Entity

Time filter

Source Type


Chang G.,Tianjin Institute of Hydrographic Surveying and Charting
Automatica | Year: 2014

This note points out that the framework proposed in (Wang et al.; 2012) is equivalent to the conventional de-coupling framework introduced in some textbooks; see e.g. (Bar-Shalom et al.; 2001). © 2013 Elsevier Ltd. All rights reserved.


Chang L.,Wuhan Naval University of Engineering | Hu B.,Wuhan Naval University of Engineering | Chang G.,Tianjin Institute of Hydrographic Surveying and Charting | Li A.,Wuhan Naval University of Engineering
IET Science, Measurement and Technology | Year: 2012

This study concerns the unscented Kalman filter (UKF) for the non-linear dynamic systems with error statistics following non-Gaussian probability distributions. A novel robust unscented Kalman filter (NRUKF) is proposed. In the NRUKF the measurement information (measurements or measurements noise) is reformulated using Huber cost function, then the standard unscented transformation (UT) is applied to exact non-linear measurement equation. Compared with the conventional Huber-based unscented Kalman filter (HUKF) which is derived by applying the Huber technique to modify the measurement update equations of the standard UKF, the NRUKF, without linear (statistical linear) approximation, has much-improved performance and versatility with maintaining the robustness. Then the NRUKF is applied to the target tracking problem. The validity of the algorithm is demonstrated through numerical simulation study. © 2012 The Institution of Engineering and Technology.


Chang G.,Tianjin Institute of Hydrographic Surveying and Charting
Journal of Process Control | Year: 2014

Adaptive and robust methods are two opposite strategies to be adopted in the Kalman filter when the difference between the predictive observation and the actual observation, i.e. the innovation vector is abnormally large. The actual observation is more weighted in the former one, and is less weighted in the later one. This article addresses the subject of making a choice between the adaptive and robust methods when abnormal innovation occurs. An adaptive method with fading memory and a robust method with enhancing memory is proposed in the Kalman filter based on the chi-square distribution of the square of the Mahalanobis distance of the innovation. A heuristic method of recursively choosing among the adaptive, the robust, and the standard Kalman filter approaches in the occurrence of abnormal innovations is proposed through incorporating the observations at the next instance. The proposed method is both adaptive and robust, i.e. having the ability of strongly tracking the variation of the state and being insensitive to gross errors in observation. Numerical simulations of a simple illustrating example validate the efficacy of the proposed method. © 2014 Elsevier Ltd. All rights reserved.


Chang L.,Wuhan Naval University of Engineering | Hu B.,Wuhan Naval University of Engineering | Chang G.,Wuhan Naval University of Engineering | Chang G.,Tianjin Institute of Hydrographic Surveying and Charting | Li A.,Wuhan Naval University of Engineering
Journal of Guidance, Control, and Dynamics | Year: 2012

A robust derivative-free algorithm named outliers robust unscented Kalman filter (ORUKF) is proposed to handle both the state and measurement outliers. Based on the generalized maximum likelihood perspective on the Kalman filter, the state is first augmented with the measurement noise, then the covariance of the augmented state is reformulated by the M estimate methodology and embedded into a modified version of the iterated unscented Kalman filter (UKF) to detect and suppress the outliers. Attractive features of the novel robust derivative-free algorithm include ability to handle multiple outliers, ability to exhibit the accuracy and flexibility of the UKF for the nonlinear problems, and high statistical efficiency under nominal conditions and flexibility to encompass maximum likelihood estimate.


Chang L.,Wuhan Naval University of Engineering | Hu B.,Wuhan Naval University of Engineering | Chang G.,Tianjin Institute of Hydrographic Surveying and Charting
Journal of Guidance, Control, and Dynamics | Year: 2014

The USQUE has been approved to be very attractive for the attitude estimation and has been extended to the integrated GPS and inertial navigation application. Actually, the USQUE can be used in any applications with quaternion such as the in-motion alignment. To calculate the propagated sigma points of the GRP in the USQUE the propagated sigma points of the error quaternion should be first determined, which is achieved by multiplying the propagated sigma points of the quaternion with a reference quaternion. In the USQUE the propagated sigma point of the quaternion in the center is selected as the reference quaternion. The intrinsic-gradient descent algorithm uses the fact that quaternion algebra provides a unique definition of the distance between two attitudes. The intrinsic-gradient-descent algorithm is an iterative method, and the number of iterations is usually very small.

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