A local geopotential model for implementation of underwater passive navigation  

作　　者：Zhigang Wang Shaofeng Bian 

机构地区：[1]Department of Navigation, Naval University of Engineering, Wuhan 430033, China

出　　处：《Progress in Natural Science:Materials International》2008年第9期1139-1145,共7页自然科学进展·国际材料（英文版）

基　　金：National Natural ScienceFoundation of China (Grant Nos. 40125013 and 40644020)

摘　　要：A main aspect of underwater passive navigation is how to identify the vehicle location on an existing gravity map, and several matching algorithms as ICCP and SITAN are the most prevalent methods that many scholars are using. In this paper, a novel algorithm that is different from matching algorithms for passive navigation is developed. The algorithm implements underwater passive navigation by directly estimating the inertial errors through Kalman filter algorithm, and the key part of this implementation is a Fourier series-based local geopotential model. Firstly, the principle of local geopotential model based on Fourier series is introduced in this paper, thus the discrete gravity anomalies data can be expressed analytically with respect to geographic coordinates to establish the observation equation required in the application of Kalman filter. Whereafter, the indicated gravity anomalies can be gotten by substituting the inertial positions to existing gravity anomalies map. Finally, the classical extended Kalman filter is introduced with the differences between measured gravity and indicated gravity used as observations to optimally estimate the errors of the inertial navigation system （INS）. This navigation algorithm is tested on simulated data with encouraging results. Although this algorithm is developed for underwater navigation using gravity data, it is equally applicable to other domains, for example vehicle navigation on magnetic or terrain data.A main aspect of underwater passive navigation is how to identify the vehicle location on an existing gravity map, and several match-ing algorithms as ICCP and SITAN are the most prevalent methods that many scholars are using.In this paper, a novel algorithm that is difierent from matching algorithms for passive navigation is developed.The algorithm implements underwater passive navigation by directly estimating the inertial errors through Kalman filter algorithm, and the key part of this implementation is a Fourier series-based local geopotential model.Firstly, the principle of local geopotential model based on Fourier series is introduced in this paper, thus the discrete gravity anomalies data can be expressed analytically with respect to geographic coordinates to establish the observation equation required in the application of Kalman filter.Whereafter, the indicated gravity anomalies can be gotten by substituting the inertial posi-tions to existing gravity anomalies map.Finally, the classical extended Kalman filter is introduced with the difierences between measured gravity and indicated gravity used as observations to optimally estimate the errors of the inertial navigation system (INS).This naviga-tion algorithm is tested on simulated data with encouraging results.Although this algorithm is developed for underwater navigation using gravity data, it is equally applicable to other domains, for example vehicle navigation on magnetic or terrain data.

关 键 词：Passive navigation Fourier series Local geopotential model Extended Kalman filter Inertial navigation system 

分 类 号：V249.322[航空宇航科学与技术—飞行器设计]