【摘要】 为克服观测向量中的粗差对状态参数滤波值的影响 ,通过分析其影响规律 ,并充分顾及到粗差在预测残差中得到全部反映的特点 ,导出了 GPS监测网动态数据处理的抗差卡尔曼滤波模型——该模型对观测空间和设计空间均具有良好的抗差性 .通过利用该抗差滤波模型对含有粗差的模拟 GPS监测网的计算 ,与采用标准卡尔曼滤波模型的计算结果相比较 ,可获得可靠的变形分析结果更多还原

【Abstract】 In order to overcome the influence of gross errors in observation vectors on the filtering values of state vectors, based on the laws that the gross errors influence the state vectors and the characteristic that they are shown completely in residual forecasting, a robust Kalman filtering model was derivesd. This model has good robusticity to observation space and design space. According to the computation results of a simulative GPS monitoring network with gross errors,and compared with the results of the standard Kalman filtering model,this robust Kalman filtering model can obtain reliable results of deformation analysis.更多还原