引入最优自适应因子的状态模型法航空重力测量

Introducing the optimal adaptive factor to improve the accuracy of airborne gravimetry based on the state model method

引入最优自适应比例因子以改善状态模型法航空重力测量的精度,并尝试将其应用到我国困难地区的重力测量.把重力扰动当作状态量引入Kalman滤波进行最优估计,并引入最优自适应因子调节状态信息的权阵,提高重力扰动的最终解算精度.利用新疆地区不同航次和航高的实测数据,计算了垂直向下方向上的重力扰动.与全球重力场模型EGM2008的对比分析表明,差值中误差在10mGal左右,接近国家在困难地区重力测量精度的限差要求.

This work introduced the optimal adaptive factor to improve the accuracy of airborne gravimetry based on the state model method,attempted to apply this technique to areas of China where gravity measurement is difficult.Gravity disturbance was used as the state vector of Kalman Filter,and the optimal adaptive factor was introduced to adjust the weight matrix of the state information to improve the accuracy of estimation of the gravity disturbance.Based on flight data at different times and different heights in Xinjiang,this work calculated the vertical gravity disturbances,and compared them with the EGM2008 global gravity model.The differences between the results from the proposed method and the EGM2008 model are around 10 mGal,which is close to the precision demand of national gravity surveys in difficult areas.