Share Email Print
cover

Proceedings Paper

Research on matching area selection criteria for gravity gradient navigation based on principal component analysis and analytic hierarchy process
Author(s): Ling Xiong; Kaihan Li; Jianqiao Tang; Jie Ma
Format Member Price Non-Member Price
PDF $14.40 $18.00

Paper Abstract

The matching area selection is the foundation of gravity gradient aided navigation. In this paper, a gravity gradient matching area selection criterion is proposed, based on the principal component analysis (PCA) and analytic hierarchy process (AHP). Firstly, the features of gravity gradient are extracted and nine gravity gradient characteristic parameters are obtained. Secondly, combining PCA with AHP, a PA model is built and the nine characteristic parameters are fused based on it. At last, the gravity gradient matching area selection criterion is given. By using this criterion, gravity gradient area can be divided into matching area and non-matching area. The simulation results show that gravity gradient position effect in the selected matching area is superior to the matching area, and the matching rate is greater than 90%, the position error is less than a gravity gradient grid.

Paper Details

Date Published: 14 December 2015
PDF: 8 pages
Proc. SPIE 9815, MIPPR 2015: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications, 981519 (14 December 2015); doi: 10.1117/12.2204819
Show Author Affiliations
Ling Xiong, Wuhan Univ. of Science and Technology (China)
Kaihan Li, Wuhan Univ. of Science and Technology (China)
Guochuang Tech Industrial Group Co., Ltd. (China)
Jianqiao Tang, Wuhan Univ. of Science and Technology (China)
Jie Ma, Huazhong Univ. of Science and Technology (China)


Published in SPIE Proceedings Vol. 9815:
MIPPR 2015: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications
Jianguo Liu; Hong Sun, Editor(s)

© SPIE. Terms of Use
Back to Top