| Title: | Conditional Density Driven Grid Design in Point-Mass Filter |
| Authors: | Duník, Jindřich Straka, Ondřej Matoušek, Jakub |
| Citation: | DUNÍK, J.., STRAKA, O.., MATOUŠEK, J.. Conditional Density Driven Grid Design in Point-Mass Filter. In Proceedings of the 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). Barcelona: IEEE, 2020. s. 9180-9184. ISBN: 978-1-5090-6631-5 , ISSN: 1520-6149 |
| Issue Date: | 2020 |
| Publisher: | IEEE |
| Document type: | konferenční příspěvek conferenceObject |
| URI: | 2-s2.0-85089239619 http://hdl.handle.net/11025/42245 |
| ISBN: | 978-1-5090-6631-5 |
| ISSN: | 1520-6149 |
| Keywords in different language: | state estimation, filtering, nonlinear sys-tems, point-mass method |
| Abstract: | Článek je věnován odhadu stavu stochastických dynamických systémů. Důraz je v článku kladen zejména na metodu bodových mas, pro kterou je navržen nový design mřížky respektující tvar podmíněné hustoty. Výsledná mřížka je tak v určitých částech stavového prostoru hustší. Nově navržený design mřížky je validován v numerické simulaci inspirované terénní navigací. |
| Abstract in different language: | The paper is devoted to the state estimation of nonlinear stochastic dynamic systems. The stress is laid on a grid-based numerical solution to the Bayesian recursive relations using the point-mass filter (PMF). In the paper, a novel conditional density driven grid (CDDG) design is proposed. The CDDG design takes advantage of non-equidistant grid points by combination of two grids; dense and sparse. The dense grid is designed to cover the state space region, where the significant mass of one or both conditional (i.e., predictive and filtering) densities is anticipated. The sparse grid covers the support of the conditional distribution tails only. As a consequence, the CDDG design improves the point-mass approximation of the conditional densities and offers better estimation performance compared to the standard equidistant grid with the same number of points and, thus, with the same computational complexity. Performance of the CDDG-based PMF is illustrated in a terrain-aided navigation scenario. |
| Rights: | Plný text je přístupný v rámci univerzity přihlášeným uživatelům. © IEEE |
| Appears in Collections: | Konferenční příspěvky / Conference Papers (KKY) Konferenční příspěvky / Conference papers (NTIS) OBD |
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