Date of Award
3-2002
Document Type
Thesis
Degree Name
Master of Science
Department
Department of Operational Sciences
First Advisor
Kenneth W. Bauer, Jr., PhD
Abstract
There are two basic ways to control an Unmanned Combat Aerial Vehicle (UCAV) as it searches for targets: allow the UCAV to act autonomously or employ man-in-the-loop control. There are also two target sets of interest: fixed or mobile targets. This research focuses on UCAV-based targeting of mobile targets using man-in-the-loop control. In particular, the interest is in how levels of satellite signal latency or signal degradation affect the ability to accurately track, target, and attack mobile targets. This research establishes a weapon effectiveness model assessing targeting inaccuracies as a function of signal latency and/or signal degradation. The research involved three phases. The first phase in the research was to identify the levels of signal latency associated with satellite communications. A literature review, supplemented by interviews with UAV operators, provided insight into the expected range latency values. The second phase of the research identified those factors whose value, in the presence of satellite signal latency, could influence targeting errors during UCAV employment. The final phase involved developing and testing a weapon effectiveness model explicitly modeling satellite signal latency in UCAV targeting against mobile targets. This phase included an effectiveness analysis study.
AFIT Designator
AFIT-GOR-ENS-02-07
DTIC Accession Number
ADA399968
Recommended Citation
Flietstra, Timothy D., "An Integrated Architecture and Feature Selection Algorithm for Radial Basis Neural Networks" (2002). Theses and Dissertations. 4513.
https://scholar.afit.edu/etd/4513