摘要
本文利用Kalman滤波方法对动态测量进行数据处理,由于高动态的GPS测量,不易确定系统动态噪声和观测噪声。同时标准的Kalman滤波在应用过程中由于状态模型确定的误差存在,滤波效果不佳。因此本文结合动态导航的实时性和高动态性,建立了动态导航系统中滤波状态方程和观测方程,采用改进的Sage-Husa自适应滤波对来进行实时定位数据处理,利用已有测量数据进行了实例分析。改进的Sage-Husa自适应滤波在计算过程中计算量小,结果稳定,有较强的自适应性。
The paper has briefly introduced the kalman filtering method in kinematic survey. Due to the high dynamic GPS survey, make the kinematic noise and measurement noise are difficult to ascertain. And the standard kalman filtering result is not optimization with the noise of the status model. So take the real time and high dynamic of the navigation system into consideration, establish the state equations and observation ones and in the paper adopt an improved Sage-Husa self adaptive filtering which makes the calculation process more simple, high quality result, and more adaptive.
出处
《现代测绘》
2009年第4期8-10,共3页
Modern Surveying and Mapping
