Title :
Underwater Obstacle Detection Based on the Change of Gravity Gradient
Author :
Yan, Zu ; Yang, Fan ; Ma, Jie ; Tian, Jinwen
Author_Institution :
Inst. for Pattern Recognition & Artificial Intell., Huazhong Univ. of Sci. & Technol., Wuhan, China
Abstract :
In view of the difficulty in obtaining gravity gradient reference maps at present, this paper presents a new method for detecting the barrier which is underwater. The method is autonomous, independent, and needing no gravity gradient reference map.This method Firstly needs record gravity gradiometer´s three readings in the submarine current route. Secondly subtract the first reading with the second reading, and subtract the second reading with the third reading, then we can get two differences. Do division of the two differences , finally we can get the inversion formula for the location of the obstacle. Through the Trust-Region-Reflective method to solve this equation, we will get the location information of the obstacle, then get its mass information. Experiments showed that using the gravity gradiometer whose precision is 10-5E, the method can detect not only the reef whose mass is 109kg magnitude within 500 meters but also the wreck whose mass is 107kg magnitude within 600 meters with no need of the gravity gradient reference map.Comparing with the traditional method of detecting obstacles, the new method meets the stringent requirements of safety and concealment very well. What´s more, the new method detects obstacles with no need of the data of the background´s gravity or gravity gradient. Therefore, the method which our paper presents is of great value in practical applications.
Keywords :
geophysical techniques; gravimeters; gravity; object detection; underwater vehicles; change of gravity gradient; gravity gradient reference map; gravity gradiometer; submarine current route; trust region reflective method; underwater obstacle detection; Artificial intelligence; Earth; Educational institutions; Gravity; Navigation; Pattern recognition; Underwater vehicles;
Conference_Titel :
Remote Sensing, Environment and Transportation Engineering (RSETE), 2012 2nd International Conference on
Conference_Location :
Nanjing
Print_ISBN :
978-1-4673-0872-4
DOI :
10.1109/RSETE.2012.6260800