一种不等式状态约束最优滤波算法

doi:10.3969/j.issn.1001-2400.2013.01.026

Abstract

Abstract:

According to state estimation for the nonlinear system with intractable inequality constraints, a novel constrained unscented kalman filter (CUKF) is proposed. The objective function is derived by using the maximum probability method, inequality constraints are treated skillfully as a penalty function, and the optimum constrained solution can be solved iteratively using the adaptively step length method. Through theoretical analyses, the constrained solution is the rigorous local minimizer of the objective function. A target tracking example based on digital navigation is presented to illustrate the efficacy of the CUKF. Simulation results show that the CUKF has a better filtering accuracy.

Key words: target tracking, inequality state constraints, unscented kalman filter (UKF), constrained unscented kalman filter (CUKF)

WU Xinhui;HUANG Gaoming;GAO Jun. Approach for optimal filtering of the nonlinear system with inequality constraints[J].J4, 2013, 40(1): 148-154.

References

［1］陈金广, 李洁, 高新波. 一种收缩非线性状态约束滤波算法［J］. 西安电子科技大学学报, 2011, 38(1): 104-109.
Chen Jinguang, Li Jie, Gao Xinbo. Iterative Shrinking Filtering Algorithm with Nonlinear State Constraints ［J］. Journal of Xidian University, 2011, 38(1): 104-109.
［2］ Julier S J, Uhlmann J K. A New Method for the Nonlinear Transformation of Means and Covariances in Filters and Estimators ［J］. IEEE Trans on Automatic Control, 2000, 45(3): 477-482.
［3］ Simon D. Kalman Filtering with State Constraints: a Survey of Linear and Nonlinear Algorithms ［J］. IET Control Theory and Applications, 2010, 4(8): 1303-1318.
［4］ Boulkroune B, Darouach M, Zasadzinski M. Moving Horizon State Estimation for Linear Discrete-time Singular Systems ［J］. IET Control Theory and Applications, 2010, 4(3): 339-350.
［5］ De Geeter J, Brussel H. A Smoothly Constrained Kalman Filter ［J］. IEEE Trans on Pattern Analysis and Machine Intelligence, 1997, 19(10): 1171-1177.
［6］ Simon D, Chia T L. Kalman Filtering with State Equality Constraints ［J］. IEEE Trans on Aerospace and Electronic Systems, 2002, 38(1): 128-136.
［7］ Vincent S, Ghaleb H, Houcine C. State Estimation under Nonlinear State Inequality Constraints: a Tracking Application ［C］//16th Mediterranean Conference on Control and Automation. France: IEEE, 2008: 1669-1674.
［8］ Bonnans J, Gilbert J. Numerical Optimization: Theoretical and Practical Aspects ［M］. New York: Springer, 2000: 51-65, 353-368.
［9］ Jiang Q, Geng G C. A Reduced-space Interior Point Method for Transient Stability Constrained Optimal Power Flow ［J］. IEEE Trans on Power Systems, 2010, 25(3): 1232-1240.
［10］ Simon D. Optimal State Estimation ［M］. New Jersey: Wiley Interscience. 2006: 212-224.

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Approach for optimal filtering of the nonlinear system with inequality constraints

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