Online Netted Threat-Avoidance Guidance of UAVs

Presence of threats in the UAV’s operational environment may challenge the mission success by putting in danger the vehicle’s safety. Aimed at developing an efficient online guidance algorithm to avoid netted threats, this research proposes a novel method which incorporates the flying vehicle dynamics directly into the guidance strategy. Unlike almost all existing works, the proposed algorithm does not generate the flight path directly, instead determines appropriate guidance commands (GCs) for control system at every point along the way. The GCs are generated in accordance with the current conditions. A suitable 3DOF point mass UAV dynamic model is developed which takes the lags in the vehicle dynamics into account. The flight path forms gradually as a result of applying the GCs to the vehicle dynamics. The UAV guidance problem is considered within a fuzzy behavior-based framework. Two independent behaviors are introduced, namely, go-to-target and threat avoidance. The issued commands of these behaviors are integrated with adjustable weighting factors. Simulation results demonstrate that proposed approach is efficient and works very well.