Comparison of Models for GPS Kinematic Data Processing

处理模型，最少的正方形(LS ) ， Kalman 过滤和 H ∞ 过滤的三个 GPS 运动学的数据的特征被讨论，他们的优点和劣势被比较。与观察数据和恰当的数据处理软件，三个模型的适用的条件，上下文和效果被试验。结果证明当活动平台在匀速运动时，三个模型的精确性是几乎相等的；当活动平台在随机的加速时，过滤模型的 H ∞ 的精确性比 LS 的优异，当过滤的 Kalman 的是最糟时。

The characteristics of three GPS kinematic data processing models, Least Squares （LS）, Kalman filtering and filtering are discussed and their advantages and disadvantages are compared. With observational data and pertinent data processing software, the applicable condition, context and effect of the three models are experimented. Results show that when the mobile platform is in uniform motion, the accuracy of the three models are almost equal; when the mobile platform is in stochastic acceleration, the accuracy of H∞ filtering model is superior to that of LS, while that of Kalman filtering is the worst.