Variational-Based Nonlinear Bayesian Filtering with Biased Observations

State estimation of dynamical systems is crucial for providing new decision-making and system automation information in different applications. However, the assumptions on the standard computational models for sensor measurements can be violated in practice due to different types of data abnormaliti...

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Veröffentlicht in:	IEEE transactions on signal processing 2022, Vol.70, p.1-13
Hauptverfasser:	Chughtai, Aamir Hussain, Majal, Arslan, Tahir, Muhammad, Uppal, Momin
Format:	Artikel
Sprache:	eng
Schlagworte:	Abnormalities Approximate Bayesian Inference Bias Bias Detection and Mitigation Decision making Detectors Dynamical systems Error detection IIR filters Kalman filters Measurement uncertainty Noise measurement Nonlinear systems Outliers (statistics) Parameter and State Estimation Robust Nonlinear Filtering Robustness State estimation State space models Variational Methods
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