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A combined iCEEMDAN and VMD method for mitigating the impact of ionospheric scintillation on GNSS signals

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Severe amplitude and phase scintillation induced by the ionospheric plasma density irregularities degrades the performance of global navigation satellite system (GNSS) receivers. Scintillation typically has adverse effects at the tracking process and thus adversely affects the raw GNSS measurements used in a number of applications. Hence, it is important to develop robust methodologies for detecting and mitigating ionospheric effects on the GNSS signals. In this paper, we propose a novel method based on the combination of improved complete ensemble empirical mode decomposition with adaptive noise (iCEEMDAN) and variational mode decomposition (VMD) methods. The proposed method employs a detrended fuctuation analysis (DFA)-based metric for robust thresholding between the scintillation-free and amplitude scintillated GNSS signals. The major contribution of the proposed method is development of novel approaches for selection of intrinsic mode functions (IMFs) based on DFA and optimised selection of [K, 훼] parameters of the VMD. The performance of the proposed method was evaluated and was observed that it is better than existing ionospheric scintillation effects mitigation algorithms for both simulated and real-time GPS scintillation datasets. The proposed method can denoise approximately 9.23–15.30 dB scintillation noise from the synthetic and 0.2–0.48 from the real scintillation index (S4) values. Therefore, the proposed (iCEEMDAN-VMD) method is appropriate for mitigating the ionospheric scintillation effects on the GNSS signals.
Czasopismo
Rocznik
Strony
1933--1948
Opis fizyczny
Bibliogr. 38 poz.
Twórcy
autor
  • Department of Electrical and Electronics Engineering, Birla Institute of Technology and Science, Pilani, K.K. Birla Goa Campus, Goa 403726, India
  • Department of Electrical and Electronics Engineering, Birla Institute of Technology and Science, Pilani, K.K. Birla Goa Campus, Goa 403726, India
  • Department of Electronics and Communication Engineering, Koneru Lakshmaiah Education Foundation, K L University, Vaddeswaram, Guntur, Andhra Pradesh 522502, India
autor
  • Department of Electrical and Electronics Engineering, Birla Institute of Technology and Science, Pilani, K.K. Birla Goa Campus, Goa 403726, India
Bibliografia
  • 1. Ahmed A, Tiwari R, Strangeways H, Rutter N, Boussakta S (2014) GPS tracking loop performance using wavelet denoising. In: The 7th ESA workshop on Satellite Navigation Technologies (NAVITEC 2014), Space Research and Technology Centre, European Space Agency (ESA/ESTEC), Newcastle University
  • 2. Ahmed WA, Wu F, Marlia D, Zhao Y et al (2019) Mitigation of ionospheric scintillation effects on GNSS signals with VMD-MFDFA. Remote Sens 11(23):2867
  • 3. Aquino M, Moore T, Dodson A, Waugh S, Souter J, Rodrigues FS (2005) Implications of ionospheric scintillation for GNSS users in Northern Europe. J Navig 58(2):241
  • 4. Cervera M, Thomas R (2006) Latitudinal and temporal variation of equatorial ionospheric irregularities determined from GPS scintillation observations. Ann Geophys Copernicus GmbH 24:3329–3341
  • 5. Colominas MA, Schlotthauer G, Torres ME (2014) Improved complete ensemble EMD: a suitable tool for biomedical signal processing. Biomed Signal Process Control 14:19–29
  • 6. De Rezende L, De Paula E, Kantor I, Kintner P (2007) Mapping and survey of plasma bubbles over Brazilian territory. J Navig 60(1):69
  • 7. Dragomiretskiy K, Zosso D (2013) Variational mode decomposition. IEEE Trans Signal Process 62(3):531–544
  • 8. Flandrin P, Rilling G, Goncalves P (2004) Empirical mode decomposition as a filter bank. IEEE Signal Process Lett 11(2):112–114
  • 9. Ganguly S, Jovancevic A, Brown A, Kirchner M, Zigic S, Beach T, Groves KM (2004) Ionospheric scintillation monitoring and mitigation using a software GPS receiver. Radio Sci 39(1):1–9
  • 10. Han J, van der Baan M (2013) Empirical mode decomposition for seismic time-frequency analysis. Geophysics 78(2):O9–O19. https://doi.org/10.1190/geo2012-0199.1
  • 11. Honório BCZ, de Matos MC, Vidal AC (2017) Progress on empirical mode decomposition-based techniques and its impacts on seismic attribute analysis. Interpretation 5(1):SC17–SC28
  • 12. Huang NE, Shen Z, Long SR, Wu MC, Shih HH, Zheng Q, Yen NC, Tung CC, Liu HH (1998) The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis. Proc R Soc Lond Ser A Math Phys Eng Sci 454(1971):903–995
