On the bias of the SIR filter in parameter estimation of the dynamics process of state space models

Tiancheng Li, Sara Rodríguez, Javier Bajo, Juan M. Corchado, Shudong Sun

科研成果: 书/报告/会议事项章节会议稿件同行评审

3 引用 (Scopus)

摘要

As a popular nonlinear estimation tool, the sampling importance resampling (SIR) filter has been applied with the expectation-maximization (EM) principle, including the typical maximum a posteriori (MAP) estimation and maximum likelihood (ML) estimation, for estimating the parameters of the state space model (SSM). This paper concentrates on an inevitable bias existing in the EM-SIR filter for estimating the dynamics process of the SSM. It is analyzed that the root reason for the bias is the sample impoverishment caused by the resampling procedure employed in the filter. A process noise simulated for the particle propagation that is larger than the real noise involved with the true state will be helpful to counteract sample impoverishment, thereby providing better filtering result. Correspondingly, the EM-SIR filter tends to yield a biased (larger-than-the-truth) estimate of the process noise if it is unknown and needs to be estimated. The bias is elaborated via a straightforward roughening approach by means of both qualitative logical deduction and quantitative numerical simulation. However, it seems hard to fully remove this bias in practice.

源语言英语
主期刊名Distributed Computing and Artificial Intelligence, 12th International Conference, DCAI 2015
编辑Sigeru Omatu, Qutaibah M. Malluhi, Grzegorz Bocewicz, Sara Rodríguez González, Edgardo Bucciarelli, Gianfranco Giulioni, Farkhund Iqba
出版商Springer Verlag
87-95
页数9
ISBN(电子版)9783319196374
DOI
出版状态已出版 - 2015
活动12th International Symposium on Distributed Computing and Artificial Intelligence, DCAI 2015 - Salamanca, 西班牙
期限: 3 6月 20155 6月 2015

出版系列

姓名Advances in Intelligent Systems and Computing
373
ISSN(印刷版)2194-5357

会议

会议12th International Symposium on Distributed Computing and Artificial Intelligence, DCAI 2015
国家/地区西班牙
Salamanca
时期3/06/155/06/15

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