Approximate Kalman filtering by both M-robustified dynamic stochastic approximation and statistical linearization methods

Approximate Kalman filtering by both M-robustified dynamic stochastic approximation and statistical linearization methods

Abstract The problem of designing a robustified Kalman filtering technique, insensitive to spiky observations, or outliers, contaminating the Gaussian observations has been presented in the paper. Firstly, a class of M-robustified dynamic stochastic approximation algorithms is derived by minimizing...

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Bibliographic Details
Main Authors: Miloš Pavlović, Zoran Banjac, Branko Kovačević
Format: Article
Language:English
Published: SpringerOpen 2023-06-01
Series:EURASIP Journal on Advances in Signal Processing
Subjects:
Impulsive noise
Kalman filtering
Non-Gaussian noise
Nonlinear filtering
Outliers
Robust estimation
Online Access:https://doi.org/10.1186/s13634-023-01030-1

Internet

https://doi.org/10.1186/s13634-023-01030-1

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