Results 241 to 250 of about 321,013 (282)

An Improved Strong Tracking Filter

2011
This paper describes an improved strong tracking filter(ISTF). In this improved algorithm, it ensures the symmetry of forecast error covariance. In addition, an equation of the time-varying fading factor is derived from the orthogonality principle conditions of strong tracking filter.
Wu Wei, Wu Aidi
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Improved strong tracking particle filter

2019 IEEE 3rd Advanced Information Management, Communicates, Electronic and Automation Control Conference (IMCEC), 2019
Aiming at the estimation of the higher nonlinear dynamic system which contains both saltatory states and the condition of likelihood function locating at the tail end of state space, this paper proposes improved strong tracking particle filter(ISTPF) method.
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Target passive tracking based on Strong Tracking Filter

2010 3rd International Conference on Computer Science and Information Technology, 2010
We put forward Adaptive PLE (APLE) based on Strong Tracking Filter (STF) for bearing and frequency measure in order to rectify the bias of PLE. Furthermore, the APLE avoids filter divergence in that it is not necessary to linearize non-linear measure equation.
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A strong tracking particle filter for state estimation

2011 Seventh International Conference on Natural Computation, 2011
One of the algorithmic cores of particle filter (PF) is the proposal distribution. A new proposal distribution combining the unscented Kalman filter (UKF) with strong tracking filter (STF) is presented. The scaling factor is added and is acquired by the techniques in the STF. It can be tuned to make the algorithm reliable and adaptive. In the nonlinear
Xiaolong Deng, JinJun Lu, Rui Yue, null Jianlin Zhang   +3 more
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Strong tracking filter based adaptive generic model control

Journal of Process Control, 1999
Abstract Generic Model Control (GMC) is a control algorithm capable of using nonlinear process model directly. Parameters in GMC controllers are easily tuned, and measurable disturbances can be compensated effectively. However, the existence of large modeling errors and unmeasurable disturbances will make the performance of GMC deteriorate.
X.Q. Xie, D.H. Zhou, Y.H. Jin
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Strong Tracking Tobit Kalman Filter with Model Uncertainties

International Journal of Control, Automation and Systems, 2019
The Tobit Kalman filter (TKF) is a good choice for applications of discrete time-varying systems with censored measurements. The traditional TKF is usually designed under the assumption of exactly knowing system state and measurement functions, which can not guarantee the good performance and is even unsuitable for system with model mismatch. To ensure
Zhan-long Du, Xiao-min Li
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Adaptive gas path diagnostics using strong tracking filter

Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering, 2013
Kalman filters are very popular in gas path diagnostics. This algorithm estimates the engine state variables to assess engine health conditions and is accurate in tracking gradual deterioration. However, the performance of the Kalman filter deteriorates when an abrupt fault occurs.
Xingxing Pu, Shangming Liu, Hongde Jiang, Daren Yu   +3 more
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Strong Tracking Filter Simultaneous Localization and Mapping Algorithm

2008 International Conference on Computer Science and Software Engineering, 2008
Simultaneous localization and mapping (SLAM) is a central and complex problem in robot research community. In SLAM, extended Kalman filter (EKF) implementation is widely used to localize the robot and build the environment map incrementally. In this paper, we propose a strong tracking filter (STF) SLAM algorithm. This algorithm applies STF to deal with
Huiping Li, Demin Xu, Yao Yao, Fubin Zhang   +3 more
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Cubature Kalman Filter Based on Strong Tracking

2015
To improve the ability of dealing with inaccurate of model and statistic characteristics of noise, as well as the abrupt change of state of cubature Kalman filter (CKF), a new nonlinear filter, called Cubature Kalman Filter based on strong tracking (CKF-ST), is proposed in this paper.
Zhang Cun, Zhao Meng, Yu Xue-Lian, Cui Ming-Lei, Zhou Yun, Wang Xue-Gang   +5 more
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Chaotic secure communication based on strong tracking filtering

Physics Letters A, 2008
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Li, Xiongjie, Xu, Zhengguo, Zhou, Donghua   +2 more
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