重力异常和重力梯度联合辅助导航算法及仿真  

Aided navigation algorithm and simulation research based on the data of gravity anomaly and gravity gradient

作　　者：王虎彪[1,2] 王勇[1] 许大欣[1] 柴华[1,2] 

机构地区：[1]中国科学院测量与地球物理研究所动力大地测量重点实验室,武汉430077 [2]中国科学院研究生院,北京100049

出　　处：《地球物理学进展》2011年第1期116-122,共7页Progress in Geophysics

基　　金：国家自然科学基金项目(41074051;40974044);中国科学院知识创新工程重要方向项目(kzcx2-yw-125)联合资助

摘　　要：鉴于潜艇的惯性导航系统误差随时间积累的缺陷,重力无源辅助导航近几年成为水下潜艇辅助导航研究的热点和前沿问题.采用多模型自适应Kalman滤波并行算法对重力异常和重力梯度联合辅助导航,通过对沿航迹重力异常和重力梯度信息因子的实时分配,加权处理得到潜艇位置的最优实时估计.选取不同特征区域的2条航线进行仿真试验,对算法的匹配可靠性和匹配误差进行分析,结果表明,该算法能弥补单纯重力异常或重力梯度匹配定位精度不够、误匹配以及匹配失效情况的不足,提高现有重力场辅助导航的定位成功率和定位精度.In view of the shortage that the error of Inertial Navigation System will be cumulated along with the rise of time, the technology of gravity-aided underwater navigation was aroused general interest. The combined-aid navigation for gravity anomaly and gravity gradient is made by using the parallel algorithm of multiple model adaptive estimation, and the information factor of gravity anomaly and gravity gradient along the ship track was allocated in real time, and then, the optimal estimation for the position of the submarine was get via the weighted process. Through selecting two sailing courses in the different character region, simulation experiments were implemented, and the matching reliability and error were analyzed. The results show that, compared with one of gravity anomaly aided navigatin and gravity gradient aided navigation, the method can achieve good performance in some aspects of positioning error, mismatching and failure matching, and it will help to better matching rate and higher positioning accuracy for the existing gravity aided navigation.

关 键 词：重力异常 重力梯度 并行Kalman滤波 权信息因子 联合辅助导航 

分 类 号：P312[天文地球—固体地球物理学]