Show simple item record

dc.contributor.advisorBailey, M.P.
dc.contributor.authorRodgers, Anthony C.
dc.contributor.authorBailey, Michael P.
dc.date1995
dc.date.accessioned2013-08-13T22:06:59Z
dc.date.available2013-08-13T22:06:59Z
dc.date.issued1995-09
dc.identifier.urihttp://hdl.handle.net/10945/35188
dc.description.abstractThe U.S. Navy currently has no means to conduct sea mine reconnaissance with assets that are organic to Aircraft Carrier Battle Groups or Amphibious Ready Groups. Magic Lanten is an Airborne Laser Mine Detection System (ALMDS) under development, that is designed to search for floating and shallow moored mines using a helicopter- mounted laser-optic sensor. It is the only ALMDS operationally tested by the Navy to date. This thesis develops a Monte Carlo simulation model called ML-Recon, which is intended for use as a tool to plan mine reconnaissance searches using the Magic Lantern system. By entering fundamental initial planning information, the user can determine the number of uniformly-spaced tracks to fly with a Magic Lantern-equipped helicopter to achieve a certain level of assurance that the area contains no floating or shallow moored mines. By employing Monte Carlo methods, ML-Recon models the three primary stochastic processes that take place during a typical search: the location of the mines, the cross-track error of the helicopter, and the detection/non-detection process of the sensor. By running ML-Recon, the user is given performance statistics for many replications of the search plan that he chooses. This approach is unique in that it provides the user with information indicating how much worse than the mean performance his plan may perform. ML- Recon also gives the user an Opportunity to view an animation of his lan, which he can use to look for tendencies in the lan to contain holes, or holidays. (AN)en_US
dc.description.urihttp://archive.org/details/mlreconsimulatio1094535188
dc.format.extent38 p.en_US
dc.language.isoen_US
dc.publisherMonterey, California. Naval Postgraduate Schoolen_US
dc.rightsThis publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. As such, it is in the public domain, and under the provisions of Title 17, United States Code, Section 105, may not be copyrighted.en_US
dc.titleML-Recon simulation model: a Monte Carlo planning aid for Magic Lantern.en_US
dc.typeThesisen_US
dc.contributor.departmentOperations Research
dc.description.funderNAen_US
dc.description.recognitionNAen_US
etd.thesisdegree.nameM.S. in Operations Researchen_US
etd.thesisdegree.levelMastersen_US
etd.thesisdegree.disciplineOperations Researchen_US
etd.thesisdegree.grantorNaval Postgraduate Schoolen_US


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record