Journal ArticleDOI
Novel hybrid of strong tracking Kalman filter and wavelet neural network for GPS/INS during GPS outages
TLDR
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.About:
This article is published in Measurement.The article was published on 2013-12-01. It has received 116 citations till now. The article focuses on the topics: GPS/INS & Global Positioning System.read more
Citations
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Journal ArticleDOI
Dual-optimization for a MEMS-INS/GPS system during GPS outages based on the cubature Kalman filter and neural networks
TL;DR: The dual optimization process using different estimators provides better error compensation results than a single optimization method, which demonstrates that the proposed solution leads to the better performance of a MEMS-based INS/GPS navigation system.
Journal ArticleDOI
Seamless GPS/Inertial Navigation System Based on Self-Learning Square-Root Cubature Kalman Filter
TL;DR: The proposed SL-SRCKF strategy is a hybrid navigation strategy called the self-learning square-root- cubature Kalman filter that comprises two cycle filtering systems that work in a tightly coupled mode and allows more accurate error correction results to be obtained during GPS outages.
Journal ArticleDOI
A hybrid fusion algorithm for GPS/INS integration during GPS outages
TL;DR: A novel hybrid fusion algorithm is proposed to provide a pseudo position information to assist the integrated navigation system during GPS outages and achieves better performance in the prediction of GPS position information than the normal artificial neural network (ANN) trained by Bayesian Regularization.
Journal ArticleDOI
Improving positioning accuracy of vehicular navigation system during GPS outages utilizing ensemble learning algorithm
TL;DR: The ensemble learning algorithm (LSBoost or Bagging), similar to the neural network, can build the SINS/GPS position model based on current and some past samples of SINS velocity, attitude and IMU output information.
Journal ArticleDOI
Improved Cubature Kalman Filter for GNSS/INS Based on Transformation of Posterior Sigma-Points Error
TL;DR: A novel sigma-points update method is proposed to enhance the robustness of cubature Kalman filter (CKF) under the circumstance of unavailable observations and results demonstrate that ICKF outperforms state-of-the-art methods.
References
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Journal ArticleDOI
Strong tracking filtering of nonlinear time-varying stochastic systems with coloured noise: application to parameter estimation and empirical robustness analysis
D. H. Zhou,Paul M. Frank +1 more
TL;DR: In this paper, Zhou et al. extended the strong tracking filter (STF) for nonlinear systems with white noise to a class of nonlinear time-varying stochastic systems with coloured noise.
Journal ArticleDOI
GPS/INS integration utilizing dynamic neural networks for vehicular navigation
TL;DR: This study suggests the use of Input-Delayed Neural Networks (IDNN) to model both the INS position and velocity errors based on current and some past samples of INS location and velocity, respectively, which results in a more reliable positioning solution during long GPS outages.
Journal ArticleDOI
Study on Innovation Adaptive EKF for In-Flight Alignment of Airborne POS
Fang Jiancheng,Yang Sheng +1 more
TL;DR: In this paper, an adaptive filtering algorithm of an extended Kalman filter (EKF) combined with innovation-based adaptive estimation is proposed, which introduces the calculated innovation covariance into the computation of the filter gain matrix directly.
Journal ArticleDOI
Predictive Iterated Kalman Filter for INS/GPS Integration and Its Application to SAR Motion Compensation
Jiancheng Fang,Xiaolin Gong +1 more
TL;DR: Through flight tests, it is shown that the PIKF has an obvious accuracy advantage over the IEKF and unscented Kalman filter (UKF) in velocity.
Journal ArticleDOI
Bridging GPS outages using neural network estimates of INS position and velocity errors
TL;DR: This research presents an alternative method of bridging GPS outages requiring no prior knowledge of the INS and GPS sensor characteristics, called the artificial-intelligence-based segmented forward predictor, which uses radial basis function neural networks to predict INS position and velocity errors during GPSOutages, resulting in reliable performance.