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Pourasad, Y., Vahidpour, V., Rastegarnia, A., Ghorbanzadeh, P. and Sanei, S. 
ORCID: 0000-0002-3437-2801,
2021.
State estimation in linear dynamical systems by partial update Kalman filtering.
Circuits, Systems, and Signal Processing.
ISSN 0278-081X
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Abstract
In this letter, we develop a partial update Kalman filtering (PUKF) algorithm to solve the state of a discrete-time linear stochastic dynamical system. In the proposed algorithm, only a subset of the state vector is updated at every iteration, which reduces its computational complexity, compared to the original KF algorithm. The required conditions for the stability of the algorithm are discussed. A closed-form expression for steady-state mean-square deviation is also derived. Numerical examples are used to validate the correctness of the provided analysis. They also reveal the PUKF algorithm exhibits a trade-off between the estimation accuracy and the computational load which is extremely profitable in practical applications.
| Item Type: | Journal article | ||||||
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| Publication Title: | Circuits, Systems, and Signal Processing | ||||||
| Creators: | Pourasad, Y., Vahidpour, V., Rastegarnia, A., Ghorbanzadeh, P. and Sanei, S. | ||||||
| Publisher: | Springer Science and Business Media LLC | ||||||
| Date: | 16 August 2021 | ||||||
| ISSN: | 0278-081X | ||||||
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| Divisions: | Schools > School of Science and Technology | ||||||
| Record created by: | Laura Ward | ||||||
| Date Added: | 31 Aug 2021 09:15 | ||||||
| Last Modified: | 16 Aug 2022 03:00 | ||||||
| URI: | https://irep.ntu.ac.uk/id/eprint/44091 |
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