Research on time-correlated errors using Allan variance in a Kalman filter applicable to vector-tracking-based GNSS software-defined receiver for autonomous ground vehicle navigation

Yiran Luo, Jian Li, Chunyang Yu, Bing Xu, You Li, Li Ta Hsu, Naser El-Sheimy

Research output: Journal article publicationJournal articleAcademic researchpeer-review

3 Citations (Scopus)

Abstract

The global navigation satellite system (GNSS) has been applied to many areas, e.g., the autonomous ground vehicle, unmanned aerial vehicle (UAV), precision agriculture, smart city, and the GNSS-reflectometry (GNSS-R), being of considerable significance over the past few decades. Unfortunately, the GNSS signal performance has the high risk of being reduced by the environmental interference. The vector tracking (VT) technique is promising to enhance the robustness in high dynamics as well as improve the sensitivity against the weak environment of the GNSS receiver. However, the time-correlated error coupled in the receiver clock estimations in terms of the VT loop can decrease the accuracy of the navigation solution. There are few works present dealing with this issue. In this work, the Allan variance is accordingly exploited to specify a model which is expected to account for this type of error based on the 1st-order Gauss-Markov (GM) process. Then, it is used for proposing an enhanced Kalman filter (KF) by which this error can be suppressed. Furthermore, the proposed system model makes use of the innovation sequence so that the process covariance matrix can be adaptively adjusted and updated. The field tests demonstrate the performance of the proposed adaptive vector-tracking time-correlated error suppressed Kalman filter (A-VTTCES-KF). When compared with the results produced by the ordinary adaptive KF algorithm in terms of the VT loop, the real-time kinematic (RTK) positioning and code-based differential global positioning system (DGPS) positioning accuracies have been improved by 14.17% and 9.73%, respectively. On the other hand, the RTK positioning performance has been increased by maximum 21.40% when compared with the results obtained from the commercial low-cost U-Blox receiver.

Original languageEnglish
Article number1026
JournalRemote Sensing
Volume11
Issue number9
DOIs
Publication statusPublished - 1 May 2019

Keywords

  • Allan variance
  • Gauss-Markov (GM) process
  • Global navigation satellite system (GNSS)
  • Innovation sequence
  • Kalman filter (KF)
  • RTKLIB
  • Software-defined receiver (SDR)
  • Time-correlated error
  • Vector tracking (VT)

ASJC Scopus subject areas

  • Earth and Planetary Sciences(all)

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