测绘学报

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基于卡尔曼滤波的地形反演方法及其仿真研究

刘繁明,钱东,郭静   

  1. 哈尔滨工程大学自动化学院
  • 收稿日期:2009-08-31 修回日期:2010-02-02 出版日期:2011-02-25 发布日期:2011-02-25
  • 通讯作者: 刘繁明

Terrain Estimation Algorithm Based on Kalman Filter and its Simulation Research

  • Received:2009-08-31 Revised:2010-02-02 Online:2011-02-25 Published:2011-02-25

摘要: 推导了基于卡尔曼滤波的海底地形反演算法,算法通过利用重力梯度仪测量重力梯度异常,提高地形反演的精度和分辨率。结合地形坡度计算理论和矩形棱柱法,建立了基于卡尔曼滤波的系统方程和量测方程。对算法进行了仿真,分析了地形均值误差、随机误差和梯度仪测量精度对反演精度的影响,最后的区域反演仿真结果表明:反演后的地形在精度和分辨率上都有所提高,证实了反演算法的正确性。

Abstract: In this paper, a terrain estimation algorithm based on kalman filter was proposed. Combining with gradient anomaly measured by gravity gradiometer, the algorithm achieved the purpose of terrain estimation by improving the accuracy and resolution of a low-resolution priori terrain. By introducing slope theory and rectangular prism method, the paper built system error model and measure equation of the kalman filter first. After that a simulation research was carried out to investigate the effect of algorithm. The simulation analyzed terrain mean noise, random noise and gravity gradiometer precision’s influence on estimation accuracy. At last, an area estimation simulation was also investigated. The results show that both the precision and resolution of estimated terrain have improved, which confirmed the correctness of the algorithm.