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Investigation of submerged maritime target detection using LIDAR

<p>Lidar is an optical remote sensing technology which uses the backscattered light to create information profiles of the scanning area. Normally the air is used as propagation medium, but in this work the Lidar's efficiency to detect submerged target in water is discussed.   Following the theories of light propagation in the air and in the water a model to simulate the target detection is created. The values of scattering and absorption of the laser pulse in water are estimated by Morel equations which give accurate values of the sea water properties. Scattering and absorption define the optical properties of the medium, so the attenuation and the backscattering coefficient are calculated. These value will have a strong dependency to the salinity, pressure, temperature, sea water constituents and so on.   After the estimation of the parameters a model based on Lidar Equation, Fresnel Equations and Snell´s law has been developed with the aim of predict the maximum range to detect the sea surface and the maximum depth to detect the sea bottom.     In order to verify the goodness of the model, a prototype 532nm Lidar system has been used to collect experimental data. The Lidar was used from a 50m high building scanning from near vertical incidence to near horizontal incidence.   The extracted data from the simulations have been compared with the data obtained from realized test. This has given  us a predicted maximum range to detect the sea surface of 220m and an estimated  maximum depth for a reference target of 17m.</p>

Identiferoai:union.ndltd.org:UPSALLA/oai:DiVA.org:ntnu-9100
Date January 2009
CreatorsAyala Fernández, Unai, Hernández, Luis Manuel
PublisherNorwegian University of Science and Technology, Department of Electronics and Telecommunications, Norwegian University of Science and Technology, Department of Electronics and Telecommunications, Institutt for elektronikk og telekommunikasjon
Source SetsDiVA Archive at Upsalla University
LanguageEnglish
Detected LanguageEnglish
TypeStudent thesis, text

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