基于模糊自适应UKF的船舶动力定位多传感器融合(英文)  

Vessel Dynamic Positioning Multi-sensor Fusion Based on Fuzzy Adaptive Unscented Kalman Filter

作　　者：徐树生[1] 李娟[1] 

机构地区：[1]青岛农业大学机电工程学院,山东青岛266109

出　　处：《山东科技大学学报（自然科学版）》2017年第5期7-15,共9页Journal of Shandong University of Science and Technology(Natural Science)

基　　金：国家自然科学基金项目(41674037,61374126,61379029);山东省自然科学基金项目(ZR2013FM021);青岛农业大学高层次人才科研基金项目(6631430)

摘　　要：为了改善船舶动力定位系统多传感器融合性能,基于模糊自适应UKF建立了一种多传感器分级融合算法。利用协方差匹配原理建立模糊自适应算法,利用新息建立测量质量控制算法和子系统故障诊断算法,将这三种算法与UKF相结合构成模糊自适应UKF算法。利用滤波状态参数构建第一级相互平行的融合算法,再基于相互独立的第一级融合性能建立第二级融合,从而构建基于模糊自适应UKF的多传感器分级融合算法,实现多传感器的动态分级融合。仿真结果验证了所建算法的有效性。To improve the performance of multi-sensor fusion of vessel dynamic positioning system （DPS） ,a hierar-chical fusion algorithm based on fuzzy adaptive unscented Kalman filter （UKF） is proposed. It combines thadaptive tilter algorithm established by using the covariance matching principle,the measurement quality control al-gorithm and the sub-system fautt diagnosis algorithm established by using innovation. Then,the tirst-level parallelfusion algorithm is set up by using tilter state parameters and the second-level fusion is established based on themu- tually independent tirst-level i^usion performance. In this way, a multi-sensor fusion algorithm is thus establishedbased on fuzzy adaptive UKF,and the dynamic hierarchical fusion of multi-sensor is achieved. The nulation results verifies the effectiveness of the proposed algorithm.

关 键 词：UKF 分级融合 模糊自适应 故障诊断 

分 类 号：U666.1[交通运输工程—船舶及航道工程]