Research on matching area selection based on multiple features fusion of full tensor gravity gradient

Jian-qiao Tang; Ling Xiong; Kai-han Li; Jie Ma

doi:10.1117/12.2204828

14 December 2015 Research on matching area selection based on multiple features fusion of full tensor gravity gradient

Jian-qiao Tang, Ling Xiong, Kai-han Li, Jie Ma

Proceedings Volume 9812, MIPPR 2015: Automatic Target Recognition and Navigation; 98120F (2015) https://doi.org/10.1117/12.2204828
Event: Ninth International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR2015), 2015, Enshi, China

Abstract

Submarines in the underwater sailing need a safe, reliable, high accurate, and covert well navigation system. Inertial navigation system (INS) is the core of underwater navigation. But the inertial navigation system gathers information based gyroscope, accelerometer and other sensors. In accordance to Newton's laws of mechanics, their own speed, location and other information is calculated by integral recursion. Since the recursive work of INS, positioning error gradually increases with time elapsing. Gravity and gravity gradient aided navigation as a passive autonomous navigation are more and more focused on, Selection of the gravity gradient matching area is one of the key to gravity gradient matching navigation. Earth's marine area is enormous, underwater environment is complex. Take advantage of multi-feature information fusion of gravity gradient full tensor, one hand a wider range of matching area can be got, to gain wider path planning area. on the other hand, the positioning accuracy of assisted navigation system can be inproved.

Citation Download Citation

Jian-qiao Tang, Ling Xiong, Kai-han Li, and Jie Ma "Research on matching area selection based on multiple features fusion of full tensor gravity gradient", Proc. SPIE 9812, MIPPR 2015: Automatic Target Recognition and Navigation, 98120F (14 December 2015); https://doi.org/10.1117/12.2204828

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available