Ship Tracking with Static Electric Field Based on Adaptive Progressive Update Extended Kalman Filter

Shouwei HU; Bing YAN

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Ship Tracking with Static Electric Field Based on Adaptive Progressive Update Extended Kalman Filter

机译：基于自适应渐进更新扩展卡尔曼滤波的静电场船舶跟踪

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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.

机译：引入了自适应渐进更新扩展卡尔曼滤波器，用于在使用静电电场的船舶跟踪中发现未知噪声。建立相应的状态空间模型;介绍了算法，并进行了仿真设计。仿真结果表明，当噪声协方差偏离实际值时，自适应算法可以有效提高算法的性能。有限数量的噪声协方差估计有利于滤波器的稳定性。

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《MATEC Web of Conferences》 |2018年第2016期|共4页
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Shouwei HU; Bing YAN;
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Ship Tracking with Static Electric Field Based on Adaptive Progressive Update Extended Kalman Filter

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