Linear minimum mean squared estimation of measurement bias driven by structured unknown inputs-Reference-Cited by-同舟云学术

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Linear minimum mean squared estimation of measurement bias driven by structured unknown inputs

Published:2014-10 Issue:8 Volume:8 Page:977-986
ISSN:1751-8792
Container-title:IET Radar, Sonar & Navigation
language:en
Short-container-title:IET Radar, Sonar & Navigation

Author:

Zhou Lin¹²,Liang Yan¹³,Zhou Jie¹³,Yang Feng¹³,Pan Quan¹³

Affiliation:

1. School of AutomationNorthwestern Polytechnical UniversityPeople's Republic of China

2. School of Computer and Information EngineeringHenan UniversityKaifengPeople's Republic of China

3. Key Laboratory of Information Fusion Technology, Ministry of EducationXi'anPeople's Republic of China

Publisher

Institution of Engineering and Technology (IET)

Subject

Electrical and Electronic Engineering

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/iet-rsn.2013.0311

Reference22 articles.

1. Approaches to adaptive filtering

2. Adaptive sequential estimation with unknown noise statistics

3. A finite-horizon adaptive Kalman filter for linear systems with unknown disturbances

4. Estimation of time-varying time delay and parameters of a class of jump Markov nonlinear stochastic systems

5. Adaptive Filtering for Stochastic Systems With Generalized Disturbance Inputs

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4. Optimal joint estimation and identification theorem to linear Gaussian system with unknown inputs;Signal Processing;2019-08

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