4.7 Article

Novel hybrid of strong tracking Kalman filter and wavelet neural network for GPS/INS during GPS outages

Journal

MEASUREMENT
Volume 46, Issue 10, Pages 3847-3854

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.measurement.2013.07.016

Keywords

GPS/INS integration; Strong tracking Kalman filter; Wavelet neural network; GPS outages

Funding

  1. Ocean special funds for scientific research on public causes [201205035-09]
  2. Specialized Research Fund for the Doctoral Program of Higher Education [20110092110039]
  3. 973 Program [2009CB724002]
  4. National Natural Science Foundation of China [41204025]
  5. Research Innovation Program for College Graduates of Jiangsu Province [CXZZ_ 0144]
  6. Scientific Research Foundation of Graduate School of Southeast University [ybjj1130]

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Aiming to improve positioning precision of the GPS/INS integrated navigation system during GPS outages, a novel model combined with strong tracking Kalman filter (STKF) and wavelet neural network (WNN) algorithms for INS errors compensation is proposed and tested. STKF is used to estimate INS errors as a replacement of Kalman filter (KF), and WNN is applied to establish a highly accurate model based on STKF when GPS works well and to predict INS errors during GPS outages. Performance of the proposed model has been experimentally verified using GPS and INS data collected in a land vehicle navigation test. The comparison results indicate that the proposed model combined with STKF/WNN algorithms can effectively provide high accurate corrections to the standalone INS during GPS outages. (C) 2013 Elsevier Ltd. All rights reserved.

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