吉林大学学报(地球科学版) ›› 2020, Vol. 50 ›› Issue (3): 883-894.doi: 10.13278/j.cnki.jjuese.20190040

• 地球探测与信息技术 • 上一篇    

基于多元线性回归的航空重力梯度测量自身梯度校正

孙勇1, 于平1, 王新月2, 黄大年1   

  1. 1. 吉林大学地球探测科学与技术学院, 长春 130026;
    2. 吉林大学仪器科学与电气工程学院, 长春 130026
  • 收稿日期:2019-03-05 发布日期:2020-05-29
  • 作者简介:孙勇(1988-),男,博士研究生,主要从事航空重磁数据处理研究,E-mail:1139906865@qq.com
  • 基金资助:
    吉林省自然科学基金项目(20180101312JC);国家高技术研究发展计划项目(2014AA06A613);博士后创新人才支持计划项目(B2017-014)

Correction of Self-Gradient in Airborne Gravity Gradient Measurement Based on Multiple Linear Regression

Sun Yong1, Yu Ping1, Wang Xinyue2, Huang Danian1   

  1. 1. College of GeoExploration Science and Technology, Jilin University, Changchun 130026, China;
    2. College of Instrumentation and Electrical Engineering, Jilin University, Changchun 130026, China
  • Received:2019-03-05 Published:2020-05-29
  • Supported by:
    Supported by National Science Foundation of Jilin Province (20180101312JC), National High-Tech R & D Program of China (2014AA06A613), and National Postdoctoral Program for Innovative Talents (B2017-014)

摘要: 航空重力梯度勘探中,载体自身产生的重力梯度效应对于超高精度的重力梯度仪而言是一种严重的干扰。由于载体结构复杂,用常规的载体建模并正演难以精确去除这种干扰。本文从统计学角度出发,用多元线性回归来处理自身梯度效应,不需要对载体模型做出任何假设与近似,用纯数据驱动的方式来校正自身梯度的干扰。回归诊断与模型仿真验证了这种校正方式有较高的准确性,并且当实际的转角落在地面标定的范围内时具备预测能力。

关键词: 航空重力梯度, 自身梯度效应, 回归分析

Abstract: The self-gradient effect produced by the vehicle is a serious disturbance to the ultra-high precision of the gravity gradiometer in an airborne gravity gradient survey. Due to the complexity of the vehicle structure, it is difficult to remove these interferences by using conventional modeling and forward calculation accurately. In this article, a multiple linear regression algorithm is used to deal with its own gradient effect, which corrects the interference from the gradient in a pure data-driven way,without making any assumptions or approximations to the vehicle model. Through regression diagnosis and model simulation, this correction method has high accuracy and predictive ability when the actual corner is within the ground calibration range.

Key words: airborne gravity gradient, self-gradient effect, regression analysis

中图分类号: 

  • P631.1
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