Upload
eileen-johns
View
217
Download
0
Embed Size (px)
Citation preview
Artificial Intelligence in the Military
Presented by
Carson English, Jason Lukis,
Nathan Morse and Nathan Swanson
Overview
• History
• Neural Networks
• Automated Target Discrimination
• Tomahawk Missile Navigation
• Ethical issues
History
• 1918 – first tests on guided missiles
• 1945 – Germany makes first ballistic missile
• 1950 – AIM-7 Sparrow– “fire-and-forget
History
• 1973 – remotely piloted vehicles (RPVs)– Used to confuse enemy air defenses
• 1983 – tomahawk missile first used by navy– Uses terrain contour matching system
• 1983 – Reagan make his famous star wars speech• 1988 – U.S.S. Vincennes mistakenly destroys
Iranian airbus due to autonomous friend/foe radar system
History
• 1991 – Smart bombs used in Gulf War to selectively destroy enemy targets– Praised for its precision and effectiveness
Neural Networks
• Inspired by studies of the brain
• Massively parallel
• Highly connected
• Many simple units
Structure of a neuron in a neural net
Neural net with three neuron layers
Three Main Neural Net Types
• Perceptron
• Multi-Layer-Perceptron
• Backpropagation Net
Perceptron
Multi-Layer-Perceptron
Backpropagation Net
· pattern association · pattern classification · regularity detection · image processing · speech analysis · optimization problems · robot steering · processing of inaccurate or incomplete inputs · quality assurance · simulation
Areas where neural nets are useful
• the operational problem encountered when attempting to simulate the parallelism of neural networks
• inability to explain any results that they obtain
Limits to Neural Networks
Automated Target Discrimination
• SAR (Synthetic Aperture Radar)
• CFAR (Constant False Alarm Rate)
• QGD (Quadratic Gamma discriminator)
• NL-QGD (multi-layer perceptron)
• Example
• Results
As researched by the Computational NeuroEngineering Laboratory in Gainsville, FL
Synthetic Aperture Radar
• Data collection for ATD
• Self-illuminating imaging radar
• Creates a height map of a surface
• Maintains spatial resolution regardless of distance from target
• Can be used day and night regardless of cloud cover
Picture of SAR rendering
Two Constant False Alarm method for determining targets
Quadratic Gamma discrimination
Non Linear QGD
Example
Results
• After training, all three discriminators were run on a data set representing 7km2 of terrain. Target detection threshold was set to 100%.
• CAFR resulted in 4,455 false alarms.
• QGD resulted in 385 false alrams.
• NL-QGD resulted in 232 false alarms.
Tomahawk Missile Navigation
• Missile contains a map of terrain
• Figures out its current position from percepts (radar & altimeter)
• Uses a modified Gaussian least square differential correction algorithm, a step size limitation filter, and a radial basis function
Radial Basis Function
Gaussian Least Square Correction
Necessary Condition
Sufficient Condition
Step size limitation filter
Weight matrix
Tolerence error = 10^-8
Ethics
• Accountability– Legal– Political– Example: Aegis defense system shoots down an Iranian
Airbus jetliner in 1988
• Use of AI in warfare• Ethics of Research and Development
– Potential uses– Military Funding of AI– Passing of the blame “just doing my job”
Sources
• “Target Discrimination in Synthetic Aperture Radar (SAR) using Artificial Neural Networks” Jose C. Principe, Munchurl Kim, John W. Fisher III. Computational NeuroEngineering Laboratory. EB-486 Electrical and Computer Engineering Department. University of Florida.
• Sandia National Laboratories. http://www.sandia.gov/radar/sar.html
• Jet Propulsion Laboratory: California Institute of Technology. http://southport.jpl.nasa.gov/desc/imagingradarv3.html
• Wageningen University, The Netherlands. http://www.gis.wau.nl/sar/sig/sar_intr.htm