To deal with the low location accuracy issue of existing underwater navigation technologies in autonomous underwater vehicles(AUVs),a distributed fusion algorithm which combines the model's analysis method with a ...To deal with the low location accuracy issue of existing underwater navigation technologies in autonomous underwater vehicles(AUVs),a distributed fusion algorithm which combines the model's analysis method with a multi-scale transformation method is proposed for integrated navigation system based on AUV.First,integrated navigation system theory and system error sources are introduced in details.Secondly,a navigation system's observation equation on the original scale is decomposed into different scales by the discrete wavelet transform method,and noise reduction is performed by setting the wavelet de-noising threshold.At last,the dynamic equation and observation equations are fused on different scales by the wavelet transformation and Kalman filter.The results show that the proposed algorithm has smaller navigation error and higher navigation accuracy.展开更多
基金National Natural Science Foundation of China(51779057,51709061,51509057)the Equipment Pre-Research Project(41412030201)the National 863 High Technology Development Plan Project(2011AA09A106)。
文摘To deal with the low location accuracy issue of existing underwater navigation technologies in autonomous underwater vehicles(AUVs),a distributed fusion algorithm which combines the model's analysis method with a multi-scale transformation method is proposed for integrated navigation system based on AUV.First,integrated navigation system theory and system error sources are introduced in details.Secondly,a navigation system's observation equation on the original scale is decomposed into different scales by the discrete wavelet transform method,and noise reduction is performed by setting the wavelet de-noising threshold.At last,the dynamic equation and observation equations are fused on different scales by the wavelet transformation and Kalman filter.The results show that the proposed algorithm has smaller navigation error and higher navigation accuracy.
