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A Robust GPS Navigation Filter Based on Maximum Correntropy Criterion with Adaptive Kernel Bandwidth.

Dah-Jing Jwo1, Yi-Ling Chen1, Ta-Shun Cho2

  • 1Department of Communications, Navigation and Control Engineering, National Taiwan Ocean University, 2 Peining Rd., Keelung 202301, Taiwan.

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Summary
This summary is machine-generated.

This study introduces an adaptive kernel bandwidth method to improve Global Positioning System (GPS) navigation accuracy in non-Gaussian noise. The new technique enhances filter performance and robust state estimation for precise positioning.

Keywords:
GPSGaussian noiseadaptive kernel bandwidthextended Kalman filterheavy-tailed noisemaximum correntropy criterion

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Area of Science:

  • Signal Processing
  • Navigation Systems
  • Robust Estimation

Background:

  • Global Positioning System (GPS) navigation is susceptible to interference and non-Gaussian noise, degrading positioning accuracy.
  • Traditional Minimum Mean-Square Error (MMSE) algorithms perform poorly with non-Gaussian noise.
  • Maximum Correntropy Criteria (MCC) adaptive filtering shows promise for handling heavy-tailed noise.

Purpose of the Study:

  • To enhance the performance of GPS navigation receivers in the presence of non-Gaussian noise.
  • To address the limitations of fixed kernel widths in conventional Maximum Correntropy Criterion-based Extended Kalman Filter (MCCEKF) algorithms.
  • To develop a robust state estimation method for GPS signals with anomalous noise values.

Main Methods:

  • Implementation of an Adaptive Kernel Bandwidth (AKB) technique within the MCC framework.
  • Generation of a kernel function matrix using adaptive variables to dynamically adjust kernel width.
  • Application of the novel MCCEKF with Adaptive Kernel Bandwidth (MCCEKF-AKB) algorithm.

Main Results:

  • The MCCEKF-AKB algorithm demonstrates improved performance over conventional MCCEKF by adapting kernel width.
  • Effective reduction of pulse noise and enhanced performance in heavy-tailed noise conditions.
  • Achieved robust state estimation for outliers while maintaining filtering accuracy.

Conclusions:

  • The proposed MCCEKF-AKB offers a computationally simple and effective solution for GPS navigation under generalized noise conditions.
  • Adaptive kernel bandwidth is crucial for optimizing MCC filter performance in non-Gaussian noise environments.
  • This approach provides a qualitative solution for studying random structures in noisy measurement data for improved localization.