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Optimal Design and Real-time Implementation of a Cooperative Guidance Algorithm against a Flying Vehicle

Motie, Mahyar | 2013

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 44509 (45)
  4. University: Sharif University of Technology
  5. Department: Aerospace Engineering
  6. Advisor(s): Nobahari, Hadi
  7. Abstract:
  8. A cooperative aerial system to defense a Ground Station (GS), against an Incoming aerial Targets (IT) is presented. GS is surrounded by given terrains and a group of homogenous Unmanned Aerial Vehicles (UAVs) are employed using a novel online guidance algorithm in a decentralized manner. The proposed algorithm includes loiter, midcourse and terminal phases. During loiter; UAVs follow an optimal circular path. IT is supposed to approach GS along an optimal low altitude trajectory with respect to the terrains. UAVs are informed the initial position and velocity of IT and they are unaware of IT trajectory. Each UAV decides on whether to engage with IT or not, and shares its decision with other UAVs. During midcourse phase, UAVs use a new online three-dimensional terrain following/avoidance algorithm to cooperatively plan their paths in such a way to increase the probability of cooperative target observation and interception. This algorithm is based on online optimization of a set of waypoints using a metaheuristic, called continuous ant colony system. A fuzzy combination of Proportional Navigation (PN) and pursuit guidance are used in both loiter and midcourse phases to track the planned trajectory. When IT is located within the seeker range of a UAV, the IT information is shared with other engaged UAVs. In the terminal phase, each engaged UAV uses PN to intercept the target. To optimize the design parameters of the new cooperative defense system, another metaheuristic, called tabu continuous ant colony system, is used with the purpose of minimizing the number of lost UAVs as well as the final miss distance and maximizing the probability of success. The performance of the proposed optimal three-phase cooperative guidance strategy is then evaluated in different engagement scenarios and compared with that of the non-cooperative case. Finally, hte numerical results show the effectiveness of the cooperative strategy
  9. Keywords:
  10. Cooperative Guidance Algorithm ; Unmanned Aerial Vehicles (UAV) ; Continuous Ant Colony System ; Three Dimentional Path Planning ; Terrain Following Avoidance ; Online Path Planning ; Optimization ; True Proportional Guidance

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