A framework for predicting underwater object recognition performance with fluorescence LIDAR

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.