Vol.68, No.1, 2021, pp.857-876, doi:10.32604/cmc.2021.016894
Kernel Entropy Based Extended Kalman Filter for GPS Navigation Processing
  • Dah-Jing Jwo*, Jui-Tao Lee
Department of Communications, Navigation and Control Engineering, National Taiwan Ocean University, Keelung, 202301, Taiwan
* Corresponding Author: Dah-Jing Jwo. Email:
Received 12 January 2021; Accepted 14 February 2021; Issue published 22 March 2021
This paper investigates the kernel entropy based extended Kalman filter (EKF) as the navigation processor for the Global Navigation Satellite Systems (GNSS), such as the Global Positioning System (GPS). The algorithm is effective for dealing with non-Gaussian errors or heavy-tailed (or impulsive) interference errors, such as the multipath. The kernel minimum error entropy (MEE) and maximum correntropy criterion (MCC) based filtering for satellite navigation system is involved for dealing with non-Gaussian errors or heavy-tailed interference errors or outliers of the GPS. The standard EKF method is derived based on minimization of mean square error (MSE) and is optimal only under Gaussian assumption in case the system models are precisely established. The GPS navigation algorithm based on kernel entropy related principles, including the MEE criterion and the MCC will be performed, which is utilized not only for the time-varying adaptation but the outlier type of interference errors. The kernel entropy based design is a new approach using information from higher-order signal statistics. In information theoretic learning (ITL), the entropy principle based measure uses information from higher-order signal statistics and captures more statistical information as compared to MSE. To improve the performance under non-Gaussian environments, the proposed filter which adopts the MEE/MCC as the optimization criterion instead of using the minimum mean square error (MMSE) is utilized for mitigation of the heavy-tailed type of multipath errors. Performance assessment will be carried out to show the effectiveness of the proposed approach for positioning improvement in GPS navigation processing.
GPS; satellite navigation; extended Kalman filter; entropy; correntropy; multipath; non-Gaussian
Cite This Article
D. Jwo and J. Lee, "Kernel entropy based extended kalman filter for gps navigation processing," Computers, Materials & Continua, vol. 68, no.1, pp. 857–876, 2021.
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