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Amplified wavelet-ANFIS-based model for GPS/INS integration to enhance vehicular navigation system

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Abstract

Inertial navigation system (INS) relying on gyroscopes and accelerometers has been recently utilized in land vehicles. These INS sensors are integrated with Global Positioning System (GPS) to provide reliable positioning solutions in case of GPS outages that commonly occur in urban canyons. The major inadequacies of INS navigation sensors are the high noise level and the large bias instabilities that are stochastic in nature. The effects of these inadequacies manifest themselves as large position errors during GPS outages. Wavelet analysis is a signal processing method which is recently auspicious by many researchers due to its advantageous adaptation to non-stationary signals and able to perform analysis in both time and frequency domain over other signal processing methods such as the fast Fourier transform in some fields. This research proposes the utilization of wavelet de-nosing to improve the signal-to-noise ratio of each of the INS sensors. In addition, a neuro-fuzzy module is used to provide a reliable prediction of the vehicle position during GPS outages. The results from a road test experiment show the effectiveness of the proposed wavelet—neuro-fuzzy module.

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Authors and Affiliations

  1. Department of Civil and Structural Engineering, Universiti Kebangsaan Malaysia (UKM), Bangi, Malaysia

    A. El-Shafie & O. A. Karim

  2. Department of Engineering Science, Universiti Malaysia Terengganu (UMT), Kuala Terengganu, Terengganu, Malaysia

    A. Najah

Authors
  1. A. El-Shafie
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  2. A. Najah
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  3. O. A. Karim
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Correspondence to A. Najah.

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El-Shafie, A., Najah, A. & Karim, O.A. Amplified wavelet-ANFIS-based model for GPS/INS integration to enhance vehicular navigation system. Neural Comput & Applic 24, 1905–1916 (2014). https://doi.org/10.1007/s00521-013-1430-y

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  • DOI: https://doi.org/10.1007/s00521-013-1430-y

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