Open AccessImproving the detection of underwater metal-containing objects by fusion of ferromagnetic sensors data with vehicle’s navigational data
Author(s) -
D. A. Frolov,
Dmitry Gromoshinsky,
Anton Korsakov,
Ekaterina Smirnova
Publication year - 2019
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/302/1/012159
Subject(s) - orientation (vector space) , sensor fusion , computer science , signal (programming language) , underwater , computer vision , real time computing , task (project management) , artificial intelligence , remote sensing , engineering , geology , oceanography , geometry , mathematics , systems engineering , programming language
Currently, the task of developing the Arctic shelf is relevant, because there are proven reserves of minerals – oil and gas. Undoubtedly, researchers and engineers, after installing the appropriate underwater infrastructure, will face the task of maintenance and repair of communications. For this purpose, autonomous unmanned underwater vehicles (AUV) can be used, with e.g. the task of inspecting pipelines. The article describes the processing algorithm for the signal from passive ferromagnetic sensors mounted on an AUV carrier used to search for metal-containing objects at the sea bottom. A scheme for such a measurement is proposed - the installation of two sensors at opposite ends of the carrier. This allows to measure the gradient of magnetic field between the sensors. The characteristic form of such a signal and the dependence of the signal on the motion parameters of the vehicle and external factors are determined. To eliminate false positives, filters are used based on the readings of the position, speed and orientation sensors of the navigation system. Using data on the motion parameters of the device allows to generate a reference signal, which is used to validate the detection of an object using the cross-correlation method. The use of data on orientation angles makes it possible to compensate for the influence of the orientation of the device in the Earth’s magnetic field.