航空重力测量重复测线数据处理技术研究

Research on Data Processing Technology for Repeated Survey Lines in Aerial Gravity Measurement

航空动态重力测量是快速获取地球重力场信息的有效手段,从广泛噪声中高精度提取重力信息的数据处理技术是重力测量的关键环节。本文首先分析了测量噪声的来源及误差特性,且明确了现阶段常用的有限冲激响应(FIR)低通滤波器可以有效滤除高频噪声。其次,针对动态特性误差和偶然误差,提出基于经验模态分解(EMD)的误差分离方法。再次,提出了适用于多条重复测线的系统平差方法,有效抑制了低频系统误差的影响。最后,对航空实测数据进行了处理。试验结果表明,基于EMD的误差分离方法将内符合精度从2.86mGal提升至0.75mGal,重复测线系统平差方法将精度进一步提升至0.28mGal。该研究对提升航空重力测量系统在数据处理技术成熟度及实用化水平方面有重要意义。

Aerodynamic gravity measurement is an effective means of quickly obtaining information about the earth's gravity field,and the data processing technology of high-precision extraction of gravity information from a wide range of noise plays an important role.This paper first analyzes the sources and error characteristics of measurement noise,and clarifies that commonly used FIR low-pass filters at present can effectively filter out high-frequency noise.Secondly,an error separation method based on Empirical Mode Decomposition(EMD)is proposed for dynamic characteristic errors and accidental errors.Then,a system adjustment method suitable for multiple repeated survey lines was proposed,which effectively suppresses the impact of low-frequency system errors.Finally,the measured aviation data is processed.The experimental results show that the EMD based error separation method improves the internal coincidence accuracy from 2.86mGal to 0.75mGal,and the repeated line system adjustment method further improves the accuracy to 0.28mGal.This study is of great significance for improving the maturity and practicality of airborne gravity measurement systems in data processing technology.