A Survey of Kalman Filter Algorithms and Variants in State Estimation

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A Survey of Kalman Filter Algorithms and Variants in State Estimation

September 2, 2021 Science and Technology 0

In the areas of modem control, communication applications, and signal processing, the Kalman filter is one of the most often used algorithms for estimating system states given unknown statistics. A correct and accurate state estimation of a linear or non-linear system can be improved by using the suitable estimate technique. To linearize the data, numerous mathematical techniques were used. The state estimation of a nonlinear system can be improved. Kalman filter methods offer linear, unbiased, and least variance estimates of unknown state vectors and are a common tool for nonlinear systems. In this study, we aimed to bridge the algorithmic and performance gap between the Kalman filter and its variants when applied to a non-linear system. When you only have When there is a lot of noisy observation data, the strategies discussed here have been proved to be more effective. This work can serve as a theoretical foundation for future research in a variety of areas, such as achieving high computing performance for high-dimensional state estimation.

Author (S) Details

Vishal Awasthi
Department of Electronics & Communication Engineering, University Institute of Engineering & Technology, CSJM University Kanpur, Uttar Pradesh, India.

Krishna Raj
Department of Electronics Engineering, HBTI, Kanpur, Uttar Pradesh, India.

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