  • 13. Humphreys TE, Psiaki ML, Hinks JC, O’Hanlon B, Kintner PM (2009) Simulating ionosphere-induced scintillation for testing GPS receiver phase tracking loops. IEEE J Sel Top Signal Process 3(4):707–715
  • 14. Jakowski N, Mayer C, Wilken V, Hoque MM (2008) Ionospheric impact on GNSS signals. Física de la Tierra 20:11
  • 15. Jiang X, Shen C, Shi J, Zhu Z (2018) Initial center frequency-guided VMD for fault diagnosis of rotating machines. J Sound Vib 435:36–55
  • 16. Kintner PM, Kil H, Beach TL, de Paula ER (2001) Fading timescales associated with GPS signals and potential consequences. Radio Sci 36(4):731–743
  • 17. Kintner PM, Ledvina BM, De Paula E (2007) GPS and ionospheric scintillations. Space Weather 5(9):1–23
  • 18. Lahmiri S, Boukadoum M (2014) Biomedical image denoising using variational mode decomposition. In: 2014 IEEE biomedical circuits and systems conference (BioCAS) proceedings, IEEE, pp 340–343
  • 19. Li H, Liu T, Wu X, Chen Q (2020) An optimized VMD method and its applications in bearing fault diagnosis. Measurement 166:108185
  • 20. Liu Y, Yang G, Li M, Yin H (2016) Variational mode decomposition denoising combined the detrended fluctuation analysis. Signal Process 125:349–364
  • 21. Liu W, Cao S, Jin Z, Wang Z, Chen Y (2017) A novel hydrocarbon detection approach via high-resolution frequency-dependent AVO inversion based on variational mode decomposition. IEEE Trans Geosci Remote Sens 56(4):2007–2024
  • 22. Mert A, Akan A (2014) Detrended fluctuation thresholding for empirical mode decomposition based denoising. Dig Signal Process 32:48–56
  • 23. Miriyala S, Koppireddi PR, Chanamallu SR (2015) Robust detection of ionospheric scintillations using MF-DFA technique. Earth Planets Space 67(1):98
  • 24. Mushini SC, Jayachandran P, Langley R, MacDougall J, Pokhotelov D (2012) Improved amplitude-and phase-scintillation indices derived from wavelet detrended high-latitude GPS data. GPS Solut 16(3):363–373
  • 25. Nalband S, Prince A, Agrawal A (2017) Entropy-based feature extraction and classification of vibroarthographic signal using complete ensemble empirical mode decomposition with adaptive noise. IET Sci Meas Technol 12(3):350–359
  • 26. Navarro X, Porée F, Carrault G (2012) ECG removal in preterm EEG combining empirical mode decomposition and adaptive filtering. In: 2012 IEEE international conference on acoustics, speech and signal processing (ICASSP), pp 661–664
  • 27. Peng CK, Buldyrev SV, Havlin S, Simons M, Stanley HE, Goldberger AL (1994) Mosaic organization of DNA nucleotides. Phys Rev E 49(2):1685
  • 28. Pullen S, Park YS, Enge P (2009) Impact and mitigation of ionospheric anomalies on ground-based augmentation of GNSS. Radio Sci 44(01):1–10
  • 29. Ratnam DV, Sivavaraprasad G, Lee J (2015) Automatic ionospheric scintillation detector for global navigation satellite system receivers. IET Radar Sonar Navig 9(6):702–711
  • 30. Ruan H, Zhang L, Luo Y, Long T (2016) GNSS carrier phase tracking with discrete wavelet transform filtering under ionospheric scintillation. IEEE Commun Lett 21(2):394–397
  • 31. Sivavaraprasad G, Padmaja RS, Ratnam DV (2017) Mitigation of ionospheric scintillation effects on GNSS signals using variational mode decomposition. IEEE Geosci Remote Sens Lett 14(3):389–393
  • 32. Smith JS (2005) The local mean decomposition and its application to EEG perception data. J R Soc Interface 2(5):443–454
  • 33. Tadivaka RV, Paruchuri BP, Miriyala S, Koppireddi PR, Devanaboyina VR (2017) Detection of ionospheric scintillation effects using LMD-DFA. Acta Geophys 65(4):777–784
  • 34. Torres ME, Colominas MA, Schlotthauer G, Flandrin P (2011) A complete ensemble empirical mode decomposition with adaptive noise. In: 2011 IEEE international conference on acoustics, speech and signal processing (ICASSP), IEEE, pp 4144–4147
  • 35. Upadhyay A, Pachori R (2017) Speech enhancement based on MEMD-VMD method. Electron Lett 53(7):502–504
  • 36. Valladares C, Chau J (2012) The low-latitude ionosphere sensor network: initial results. Radio Sci 47(04):1–18
  • 37. Wu Z, Huang NE (2009) Ensemble empirical mode decomposition: a noise-assisted data analysis method. Adv Adapt Data Anal 1(01):1–41
  • 38. Yeh JR, Shieh JS, Huang NE (2010) Complementary ensemble empirical mode decomposition: a novel noise enhanced data analysis method. Adv Adapt Data Anal 2(02):135–156
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-53d78161-8f6a-4e76-b9e4-04f36bdf827f
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