Electro-optical systems and neural-inspired processing: A system architecture and technology analysis with applications to law enforcement small arms fire indication systems

This dissertation is a transdisciplinary analysis on law-enforcement small arms indication systems. The technology focus is on electro-optical sensors and neural-inspired processing. Dual-color, high-rate, imaging, and high-performance indication systems are all evaluated. A platform-level design decomposition that starts with the customer needs and finishes with the sensor and processor requirements is performed; the requirements are then used for architecture and technology trade studies. To understand sensor solutions, the target phenomenology is studied, a model is developed, and a sensor performance analysis is conducted. To identify processing solutions, a baseline algorithm, using traditional digital signal processing techniques, is identified, its effectiveness is evaluated with stimuli generated from the target/sensor model, and then biological neural network are studied for opportunities to improve the processing. The result is a series of architectures that are evaluated against requirements derived from real-world scenarios. These developed architectures can be later matured into systems that can be used by law-enforcement for surveillance.

Grantor dc:publisher

Texas Tech University

Year dc:date.issued

2009

Author dc:creator

• Symeonidis, Simeon

Contributors dc:contributor

• Ertas, Atila
• Tate, Derrick
• Maxwell, Timothy T.
• Dallas, Timothy E. J.
• Barhorst, Alan

• Infrared sensors
• Small arms indication
• Neural networks

Statement dc:rights

• Unrestricted.

Language dc:language

eng

Identifier

http://hdl.handle.net/2346/18767

OAI identifier oai:identifier

oai:tdl-ir.tdl.org:2346/18767