大连海事大学学报 >
2016 , Vol. 42 >Issue 4: 7 - 12
DOI: https://doi.org/10.16411/j.cnki.issn1006-7736.2016.04.002
基于自适应无迹卡尔曼滤波的动力定位状态估计
收稿日期: 2016-03-07
修回日期: 2016-05-27
网络出版日期: 2016-05-27
基金资助
国家自然科学基金资助项目(61301279；51479158).
Attitude estimation of dynamic positioning system based on adaptive unscented Kalman filter
Received date: 2016-03-07
Revised date: 2016-05-27
Online published: 2016-05-27
针对复杂海洋情况下由模型的不准确导致的过程噪声变化使得无迹卡尔曼滤波估计精度下降的问题，提出一种自适应无迹卡尔曼滤波方法.该方法根据一段时间内观测值与后验估计值的偏差，自适应估计出当前时刻的过程噪声.仿真结果表明：当过程噪声发生变化时，自适应无迹卡尔曼滤波可以较为准确估计出变化的过程噪声，提高状态估计的准确性，使滤波结果更加准确.
关键词： 动力定位; 自适应无迹卡尔曼滤波; 过程噪声
丁浩晗 , 冯辉 , 徐海祥 . 基于自适应无迹卡尔曼滤波的动力定位状态估计[J]. 大连海事大学学报, 2016 , 42(4) : 7 -12 . DOI: 10.16411/j.cnki.issn1006-7736.2016.04.002
To solve the estimate accuracy decreasing problem of the conventional unscented Kalman filter caused by diverges of process noise owing to system uncertainty in complex ocean occasion, an adaptive unscented Kalman filter method was proposed, which can adaptively estimate the process noise of current moment based on deviation values between observed values and posteriori estimates values during a period. Numerical simulation results show that the adaptive unscented Kalman filter can accurately estimate the process noise when the process noise changes, which can increase the state estimate accuracy, and improve the filter result.
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