| Issue |
MATEC Web Conf.
Volume 232, 2018
2018 2nd International Conference on Electronic Information Technology and Computer Engineering (EITCE 2018)
|
|
|---|---|---|
| Article Number | 04063 | |
| Number of page(s) | 4 | |
| Section | Circuit Simulation, Electric Modules and Displacement Sensor | |
| DOI | https://doi.org/10.1051/matecconf/201823204063 | |
| Published online | 19 November 2018 | |
Ship Tracking with Static Electric Field Based on Adaptive Progressive Update Extended Kalman Filter
1
Science and Technology on Near-Surface Detection Laboratory, Wuxi, Jiangsu 214035, China
2
College of Weapon Engineering, Naval University of Engineering, Wuhan, Hubei 430033, China
a Corresponding author: bingyan_wh@163.com
An adaptive progressive update extended Kalman filter is introduced for unknown noise in ship tracking using static electric field. The corresponding state space model is established; the algorithm is introduced, and the simulation is designed. The simulation results show that the adaptive algorithm can effectively improve the performance of the algorithm, when the noise covariance deviates from the real value; the finite number of noise covariance estimation is beneficial to the stability of the filter.
© The Authors, published by EDP Sciences, 2018
This is an open access article distributed under the terms of the Creative Commons Attribution License 4.0 (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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