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| Title: | High-degree Cubature Quadrature Kalman Filter with Fractional Delayed Measurement |
| Authors: | Kumar, Guddu Saroj Ramabadran, Swaminathan Singh, Abhinoy Kumar |
| Keywords: | Gaussian distribution;And fractional delayed;Bayesian;Delayed measurements;Filter-based;Filtering algorithm;Filtering method;Gaussian filtering;Gaussian filters;Non-linear bayesian filtering;Quadrature Kalman filters;Kalman filters |
| Issue Date: | 2022 |
| Publisher: | Institute of Electrical and Electronics Engineers Inc. |
| Citation: | Kumar, G., Swaminathan, R., & Singh, A. K. (2022). High-degree cubature quadrature kalman filter with fractional delayed measurement. Paper presented at the INDICON 2022 - 2022 IEEE 19th India Council International Conference, doi:10.1109/INDICON56171.2022.10040169 Retrieved from www.scopus.com |
| Abstract: | Gaussian filtering is a popular Bayesian approximation filtering method for nonlinear systems. In general, the Gaussian filters are designed for non-delayed measurements however, the measurements are often delayed in practice. This paper considers that the delay is fractional multiple of sampling interval. Subsequently, it extends a significantly accurate filter, named higher degree cubature quadrature Kalman filter (HDCQKF), for handling the fractional delay problems. The simulation results conclude an improved accuracy of the HDCQKF-based delayed filtering algorithm in comparison to the popularly known cubature Kalman filter (CKF)-based delayed filtering algorithm. © 2022 IEEE. |
| URI: | https://doi.org/10.1109/INDICON56171.2022.10040169 https://dspace.iiti.ac.in/handle/123456789/11643 |
| Type of Material: | Conference Paper |
| Appears in Collections: | Department of Electrical Engineering |
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