基于经验模态分解的航空重力测量动态误差分离

航空重力测量数据在测量的过程中很容易受到飞机动态运动的影响,飞机动态运动强时,航空重力测量数据的质量也随之降低,虽然经过数字滤波后可以将航空重力异常数据中的大部分噪声去除,但一部分与信号重叠的噪声还是无法被消除.利用经验模态分解对受飞机动态影响较大的一组实测数据进行深化处理.结果表明,在不影响航空重力异常数据分辨率的情况下,该方法很好地消除了由飞机动态运动引起的动态误差,使得航空重力测量的内符合精度由1.43mGal提升到了1.27mGal.

Dynamic errors separation of airborne gravimetry based on empirical mode decomposition

The data of airborne gravimetry measurement is easily interfered by the dynamic movement of planes,and the quality of the data of airborne gravimetry will also decline when the dynamic movement of planes is strong.Through digital filtering, most of the noises in gravity anomaly data can be removed.However,a part of noises overlapped with useful signals cannot be wiped out.Using empirical mode decomposition,we can process a group of measured data in depth which have great influence on dynamic movement of planes.The result indicates that the dynamic errors caused by the dynamic movement of planes could be eliminated without affecting the data resolu-tion of airborne gravity anomaly,thus enhancing the internal accord accuracy from 1.43 to 1.27 mGal.