摘要
在动态定位或动态变形监测中,Ka lm an滤波状态模型主要采用随机游走、常速度和常加速运动学模型。然而用这些简单的运动学模型描述变形体的复杂运动状态不可避免地含有模型误差,且由于某些异常扰动必然使得原先选用的状态模型出现显著性的模型偏差,从而严重影响滤波的精度。采用模拟数据,分别对状态模型为随机游走模型、常速度模型、常加速度模型以及附有偏差校正的常速度模型的Ka lm an滤波模型进行了比较分析,给出了不同模型在变形监测应用中的优缺点。
In the kinematic positioning or dynamic deformation monitoring, random walk model, constant velocity model and constant acceleration model are usually applied as the state model of Kalman filter. However, with these simple kinematic models to describe the complex movement of the deformed body,the modeled results will are inevitably contained errors and under some abnormal disturbance there are inevitably significant model biases in the original kinematic model, which will seriously affect the accuracy of filtering. With simulated data random walk model, constant velocity model, constant acceleration model and constant velocity model with correction of the model biases are comparatively analyzed. The advantages and disadvantages of the above models are summarized for the application of deformation monitoring.
出处
《大地测量与地球动力学》
CSCD
北大核心
2009年第6期88-92,共5页
Journal of Geodesy and Geodynamics
基金
国家自然科学基金(40704002)
湖南省自然科学基金(08JJ6025)
关键词
KALMAN滤波
偏差校正
随机游走模型
常速度模型
常加速度模型
Kalman filter
correction of the model biases
random walk model
constant velocity model
constant acceleration model
