipath compared to a GPS satellite at the same azimuth and elevation, which is in line with a lower Galileo satellite elevation rate.
引用
收藏
页码:69 / 80
页数:12
相关论文
共 50 条
  • [31] Heart rate variability characterization:: Time-frequency representation and nonlinear analysis
    Vallverdú, M
    Clariá, F
    Carvajal, R
    Martínez, P
    Alonso, JL
    Zareba, W
    Viñolas, X
    de Luna, AB
    Caminal, P
    COMPUTERS IN CARDIOLOGY 1999, VOL 26, 1999, 26 : 257 - 260
  • [32] Radar range profile analysis with natural frame time-frequency representation
    Chen, VC
    WAVELET APPLICATIONS IV, 1997, 3078 : 433 - 448
  • [33] Analysis of nonlinear FM signals by pattern recognition of their time-frequency representation
    Barbarossa, S
    Lemoine, O
    IEEE SIGNAL PROCESSING LETTERS, 1996, 3 (04) : 112 - 115
  • [34] Time-Frequency Representation of Signals by Wavelet Transform
    Pukhova, Valentina
    Gorelova, Elizaveta
    Burnasheva, Sakhaya
    Ferrini, Gabriele
    PROCEEDINGS OF THE 2017 IEEE RUSSIA SECTION YOUNG RESEARCHERS IN ELECTRICAL AND ELECTRONIC ENGINEERING CONFERENCE (2017 ELCONRUS), 2017, : 715 - 718
  • [35] Phonocardiogram classification using time-frequency representation
    Shino, H
    Yoshida, H
    Mizuta, H
    Yana, K
    PROCEEDINGS OF THE 19TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, VOL 19, PTS 1-6: MAGNIFICENT MILESTONES AND EMERGING OPPORTUNITIES IN MEDICAL ENGINEERING, 1997, 19 : 1636 - 1637
  • [36] Representation of Operators by Sampling in the Time-Frequency Domain
    Monika Dörfler
    Bruno Torrésani
    Sampling Theory in Signal and Image Processing, 2011, 10 (1-2): : 171 - 190
  • [37] Computation complexity of time-frequency representation of signals
    Misurec, J
    Koula, I
    Proceedings of the 4th WSEAS International Conference on Applications of Electrical Engineering, 2005, : 167 - 169
  • [38] Approximating the Time-Frequency Representation of Biosignals with Chirplets
    Talakoub, Omid
    Cui, Jie
    Wong, Willy
    EURASIP JOURNAL ON ADVANCES IN SIGNAL PROCESSING, 2010,
  • [39] AN ANALYSIS OF INSTANTANEOUS FREQUENCY REPRESENTATION USING TIME-FREQUENCY DISTRIBUTIONS - GENERALIZED WIGNER DISTRIBUTION
    STANKOVIC, L
    STANKOVIC, S
    IEEE TRANSACTIONS ON SIGNAL PROCESSING, 1995, 43 (02) : 549 - 552
  • [40] Sparse Bayesian representation in time-frequency domain
    Kim, Gwangsu
    Lee, Jeongran
    Kim, Yongdai
    Oh, Hee-Seok
    JOURNAL OF STATISTICAL PLANNING AND INFERENCE, 2015, 166 : 126 - 137