A Robust Adaptive Unscented Kalman Filter for Nonlinear Estimation with Uncertain Noise Covariance

A Robust Adaptive Unscented Kalman Filter for Nonlinear Estimation with Uncertain Noise Covariance

The Unscented Kalman filter (UKF) may suffer from performance degradation and even divergence while mismatch between the noise distribution assumed as a priori by users and the actual ones in a real nonlinear system. To resolve this problem, this paper proposes a robust adaptive UKF (RAUKF) to impro...

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Bibliographic Details
Main Authors: Binqi Zheng, Pengcheng Fu, Baoqing Li, Xiaobing Yuan
Format: Article
Language:English
Published: MDPI AG 2018-03-01
Series:Sensors
Subjects:
Adaptive filter
data fusion
robust state estimation
nonlinear system
uncertain noise covariance
Online Access:http://www.mdpi.com/1424-8220/18/3/808

Internet

http://www.mdpi.com/1424-8220/18/3/808

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