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Sensors (Basel). 2018 Nov 6;18(11). pii: E3809. doi: 10.3390/s18113809.

A Modified Extended Kalman Filter for a Two-Antenna GPS/INS Vehicular Navigation System.

Author information

1
School of Geomatics, Liaoning Technical University, Fuxin 123000, China. kinghaoys@163.com.
2
State Key Laboratory of Satellite Navigation System and Equipment Technology, Shijiazhuang 050081, China. kinghaoys@163.com.
3
School of Geomatics, Liaoning Technical University, Fuxin 123000, China. xu_ag@126.com.
4
School of Geomatics, Liaoning Technical University, Fuxin 123000, China. survey_suixin@163.com.
5
State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun 130025, China. wangyulei@jlu.edu.cn.

Abstract

Recently, the integration of an inertial navigation system (INS) and the Global Positioning System (GPS) with a two-antenna GPS receiver has been suggested to improve the stability and accuracy in harsh environments. As is well known, the statistics of state process noise and measurement noise are critical factors to avoid numerical problems and obtain stable and accurate estimates. In this paper, a modified extended Kalman filter (EKF) is proposed by properly adapting the statistics of state process and observation noises through the innovation-based adaptive estimation (IAE) method. The impact of innovation perturbation produced by measurement outliers is found to account for positive feedback and numerical issues. Measurement noise covariance is updated based on a remodification algorithm according to measurement reliability specifications. An experimental field test was performed to demonstrate the robustness of the proposed state estimation method against dynamic model errors and measurement outliers.

KEYWORDS:

adaptive noise covariance; measurement outliers; navigation system; numerical issue; positive feedback; two-antenna GPS/INS

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