摘要
为提高水下重力匹配算法的定位精度和稳健性,将容积卡尔曼滤波应用到水下重力匹配惯性导航中,同时引入抗差估计和自适应因子,提出了基于抗差自适应容积卡尔曼滤波的水下重力匹配导航SITAN算法。利用重力异常模型数据开展仿真实验,结果表明,所提算法能有效修正惯导整体航迹,在观测值未加入粗差的情况下较普通容积卡尔曼滤波算法提高了76%的导航定位精度,在观测值加入30 mGal粗差的情况下,提高了88%的导航定位精度。该研究成果可为后续水下重力匹配导航算法的理论研究及工程实践提供一定的数据支撑。
In order to improve the positioning accuracy and robustness of underwater gravity matching algorithm,the cubature Kalman filter is applied to underwater gravity matching inertial navigation.The SITAN algorithm for underwater gravity matching navigation based on robust adaptive cubature Kalman filter is proposed through introducing robust estimation and adaptive factor.The proposed algorithm can effectively correct the overall inertial navigation path based on simulation of gravity anomaly model data,and the navigation and positioning accuracy is improved by 76%compared with the ordinary cubature Kalman filter algorithm when the observed value without gross error,and the navigation and positioning accuracy is improved by 88%when the observed value is added 30 mGal gross error.The research results can provide some data support for the subsequent theoretical research and engineering practice of underwater gravity matching navigation algorithm.
作者
付林威
赵东明
范雕
付林
FU Linwei;ZHAO Dongming;FAN Diao;FU Lin(Institute of Geospatial Information,Strategic Support Force Information Engineering University,Zhengzhou 450001,China)
出处
《海洋测绘》
CSCD
北大核心
2024年第2期5-8,26,共5页
Hydrographic Surveying and Charting
基金
国家自然科学基金(42174008,42204009)。
