Kang Yingyao, Zhao Lin, Cheng Jianhua, Wu Mouyan, Fan Xiaoliang
College of Automation, Harbin Engineering University, Harbin 150001, China.
Sensors (Basel). 2018 Jan 26;18(2):364. doi: 10.3390/s18020364.
Integrated navigation algorithms under the grid frame have been proposed based on the Kalman filter (KF) to solve the problem of navigation in some special regions. However, in the existing study of grid strapdown inertial navigation system (SINS)/Doppler velocity log (DVL) integrated navigation algorithms, the Earth models of the filter dynamic model and the SINS mechanization are not unified. Besides, traditional integrated systems with the KF based correction scheme are susceptible to measurement errors, which would decrease the accuracy and robustness of the system. In this paper, an adaptive robust Kalman filter (ARKF) based hybrid-correction grid SINS/DVL integrated navigation algorithm is designed with the unified reference ellipsoid Earth model to improve the navigation accuracy in middle-high latitude regions for marine application. Firstly, to unify the Earth models, the mechanization of grid SINS is introduced and the error equations are derived based on the same reference ellipsoid Earth model. Then, a more accurate grid SINS/DVL filter model is designed according to the new error equations. Finally, a hybrid-correction scheme based on the ARKF is proposed to resist the effect of measurement errors. Simulation and experiment results show that, compared with the traditional algorithms, the proposed navigation algorithm can effectively improve the navigation performance in middle-high latitude regions by the unified Earth models and the ARKF based hybrid-correction scheme.
基于卡尔曼滤波器(KF)提出了网格框架下的组合导航算法,以解决某些特殊区域的导航问题。然而,在现有的网格捷联惯性导航系统(SINS)/多普勒速度计(DVL)组合导航算法研究中,滤波器动态模型和SINS力学编排的地球模型并不统一。此外,基于KF校正方案的传统组合系统易受测量误差影响,这会降低系统的精度和鲁棒性。本文设计了一种基于自适应鲁棒卡尔曼滤波器(ARKF)的混合校正网格SINS/DVL组合导航算法,采用统一的参考椭球体地球模型,以提高海洋应用中高纬度地区的导航精度。首先,为统一地球模型,引入了网格SINS的力学编排,并基于相同的参考椭球体地球模型推导了误差方程。然后,根据新的误差方程设计了更精确的网格SINS/DVL滤波器模型。最后,提出了一种基于ARKF的混合校正方案来抵抗测量误差的影响。仿真和实验结果表明,与传统算法相比,所提出的导航算法通过统一的地球模型和基于ARKF的混合校正方案,能够有效提高中高纬度地区的导航性能。