Cargando…
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...
Autores principales: | Zheng, Binqi, Fu, Pengcheng, Li, Baoqing, Yuan, Xiaobing |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5876731/ https://www.ncbi.nlm.nih.gov/pubmed/29518960 http://dx.doi.org/10.3390/s18030808 |
Ejemplares similares
-
Adaptive Unscented Kalman Filter for Target Tracking with Unknown Time-Varying Noise Covariance
por: Ge, Baoshuang, et al.
Publicado: (2019) -
Quaternion-Based Robust Attitude Estimation Using an Adaptive Unscented Kalman Filter
por: Chiella, Antônio C. B., et al.
Publicado: (2019) -
Adaptive Robust Unscented Kalman Filter for AUV Acoustic Navigation
por: Wang, Junting, et al.
Publicado: (2019) -
Adaptive Unscented Kalman Filter for Target Tacking with Time-Varying Noise Covariance Based on Multi-Sensor Information Fusion
por: Wang, Dapeng, et al.
Publicado: (2021) -
Maximum Correntropy Unscented Kalman Filter for Spacecraft Relative State Estimation
por: Liu, Xi, et al.
Publicado: (2016)