Particle filter algorithm based on geometric center and likelihood estimation-Reference-Cited by-同舟云学术

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Particle filter algorithm based on geometric center and likelihood estimation

Published:2021-08-01 Issue:8 Volume:11 Page:085206
ISSN:2158-3226
Container-title:AIP Advances
language:en
Short-container-title:AIP Advances

Author:

Fang Xing¹^ORCID,Luo Yin²³,Wang Lei²³,Jiang ShuiBin²³,Xu Nan²³,Zeng Daniel Dajun³⁴⁵

Affiliation:

1. School of Management and Economics, Tianjin University, Beijing, China

2. Wenge Technology Co., Ltd., Beijing, China

3. The State Key Laboratory of Management and Control for Complex System, Institute of Automation, Chinese Academy of Sciences, Beijing, China

4. University of Chinese Academy of Sciences, Beijing, China

5. Department of Management Information Systems, University of Arizona, Tucson, Arizona 85001, USA

Funder

The National Key R&D Program of China

The Key Research Program of the Chinese Academy of Sciences

The National Natural Science Foundation of China

Publisher

AIP Publishing

Subject

General Physics and Astronomy

Link

https://aip.scitation.org/doi/pdf/10.1063/5.0058367

Reference30 articles.

1. A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking

2. Efficient Particle Filtering via Sparse Kernel Density Estimation

3. A hybrid algorithm based on particle filter and genetic algorithm for target tracking

4. Indoor Positioning Integrating PDR/Geomagnetic Positioning Based on the Genetic-Particle Filter

5. Locating Smartphones Indoors Using Built-In Sensors and Wi-Fi Ranging With an Enhanced Particle Filter

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