Robust Algorithms for on Minor-Free Graphs Based on the Sherali-Adams Hierarchy

Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques - Lecture Notes in Computer Science ◽

10.1007/978-3-642-03685-9_20 ◽

2009 ◽

pp. 258-271 ◽

Cited By ~ 9

Author(s):

Avner Magen ◽

Mohammad Moharrami

Keyword(s):

Robust Algorithms ◽

Minor Free Graphs

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Robust algorithms for relative orientation

Acta Geodaetica et Geophysica Hungarica ◽

10.1556/ageod.36.2001.1.4 ◽

2001 ◽

Vol 36 (1) ◽

pp. 35-38 ◽

Cited By ~ 1

Author(s):

Judit Somogyi ◽

L. Battha

Keyword(s):

Relative Orientation ◽

Robust Algorithms

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Development and Analysis of Robust Algorithms for Guaranteed Ellipsoidal Estimation of a State of Multidimensional Linear

Journal of Automation and Information Sciences ◽

10.1615/jautomatinfscien.v32.i11.20 ◽

2000 ◽

Vol 32 (11) ◽

pp. 13-23

Author(s):

Victor V. Volosov ◽

Lidiya I. Tyutyunnik

Keyword(s):

Robust Algorithms ◽

Multidimensional Linear

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Centered error entropy Kalman filter with application to satellite attitude determination

Transactions of the Institute of Measurement and Control ◽

10.1177/01423312211019867 ◽

2021 ◽

pp. 014233122110198

Author(s):

Baojian Yang ◽

Lu Cao ◽

Dechao Ran ◽

Bing Xiao

Keyword(s):

Kalman Filter ◽

Gaussian Noise ◽

Attitude Determination ◽

Complexity Analysis ◽

Iteration Algorithm ◽

Robust Algorithms ◽

Convergence Conditions ◽

Satellite Attitude ◽

Heavy Tailed ◽

Non Gaussian

Due to unavoidable factors, heavy-tailed noise appears in satellite attitude estimation. Traditional Kalman filter is prone to performance degradation and even filtering divergence when facing non-Gaussian noise. The existing robust algorithms have limited accuracy. To improve the attitude determination accuracy under non-Gaussian noise, we use the centered error entropy (CEE) criterion to derive a new filter named centered error entropy Kalman filter (CEEKF). CEEKF is formed by maximizing the CEE cost function. In the CEEKF algorithm, the prior state values are transmitted the same as the classical Kalman filter, and the posterior states are calculated by the fixed-point iteration method. The CEE EKF (CEE-EKF) algorithm is also derived to improve filtering accuracy in the case of the nonlinear system. We also give the convergence conditions of the iteration algorithm and the computational complexity analysis of CEEKF. The results of the two simulation examples validate the robustness of the algorithm we presented.

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