Aggregate models for target acquisition in urban terrain
Approved for public release, distribution is unlimited. === High-resolution combat simulations that model urban combat currently use computationally expensive algorithms to represent urban target acquisition at the entity level. While this may be suitable for small-scale urban combat scenarios, simu...
Main Author: | |
---|---|
Other Authors: | |
Format: | Others |
Published: |
Monterey, California. Naval Postgraduate School
June
|
Subjects: | |
Online Access: | http://hdl.handle.net/10945/1181 |
id |
ndltd-nps.edu-oai-calhoun.nps.edu-10945-1181 |
---|---|
record_format |
oai_dc |
spelling |
ndltd-nps.edu-oai-calhoun.nps.edu-10945-11812017-05-24T16:06:51Z Aggregate models for target acquisition in urban terrain Mlakar, Joseph A. Rasmussen, Craig W. Cioppa, Thomas M. Phillips, Donovan Naval Postgraduate School Department of Applied Mathematics Department of Operations Research Urban warfare Markov processes Probability of line of sight Line of sight Urban target acquisition Cumulative distribution functions Markov chains Systems of differential equations Approved for public release, distribution is unlimited. High-resolution combat simulations that model urban combat currently use computationally expensive algorithms to represent urban target acquisition at the entity level. While this may be suitable for small-scale urban combat scenarios, simulation run time can become unacceptably long for larger scenarios. Consequently, there is a need for models that can lend insight into target acquisition in urban terrain for largescale scenarios in an acceptable length of time. This research develops urban target acquisition models that can be substituted for existing physicsbased or computationally expensive combat simulation algorithms and result in faster simulation run time with an acceptable loss of aggregate simulation accuracy. Specifically, this research explores (1) the adaptability of probability of line of sight estimates to urban terrain; (2) how cumulative distribution functions can be used to model the outcomes when a set of sensors is employed against a set of targets; (3) the uses for Markov Chains and Event Graphs to model the transition of a target among acquisition states; and (4) how a system of differential equations may be used to model the aggregate flow of targets from one acquisition state to another. Captain, United States Marine Corps June 2004 2012-03-14T17:30:49Z 2012-03-14T17:30:49Z 2004-06 Thesis http://hdl.handle.net/10945/1181 This 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. xviii, 134 p. : ill. (some col.), col. maps application/pdf Monterey, California. Naval Postgraduate School |
collection |
NDLTD |
format |
Others
|
sources |
NDLTD |
topic |
Urban warfare Markov processes Probability of line of sight Line of sight Urban target acquisition Cumulative distribution functions Markov chains Systems of differential equations |
spellingShingle |
Urban warfare Markov processes Probability of line of sight Line of sight Urban target acquisition Cumulative distribution functions Markov chains Systems of differential equations Mlakar, Joseph A. Aggregate models for target acquisition in urban terrain |
description |
Approved for public release, distribution is unlimited. === High-resolution combat simulations that model urban combat currently use computationally expensive algorithms to represent urban target acquisition at the entity level. While this may be suitable for small-scale urban combat scenarios, simulation run time can become unacceptably long for larger scenarios. Consequently, there is a need for models that can lend insight into target acquisition in urban terrain for largescale scenarios in an acceptable length of time. This research develops urban target acquisition models that can be substituted for existing physicsbased or computationally expensive combat simulation algorithms and result in faster simulation run time with an acceptable loss of aggregate simulation accuracy. Specifically, this research explores (1) the adaptability of probability of line of sight estimates to urban terrain; (2) how cumulative distribution functions can be used to model the outcomes when a set of sensors is employed against a set of targets; (3) the uses for Markov Chains and Event Graphs to model the transition of a target among acquisition states; and (4) how a system of differential equations may be used to model the aggregate flow of targets from one acquisition state to another. === Captain, United States Marine Corps |
author2 |
Rasmussen, Craig W. |
author_facet |
Rasmussen, Craig W. Mlakar, Joseph A. |
author |
Mlakar, Joseph A. |
author_sort |
Mlakar, Joseph A. |
title |
Aggregate models for target acquisition in urban terrain |
title_short |
Aggregate models for target acquisition in urban terrain |
title_full |
Aggregate models for target acquisition in urban terrain |
title_fullStr |
Aggregate models for target acquisition in urban terrain |
title_full_unstemmed |
Aggregate models for target acquisition in urban terrain |
title_sort |
aggregate models for target acquisition in urban terrain |
publisher |
Monterey, California. Naval Postgraduate School |
publishDate |
June |
url |
http://hdl.handle.net/10945/1181 |
work_keys_str_mv |
AT mlakarjosepha aggregatemodelsfortargetacquisitioninurbanterrain |
_version_ |
1718452432049012736 |