基于扩展卡尔曼滤波器的AUV导航定位数据融合

Data Fusion for AUV Navigation and Positioning Based on Extended Kalman Filter

中文关键词:  AUV  扩展卡尔曼滤波器  数据融合  滤波发散  机动目标跟踪模型

英文关键词:AUV(autonomous uderwater vehicle)  extended Kalman filter  data fusion  filtering divergence  maneuvering goal tracking model

中文摘要:

      导航定位是AUV（自主式水下潜器）自动化受限的关键技术。GPS等单独的定位方式又存在缺陷。故采用低成本罗经-DVL-GPS组合导航定位。因为导航定位观测的非线性关系，设计了基于扩展卡尔曼滤波器的导航定位数据融合算法。针对扩展卡尔曼滤波器存在的滤波发散现象，引入机动目标模型抑制滤波发散，研究并仿真了AUV的两种运动方式，实现了覆盖四个象限运动的导航定位仿真，结果表明算法能有效进行数据融合，提高状态估计精确度。

英文摘要:

      Navigation and positioning is the key limit factor for AUV(autonomous uderwater vehicle) automation.Positioning means like GPS ect.have weakness.So cheap compass-DVL(Doppler velocity log)-GPS integrated navigation and positioning is used.Because of the mlinear measurement relationship of navigation and positioning,extended Kalman filter based navigation and positioning data fusion algorithm is designed.Aimming at the phenomenon of extended Kalman filters divergence,two motion states are researched and simulated,and maneuvering goal model is introduced to prevent filtering divergence,navigation and positioning simulation which covers four quadrants is implemented,the result indicates algrithom is capable of effective data fusion,accuracy and precision in the state estimates are improved.