Enhanced UAVs mobility models for surveillance and intruders detection missions

Abstract

The use of chaotic solutions in designing UAVs’ (Unmanned Aerial Vehicles) mobility models for surveillance systems is becoming the trend in the last years. The substitution of the random part by a chaotic solution of a dynamic system has proven to be more effective. Therefore, this paper presents CSC (Chaotic Squad Coordination), a novel implementation scheme of UAVs mobility models in surveillance and intruders detection missions. The CSC comes as a low-cost solution to make the UAVs swarm efficiently explore the area of interest and detect malicious intruders, all in a spontaneous manner using a chaotic solution without the need for energy-consuming approaches like the ACO algorithm or deterministic group flocking rules. The used strategy guards the swarm’s movement unpredictability and offers the possibility of implementing a scalable collision avoidance flight plan. In addition, we designed a hybrid chaotic mobility model that switches between two chaotic attractors (Rossler and Ma systems). We used an iterative evolutionary algorithm to optimize its parameters in order to improve the overall delivered quality of service. Extensive simulation experiments are provided in this work to compare seven UAVs chaotic mobility models. The results confirmed the superiority of the CSC strategy that produced better quality of service concerning the swarm’s connectivity, the area coverage, and intruders detection, where the designed mobility model provides an overall reasonable trade-off in parallel with its higher area coverage fairness compared with its peers (CSC-based mobility models)