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2018 | OriginalPaper | Chapter

3. Dynamic Bias Estimation with Gaussian Mean Shift Registration

Authors : Zhongliang Jing, Han Pan, Yuankai Li, Peng Dong

Published in: Non-Cooperative Target Tracking, Fusion and Control

Publisher: Springer International Publishing

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Abstract

In order to estimate multi-sensor dynamic bias, a Gaussian mean shift registration (GMSR) algorithm is proposed here. The sufficient condition of convergence of the Gaussian mean shift procedure is given. It extends the current theorem from a strictly convex kernel to a piece-wise convex and concave kernel. The Gaussian mean shift algorithm is implemented in the framework of the extended Kalman filter (EKF) to estimate the dynamic bias for a single target, which is an iterative optimization method. Besides, the proposed algorithm is close to the theoretical lower bound. Simulations show that the proposed method has significant improvement and is more efficient in estimating the dynamic bias than other methods.

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previous chapter Nonlinear Filter
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Metadata
Title
Dynamic Bias Estimation with Gaussian Mean Shift Registration
Authors
Zhongliang Jing
Han Pan
Yuankai Li
Peng Dong
Copyright Year
2018
Book
Non-Cooperative Target Tracking, Fusion and Control

Print ISBN: 978-3-319-90715-4

Electronic ISBN: 978-3-319-90716-1

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-3-319-90716-1_3

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