Proceedings ArticleDOI
An improved adaptive Kalman filtering algorithm for advanced robot navigation system based on GPS/INS
Xiaochuan Zhao,Yi Qian,Min Zhang,Jinzhe Niu,Yuxiang Kou +4 more
- pp 1039-1044
TLDR
The experimental results demonstrate that the improved adaptive Kalman filtering algorithm proposed in this paper has a strong adaptability to time-varying measurement noises, which improves precision of the advanced robot navigation.Abstract:
Navigation technology plays an important role in the designing of advanced robot. An advanced robot navigation system based on GPS/INS is modeled in this paper. According to the model, the causes of the errors in measurement equation are analyzed, concluding that HDOP (Horizontal Dilution of Precision) and VDOP (Vertical Dilution of Precision) provided by GPS receiver are the crucial factors for the change of measurement noise in the mathematical model. Based on the above conclusion, this paper proposes a novel second order fuzzy self-adaptive filter design. Choosing the differences of location and velocity information provided by GPS receiver and INS device as the inputs, this filter modifies the regulation factor based on the residual sequence statistical information and PDOP (Position Dilution of Precision) provided by GPS receiver to correct the outputs of INS device using fuzzy logic. The experimental results demonstrate that the improved adaptive Kalman filtering algorithm proposed in this paper has a strong adaptability to time-varying measurement noises, which improves precision of the advanced robot navigation.read more
Citations
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Journal ArticleDOI
Accurate Solution of Navigation Equations in GPS Receivers for Very High Velocities Using Pseudorange Measurements
TL;DR: Seven methods for solving navigation equations in very high velocities using least squares method and its combination with the variance estimation methods for weighting observations based on their qualities are studied and proposed method can improve the accuracy of positioning more than 50%.
Journal ArticleDOI
Position Estimation in Single-Frequency GPS Receivers Using Kalman Filter with Pseudo-Range and Carrier Phase Measurements
TL;DR: The corporation of pseudo-range capability and carrier phase in single-frequency GPS receivers will be discussed which makes a substitute for the pure pseudo- range observations and provides a high level of positioning accuracy to achieve this aim.
Journal ArticleDOI
Robust Kalman filter-based least squares identification of a multivariable system
TL;DR: A novel direct identification using the residual model of Kalman filter is proposed for multiple-input and multiple-output Box–Jenkins model of the system formed of the signal and disturbance models using the remnant model relating the input and output without any a priori knowledge of the statistics of the disturbance and measurement noise corrupting the output.
Adaptive Kalman Filtering Methods for Low-Cost GPS/INS Localization for Autonomous Vehicles
Adam Werries,John M. Dolan +1 more
TL;DR: This work shows that by adapting Q based on the state-correction sequence and R based on GPS receiver-reported standard deviation, this filter reduces GPS root-mean-squared error by 23% in comparison to raw GPS, with 15% from only adapting R.
Journal ArticleDOI
A Cascaded Approach for Quadrotor's Attitude Estimation
TL;DR: In this paper, the authors used two extended Kalman filters (EKF) along with a Direction Cosine Matrix (DCM) algorithm to estimate the orientation of a quadrotor using single low-cost IMU sensor.
References
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