Smoothing joint integrated probabilistic data association | Zendy

Kim Tae Han | Zendy; Mušicki Darko | Zendy; Song Taek Lyul | Zendy; Lee Chul Mok | Zendy

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Smoothing joint integrated probabilistic data association

Author(s) -

Kim Tae Han,

Mušicki Darko,

Song Taek Lyul,

Lee Chul Mok

Publication year - 2015

Publication title -

iet radar, sonar and navigation

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.489

H-Index - 82

eISSN - 1751-8792

pISSN - 1751-8784

DOI - 10.1049/iet-rsn.2013.0347

Subject(s) - smoothing , probabilistic logic , joint (building) , association (psychology) , computer science , data association , data mining , association rule learning , artificial intelligence , psychology , engineering , computer vision , architectural engineering , psychotherapist

The authors extend the smoothing integrated probabilistic data association algorithm to multi‐target tracking in clutter, or alternatively, use smoothing to improve the joint integrated probabilistic data association (JIPDA) algorithm. The predictions of forward and backward JIPDA are fused to form the smoothing prediction, which is used for smoothing multi‐target data association.

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