Target tracking algorithm based on adaptive strong tracking particle filter-Reference-Cited by-同舟云学术

Target tracking algorithm based on adaptive strong tracking particle filter

Published:2016-10 Issue:7 Volume:10 Page:704-710
ISSN:1751-8830
Container-title:IET Science, Measurement & Technology
language:en
Short-container-title:IET Science, Measurement & Technology

Author:

Jia‐qiang Li¹,Rong‐hua Zhao²,Jin‐li Chen¹³,Chun‐yan Zhao²,Yan‐ping Zhu³

Affiliation:

1. Collaborative Innovation Center on Forecast and Evaluation of Meteorological DisastersNanjing University of Information Science and TechnologyNanjing210044People's Republic of China

2. School of Electronic and Information EngineeringNanjing University of Information Science and TechnologyNanjing210044People's Republic of China

3. Jiangsu Key Laboratory of Meteorological Observation and Information ProcessingNanjing210044People's Republic of China

Funder

National Natural Science Foundation of China

Publisher

Institution of Engineering and Technology (IET)

Subject

Electrical and Electronic Engineering,Atomic and Molecular Physics, and Optics

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/iet-smt.2016.0044

Reference26 articles.

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3. Two‐dimensional dissipative control and filtering for Roesser model;Choon K.;IEEE Trans. Autom. Control,2015

4. Modified Kalman Filters for Channel Estimation in Orthogonal Space-Time Coded Systems

5. Kalman filter‐based distributed predictive control of large‐scale multi‐rate system: application to power networks;Roshany‐Yamchi S.;IEEE Trans. Control Syst. Technol.,2013

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