Date of Award
3-2004
Document Type
Thesis
Degree Name
Master of Science in Computer Engineering
Department
Department of Electrical and Computer Engineering
First Advisor
Gary B. Lamont, PhD
Abstract
Current military affairs indicate that future military warfare requires safer, more accurate, and more fault-tolerant weapons systems. Unmanned Aerial Vehicles (UAV) are one answer to this military requirement. Technology in the UAV arena is moving toward smaller and more capable systems and is becoming available at a fraction of the cost. Exploiting the advances in these miniaturized flying vehicles is the aim of this research. How are the UAVs employed for the future military? The concept of operations for a micro-UAV system is adopted from nature from the appearance of flocking birds, movement of a school of fish, and swarming bees among others. All of these natural phenomena have a common thread: a global action resulting from many small individual actions. This "emergent behavior" is the aggregate result of many simple interactions occurring within the flock, school, or swarm. In a similar manner, a more robust weapon system uses emergent behavior resulting in no "weakest link" because the system itself is made up of simple interactions by hundreds or thousands of homogeneous UAVs. The global system in this research is referred to as a swarm. Losing one or a few individual unmanned vehicles would not dramatically impact the "swarms" ability to complete the mission or cause harm to any human operator. Swarming reconnaissance is the emergent behavior of swarms to perform a reconnaissance operation. An in-depth look at the design of a reconnaissance swarming mission is studied. A taxonomy of passive reconnaissance applications is developed to address feasibility. Evaluation of algorithms for swarm movement, communication, sensor input/analysis, targeting, and network topology result in priorities of each model's desired features. After a thorough selection process of available implementations, a subset of those models are integrated and built upon resulting in a simulation that explores the innovations of swarming UAVs.
AFIT Designator
AFIT-GCE-ENG-04-01
DTIC Accession Number
ADA426466
Recommended Citation
Corner, Joshua J., "Swarming Reconnaissance Using Unmanned Aerial Vehicles in a Parallel Discrete Event Simulation" (2004). Theses and Dissertations. 3977.
https://scholar.afit.edu/etd/3977
Included in
Controls and Control Theory Commons, Multi-Vehicle Systems and Air Traffic Control Commons