Joint Gravity and Gravity Gradient Inversion for Subsurface Object Detection

Author

Lin Wu ; Xiaoping Ke ; Houtse Hsu ; Jian Fang ; Chengyi Xiong ; Yong Wang

Author_Institution

State Key Lab. of Geodesy & Earth´s Dynamics, Inst. of Geodesy & Geophys., Wuhan, China

Volume

10

Issue

4

fYear

2013

fDate

41456

Firstpage

865

Lastpage

869

Abstract

A novel approach of joint gravity and gravity gradient inversion is presented for passive subsurface object detection in this letter. Gravity and gravity gradient anomalies induced by an object can be measured and inversed to estimate the mass, orientation, and distance of the object. The new equations of gravity inversion are explored, and the weighted least squares estimation is constructed. Therefore, the two kinds of data are complementary to each other in the joint inversion via the self-adaptive weights. Simulation results show that the proposed approach is more efficient and robust than the previous gravity gradient tensor inversion.

Keywords

buried object detection; geophysical techniques; gravity; least squares approximations; gravity gradient anomalies; gravity gradient tensor inversion; joint gravity; passive subsurface object detection; self-adaptive weights; weighted least squares estimation; Equations; Estimation; Gravity; Joints; Mathematical model; Object detection; Tensile stress; Autonomous underwater vehicle (AUV); gravity gradient tensor; gravity inversion; subsurface object; underwater object detection;

fLanguage

English

Journal_Title

Geoscience and Remote Sensing Letters, IEEE

Publisher

ieee

ISSN

1545-598X

Type

jour

DOI

10.1109/LGRS.2012.2226427

Filename

6389708