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中文摘要：
提出一种基于局部地球重力场模型的水下重力辅助导航新模式。首先介绍一种利用快速傅里叶拟合技术建立的连续局部重力场模型,随后在该模型的基础上,将测量重力与惯导指示重力之差表示为连续的解析形式,最后以重力差作为包含惯导位置误差的量测值,结合扩展卡尔曼滤波算法对惯导位置误差进行最优估计。以分辨率为2′×2′的某区域重力异常数据为背景场进行仿真,局部重力场模型的平均误差小于0.13mGal（1mGal=10-3cm/s2）,潜器的平均经纬定位误差分别小于0.20nm和0.25nm。
英文摘要：
Implementing underwater gravity aided inertial navigation on Kalman filter requires the modeling of gravity measurements and their errors.Due to that background a new pattern of gravity aided navigation which is based on local gravity field modeling is given in this paper.Firstly,a fast Fourier series based local gravity field modeling is introduced,by which the difference between measured gravity and indicated gravity is then expressed as a continual analytical equation.After that,the extended Kalman filter is introduced, with the gravity difference used as measurement, to est base, and from the 0.13 mGal（1 mGa mile respectively. imate the position error of INS. Finally, a simulation is done on 2′×2′ gravity anomaly dataresults it can be seen that the mean error of the local gravity field modeling is less than 10^3 cm/s2）, and the mean location error in longitude and latitude is 0.20 and 0.25 nautical mile respectively,
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