Abstract: The major error sources of deriving TEC from GPS observational data are instrumental biases. Two methods of extracting TEC and instrumental biases based on single site's GPS observations, called Kalman filter and self adjusted cell methods respectively, are presented. TEC and instrumental biases were computed by using these two methods from GPS data at several sites in 2004. The results were analyzed respectively and then compared with each other. The results also were compared with corresponding values published by CODE (Center for Orbit Determination in Europe).Its statistical characteristics with respect to the latitude of observational site were discussed. The main results can be concluded that the proposed methods can be used to derive TEC and instrumental biases which are accuracy enough with respect to CODE's published values. The standard deviations of derived instrumental biases are related to latitudes of observational sites. For China region, based on the paper's computational results, it shows that the sites with lower latitude are related with larger deviation, which is a implication that ionosphere is more complex in low latitude area than that in mid latitude and more caution should be paid in using the assumption of simple smooth ionospheric model in lower latitude.

Key words: GPS, instrumental bias, Kalman filter, TEC

摘要： 从GPS数据中解算电离层总电子含量(TEC)的最大误差源是硬件延迟。作者介绍了两种解算电离层TEC和硬件延迟的方法。利用单站的GPS双频数据，计算了2004年电离层TEC和硬件延迟，对两种方法得到的硬件延迟进行了比较，并且和欧洲定轨中心的公布结果进行了对比，同时分析了不同纬度台站数据解算硬件延迟的误差特点。结果表明：这两种方法均可以解算TEC和硬件延迟，结果是可靠的。解算的硬件延迟的标准偏差与观测站的纬度有关，在中国区域，纬度越低，估算的硬件延迟偏差越大，对这一情况进行了分析。

关键词: GPS, 硬件延迟, 卡尔曼滤波, 电离层总电子含量(TEC)