江 鹏, 叶世榕, 何书镜, 刘炎炎. 自适应Kalman滤波用于GPS层析大气湿折射率[J]. 武汉大学学报 ( 信息科学版), 2013, 38(3): 299-302.
引用本文: 江 鹏, 叶世榕, 何书镜, 刘炎炎. 自适应Kalman滤波用于GPS层析大气湿折射率[J]. 武汉大学学报 ( 信息科学版), 2013, 38(3): 299-302.
JIANG Peng, YE Shirong, HE Shujing, LIU Yanyan. Ground\|based GPS Tomography of Wet Refractivity with Adaptive Kalman Filter[J]. Geomatics and Information Science of Wuhan University, 2013, 38(3): 299-302.
Citation: JIANG Peng, YE Shirong, HE Shujing, LIU Yanyan. Ground\|based GPS Tomography of Wet Refractivity with Adaptive Kalman Filter[J]. Geomatics and Information Science of Wuhan University, 2013, 38(3): 299-302.

自适应Kalman滤波用于GPS层析大气湿折射率

Ground\|based GPS Tomography of Wet Refractivity with Adaptive Kalman Filter

  • 摘要: 在分析Kalman滤波层析方法的基础上,将基于指数渐消因子的自适应Kalman滤波方法用于层析大气湿折射率,并结合香港地区CORS网观测资料及探空气象观测资料进行了分析。结果表明,该方法能够长时间以较高精度反演湿折射率垂直轮廓线,较好地反映了大气的实际状况,有效避免了一般Kalman滤波可能出现的发散。

     

    Abstract: An exponent fading factor adaptive Kalman filter algorithm instead of standard Kalman filter is introduced to improve the ground\|based GPS tomographic method of wet refractivity. Two different periods of GPS observation data and meteorological data from Hong Kong CORS are processed to determinate the 3D distribution of wet refractivity with tomographic method. The results show that this method can retrieve the wet refractivity vertical profile and 3D distribution precisely within a long tomographic procedure without any divergence.

     

/

返回文章
返回