Robust fixed‐point Kalman smoother for bilinear state‐space systems with non‐Gaussian noise and parametric uncertainties
Xuehai Wang,
Yage Liu,
Sirui Zhao
Abstract:SummaryKalman smoother is an effective algorithm to estimate the state of the dynamic systems with Gaussian noise. However, when the system is affected by non‐Gaussian noise, the traditional Kalman smoother may suffer severe performance degradation, since it is derived from the minimum mean square error criterion. By introducing the maximum correntropy criterion, which accounts for all higher order moments and has the ability to resist non‐Gaussian noise, this article studies the state estimation problem of th… Show more
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