Anti-Jamming for UAVs using Artificial Intelligence based Swarm  Behavior

Silva,Tiago Alexandre Sousa

http://hdl.handle.net/10400.26/59810

Use this identifier to reference this record.

Name:	Description:	Size:	Format:
Tese 196 Silva.pdf		2.85 MB	Adobe PDF	Download

Send Feedback

Authors

Silva,Tiago Alexandre Sousa

Advisor(s)

Grilo, António Manuel Raminhos Cordeiro

Abstract(s)

The use of Unmanned Aerial Vehicles (UAVs) has seen remarkable growth in the performance of strategic tasks, both in civilian and military environments. This research, therefore, sets out to study the effectiveness of Anti-Jamming methods for UAVs supported by Artificial Intelligence based Swarm Behavior compared to conven tional methods. This work, therefore, provides an essential theoretical framework for understanding the proposed research, conducting a detailed study of the state of the art in the field of Unmanned Aerial Vehicles and Electronic Warfare. In addition, it highlights the fundamental tools required to carry out the research effectively, ranging from realistic UAV antenna models to advanced weapon intelligence techniques. Several experimental tests and simulations were carried out to validate the hypotheses formulated, allowing concrete results to be obtained that demonstrate the effectiveness of the proposed strategies. The results show that using a genetic approach can achieve effective results, although they are often costly regarding simulation time. In contrast, the Reinforcement Learning (RL) approach shows assertive results when pre-trained with realistic data in a helpful simulation time. The results obtained not only corroborate the viability of the theoretical approaches developed but also provide valuable parameters for future research and practical applications in the field of defence and security.