Pregled bibliografske jedinice broj: 887183
Mixture Reduction on Matrix Lie Groups
Mixture Reduction on Matrix Lie Groups // IEEE signal processing letters, 24 (2017), 11; 1719-1723 doi:10.1109/LSP.2017.2723765 (međunarodna recenzija, članak, znanstveni)
CROSBI ID: 887183 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Mixture Reduction on Matrix Lie Groups
Autori
Ćesić, Josip ; Marković, Ivan ; Petrović, Ivan
Izvornik
IEEE signal processing letters (1070-9908) 24
(2017), 11;
1719-1723
Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni
Ključne riječi
Mixture reduction ; estimation on matrix Lie groups ; multitarget tracking ; probability hypothesis density filter
Sažetak
Many physical systems evolve on matrix Lie groups and mixture filtering designed for such manifolds represent an inevitable tool for challenging estimation problems. However, mixture filtering faces the issue of a constantly growing number of components, hence require appropriate mixture reduction techniques. In this letter we propose a mixture reduction approach for distributions on matrix Lie groups, called the concentrated Gaussian distributions (CGDs). This entails appropriate reparametrization of CGD parameters to compute the KL divergence, pick and merge the mixture components. Furthermore, we also introduce a multitarget tracking filter on Lie groups as a mixture filtering study example for the proposed reduction method. In particular, we implemented the probability hypothesis density filter on matrix Lie groups. We validate the filter performance using the optimal subpattern assignment metric on a synthetic dataset consisting of 100 randomly generated multitarget scenarios.
Izvorni jezik
Engleski
Znanstvena područja
Elektrotehnika, Računarstvo, Temeljne tehničke znanosti
POVEZANOST RADA
Projekti:
EK-H2020-688117 - Sigurna interakcija ljudi i robota u logističkim primjenama za visoko fleksibilna skladišta (SafeLog) (Petrović, Ivan, EK ) ( CroRIS)
Ustanove:
Fakultet elektrotehnike i računarstva, Zagreb
Citiraj ovu publikaciju:
Časopis indeksira:
- Current Contents Connect (CCC)
- Web of Science Core Collection (WoSCC)
- Science Citation Index Expanded (SCI-EXP)
- SCI-EXP, SSCI i/ili A&HCI
- Scopus