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arXiv · 1303.2395

State estimation under non-Gaussian Levy noise: A modified Kalman filtering method

Xu Sun·Jinqiao Duan·Xiaofan Li·Xiangjun Wang
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Abstract

The Kalman filter is extensively used for state estimation for linear systems under Gaussian noise. When non-Gaussian Lévy noise is present, the conventional Kalman filter may fail to be effective due to the fact that the non-Gaussian Lévy noise may have infinite variance. A modified Kalman filter for linear systems with non-Gaussian Lévy noise is devised. It works effectively with reasonable computational cost. Simulation results are presented to illustrate this non-Gaussian filtering method.

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Xu Sun, Jinqiao Duan, Xiaofan Li, Xiangjun Wang. 2013-03-10. State estimation under non-Gaussian Levy noise: A modified Kalman filtering method. https://arxiv.org/abs/1303.2395

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