| Title: | Density Approximation Error Assessment and Compensation in Point-Mass Filter |
| Authors: | Matoušek, Jakub Duník, Jindřich Straka, Ondřej Blasch, Erik |
| Citation: | MATOUŠEK, J. DUNÍK, J. STRAKA, O. BLASCH, E. Density Approximation Error Assessment and Compensation in Point-Mass Filter. In Proceedings of the 2022 IEEE 25th International Conference on Information Fusion (FUSION). Linköping, Sweden: IEEE, 2022. s. 1-7. ISBN: 978-1-73774-972-1 , ISSN: neuvedeno |
| Issue Date: | 2022 |
| Publisher: | IEEE |
| Document type: | konferenční příspěvek ConferenceObject |
| URI: | 2-s2.0-85136546546 http://hdl.handle.net/11025/51448 |
| ISBN: | 978-1-73774-972-1 |
| ISSN: | neuvedeno |
| Keywords in different language: | State estimation;Point-mass filter;Density approximation;Approximation error |
| Abstract in different language: | This paper deals with the state estimation of non-linear stochastic dynamic systems with an emphasis on a probability density function approximation used by point-mass filters. Approximation error of the standard point-mass density is analysed and quantified, and a novel point-mass density approximation with inherent approximation error minimisation is developed. The properties of the proposed point-mass are theoretically analysed and numerically illustrated. |
| Rights: | Plný text je přístupný v rámci univerzity přihlášeným uživatelům. © IEEE |
| Appears in Collections: | Konferenční příspěvky / Conference papers (NTIS) Konferenční příspěvky / Conference Papers (KKY) OBD |
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