Data fusion based on short-term memory Kalman filtering using intermittent-displacement and acceleration signal with a time-varying bias-Reference-Cited by-同舟云学术

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Data fusion based on short-term memory Kalman filtering using intermittent-displacement and acceleration signal with a time-varying bias

Published:2024-07 Issue: Volume:216 Page:111482
ISSN:0888-3270
Container-title:Mechanical Systems and Signal Processing
language:en
Short-container-title:Mechanical Systems and Signal Processing

Author:

Pal Ashish^ORCID,Nagarajaiah Satish^ORCID

Publisher

Elsevier BV

Reference56 articles.

1. Sparsity promoting algorithm for identification of nonlinear dynamic system based on unscented kalman filter using novel selective thresholding and penalty-based model selection;Pal;Mech. Syst. Signal Process.,2024

2. Displacement measurement and nonlinear structural system identification: a vision-based approach with camera motion correction using planar structures;Jiao;Struct. Control Health Monit.,2021

3. The unscented Kalman filter and particle filter methods for nonlinear structural system identification with non-collocated heterogeneous sensing;Chatzi;Struct. Control Health Monit.,2009

4. Reliability verification of a vision-based dynamic displacement measurement for system identification;Kim;J. Wind Eng. Ind. Aerodyn.,2019

5. A novel unscented Kalman filter for recursive state-input-system identification of nonlinear systems;Lei;Mech. Syst. Signal Process.,2019

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