A framework for predicting underwater object recognition performance with fluorescence LIDAR

Stefania Matteoli,Giovanni Corsini,Marco Diani,Laura Zotta

doi:10.1109/igarss.2017.8127450

A framework for predicting underwater object recognition performance with fluorescence LIDAR

Stefania Matteoli, Giovanni Corsini + Show 2 more

https://doi.org/10.1109/igarss.2017.8127450

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Publication Date: Jul 1, 2017

Citations: 5

Affiliation: Institute of Electronics, Computer and Telecommunication Engineering, National Research Council, University of Pisa, Rina Services (Italy)

#Light Detection And Ranging #Fluorescence Light Detection And Ranging + Show 8 more

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Abstract

Detecting and recognizing underwater objects is a topic of great interest in many maritime applications, such as harbor security, safe navigation of autonomous underwater vehicles, and safety of the littoral zone [1]. Fluorescence Light Detection And Ranging (LIDAR) systems play an important role in this context. In this work, a framework for predicting the performance of underwater object recognition by means of fluorescence LIDAR is proposed with the aim of assisting the user during operations such as mission planning and LIDAR system design. Experimental results obtained within a Monte Carlo simulation framework reveal the potential of the proposed framework.

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