Computer-aided detection of rapid, overt, airborne, reconnaissance data with the capability of removing oceanic noises
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Authors
Fritz, James R.
Subjects
Mine Countermeasures
Computer Aided Detection
Computer Aided Identification
Optimization
Physical Oceanography
Computer Aided Detection
Computer Aided Identification
Optimization
Physical Oceanography
Advisors
Chu, Peter C.
Fan, Chenwu
Date of Issue
2013-12
Date
Dec-13
Publisher
Monterey, California. Naval Postgraduate School
Language
Abstract
There have been three times more attacks to naval ships using sea mines than all other forms combined. Sea mines have always been viewed upon as underhanded and unchivalrous, yet they provide a weaker navy the capability to stall and damage a vastly superior navy. Utilizing unmanned sensors to detect sea mines is the goal of the navy for the future. Computer-aided detection (CAD) of sea mines is much faster and more consistent than a human operator, yet it is not currently being utilized by any of our mine countermeasure assets. Although there are many studies that have incorporated computer aided detection and classification algorithms with sonar imagery for mine warfare, few have used Light Detection and Ranging (LIDAR). During an amphibious assault scenario the ability to land assets quickly and mitigate risk is vital to the success. This thesis analyzes Rapid Overt Aerial Reconnaissance data from an Office of Naval Research experiment by Fort Walton Beach, FL. The CAD algorithm that was developed consistently detects sea mines in LIDAR data while having a manageable false alarm rate.
Type
Thesis
Description
Series/Report No
Department
Oceanography
Organization
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NPS Report Number
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Citation
Distribution Statement
Approved for public release; distribution is unlimited.
Rights
This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.