| bibtype |
C -
Conference Paper (international conference)
|
| ARLID |
0559994 |
| utime |
20230316105347.4 |
| mtime |
20220815235959.9 |
| SCOPUS |
85131241649 |
| WOS |
000864187906010 |
| DOI |
10.1109/ICASSP43922.2022.9747607 |
| title
(primary) (eng) |
Point-Mass Filter with Decomposition of Transient Density |
| specification |
| page_count |
5 s. |
| media_type |
P |
|
| serial |
| ARLID |
cav_un_epca*0559993 |
| ISBN |
978-1-6654-0540-9 |
| title
|
2022 IEEE International Conference on Acoustics, Speech, and Signal Processing |
| page_num |
5752-5756 |
| publisher |
| place |
Singapore |
| name |
IEEE |
| year |
2022 |
|
|
| keyword |
State estimation |
| keyword |
nonlinear systems |
| keyword |
point-mass method |
| author
(primary) |
| ARLID |
cav_un_auth*0101212 |
| name1 |
Tichavský |
| name2 |
Petr |
| institution |
UTIA-B |
| full_dept (cz) |
Stochastická informatika |
| full_dept (eng) |
Department of Stochastic Informatics |
| department (cz) |
SI |
| department (eng) |
SI |
| full_dept |
Department of Stochastic Informatics |
| share |
50 |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| author
|
| ARLID |
cav_un_auth*0434606 |
| name1 |
Straka |
| name2 |
O. |
| country |
CZ |
| share |
40 |
|
| author
|
| ARLID |
cav_un_auth*0213309 |
| name1 |
Duník |
| name2 |
J. |
| country |
CZ |
| share |
10 |
|
| source |
|
| cas_special |
| project |
| project_id |
GA22-11101S |
| agency |
GA ČR |
| country |
CZ |
| ARLID |
cav_un_auth*0435406 |
|
| abstract
(eng) |
The paper deals with the state estimation of nonlinear stochastic dynamic systems with special attention on a grid-based numerical solution to the Bayesian recursive relations, the point-mass filter (PMF). In the paper, a novel functional decomposition of the transient density describing the system dynamics is proposed. The decomposition is based on a non-negative matrix factorization and separates the density into functions of the future and current states. Such decomposition facilitates a thrifty calculation of the convolution, which is a bottleneck of the PMF performance. The PMF estimate quality and computational costs can be efficiently controlled by choosing an appropriate rank of the decomposition. The performance of the PMF with the transient density decomposition is illustrated in a terrain-aided navigation scenario. |
| action |
| ARLID |
cav_un_auth*0434607 |
| name |
IEEE International Conference on Acoustics, Speech, and Signal Processing 2022 |
| dates |
20220522 |
| mrcbC20-s |
20220527 |
| place |
Singapur |
| country |
SG |
|
| RIV |
BB |
| FORD0 |
20000 |
| FORD1 |
20200 |
| FORD2 |
20205 |
| reportyear |
2023 |
| num_of_auth |
3 |
| presentation_type |
PR |
| inst_support |
RVO:67985556 |
| permalink |
https://hdl.handle.net/11104/0333427 |
| confidential |
S |
| mrcbC86 |
n.a. Proceedings Paper Acoustics|Computer Science Artificial Intelligence|Engineering Electrical Electronic |
| arlyear |
2022 |
| mrcbU14 |
85131241649 SCOPUS |
| mrcbU24 |
PUBMED |
| mrcbU34 |
000864187906010 WOS |
| mrcbU63 |
cav_un_epca*0559993 2022 IEEE International Conference on Acoustics, Speech, and Signal Processing IEEE 2022 Singapore 5752 5756 978-1-6654-0540-9 |
|