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The unscented particle filter

Abstract:

In this paper, we propose a new particle filter based on sequential importance sampling. The algorithm uses a bank of unscented filters to obtain the importance proposal distribution. This proposal has two very "nice" properties. Firstly, it makes efficient use of the latest available information and, secondly, it can have heavy tails. As a result, we find that the algorithm outperforms standard particle filtering and other nonlinear filtering methods very substantially. This experimental fin...

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Authors


Van Der Merwe, R More by this author
De Freitas, N More by this author
Publisher:
Neural information processing systems foundation
Publication date:
2001
ISSN:
1049-5258
URN:
uuid:a78bd23c-b83c-40b1-adb3-aab6aa479ee9
Source identifiers:
464333
Local pid:
pubs:464333
ISBN-10:
0262122413
ISBN-13:
9780262122412

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