Particle Filters Revisited*

Torben Knudsen; John-Josef Leth

doi:10.1109/ANZCC50923.2020.9318384

Particle Filters Revisited*

Publikation: Bidrag til bog/antologi/rapport/konference proceeding › Konferenceartikel i proceeding › Forskning › peer review

1 Citationer (Scopus)

Abstract

Particle filters are often explained by either heuristics arguments or complex mathematics. Present day particle filters rely on various methods such as importance sampling, resampling method and resampling strategy. Moreover, there are different derivations for discrete and continuous time dynamic models. In this paper we offer a new simple derivation which works both in the discrete and continuous case, and which avoid importance sampling and resampling. The resulting algorithm has a performance as good as the standard MATLAB particle filter.

Originalsprog	Engelsk
Titel	2020 Australian and New Zealand Control Conference (ANZCC)
Antal sider	6
Forlag	IEEE
Publikationsdato	2020
Sider	36-41
Artikelnummer	9318384
ISBN (Trykt)	978-1-7281-9993-1
ISBN (Elektronisk)	978-1-7281-9992-4
DOI	https://doi.org/10.1109/ANZCC50923.2020.9318384
Status	Udgivet - 2020
Begivenhed	2020 Australian and New Zealand Control Conference (ANZCC) - Gold Coast, Australien Varighed: 26 nov. 2020 → 27 nov. 2020

Konference

Konference	2020 Australian and New Zealand Control Conference (ANZCC)
Land/Område	Australien
By	Gold Coast
Periode	26/11/2020 → 27/11/2020

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title = "Particle Filters Revisited*",

abstract = "Particle filters are often explained by either heuristics arguments or complex mathematics. Present day particle filters rely on various methods such as importance sampling, resampling method and resampling strategy. Moreover, there are different derivations for discrete and continuous time dynamic models. In this paper we offer a new simple derivation which works both in the discrete and continuous case, and which avoid importance sampling and resampling. The resulting algorithm has a performance as good as the standard MATLAB particle filter.",

author = "Torben Knudsen and John-Josef Leth",

year = "2020",

doi = "10.1109/ANZCC50923.2020.9318384",

language = "English",

isbn = "978-1-7281-9993-1",

pages = "36--41",

booktitle = "2020 Australian and New Zealand Control Conference (ANZCC)",

publisher = "IEEE",

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note = "2020 Australian and New Zealand Control Conference (ANZCC) ; Conference date: 26-11-2020 Through 27-11-2020",

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T1 - Particle Filters Revisited*

AU - Knudsen, Torben

AU - Leth, John-Josef

PY - 2020

Y1 - 2020

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AB - Particle filters are often explained by either heuristics arguments or complex mathematics. Present day particle filters rely on various methods such as importance sampling, resampling method and resampling strategy. Moreover, there are different derivations for discrete and continuous time dynamic models. In this paper we offer a new simple derivation which works both in the discrete and continuous case, and which avoid importance sampling and resampling. The resulting algorithm has a performance as good as the standard MATLAB particle filter.

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U2 - 10.1109/ANZCC50923.2020.9318384

DO - 10.1109/ANZCC50923.2020.9318384

M3 - Article in proceeding

SN - 978-1-7281-9993-1

SP - 36

EP - 41

BT - 2020 Australian and New Zealand Control Conference (ANZCC)

PB - IEEE

T2 - 2020 Australian and New Zealand Control Conference (ANZCC)

Y2 - 26 November 2020 through 27 November 2020

ER -

Particle Filters Revisited*

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