卡尔曼滤波地形反演算法的系统方程建模

Error Equation Modeling of Bathymetry Prediction Algorithm Based on Kalman Filter

利用重力梯度反演局部地形可获取较高的反演精度。传统地形反演算法以大尺度离线反演为主,不便于算法移植和与其他系统的组合。研究了利用卡尔曼滤波对潜艇周围局部地形进行反演的方法。重点在地形坡度理论基础上对卡尔曼滤波系统误差方程建模,介绍了详细的推导过程。仿真结果证实了该误差模型的有效性。

Using gravity gradient data to estimate local terrain can get a perfect precision.But traditional estimation algorithms are mainly for large-scale and in an off-line way,which have hindered them from transplanting and combining with other data source.This paper studied a bathymetry estimation algorithm based on kalman filter,and focused on its system error equation modeling by introducing terrain slope theory.Terrain slope and those statistical methods are equivalent in describing terrain correlation,but compared with those statistical methods,the former reduced complexity of the model.The biggest advantage of the new model is that it avoids the lack of theoretical basis when statistical methods determine statistical parameters,consequently,further improves adaptability of estimation algorithm.