A Hybrid Bald Eagle Search Algorithm for Time Difference of Arrival Localization

The technology of wireless sensor networks (WSNs) is developing rapidly, and it has been applied in diverse fields, such as medicine, environmental control, climate prediction, monitoring, etc. Location one the critical fields WSNs. Time difference arrival (TDOA) widely used to locate targets because a simple model, easy implement. Aiming at problems large deviation low accuracy nonlinear equation solution for TDOA, many metaheuristic algorithms have proposed address problems. By analyzing available literature, can be seen that swarm intelligence achieved remarkable results this domain. aim paper achieve further improvements solving localization problem by TDOA. To goal, we hybrid bald eagle search (HBES) algorithm, which improve performance (BES) algorithm using strategies chaotic mapping, Lévy flight, opposition-based learning. evaluate HBES, compared HBES with particle butterfly optimization COOT Grey Wolf sine cosine based on 23 test functions. comparison show better than other reputable algorithms. Additionally, was solve TDOA location simulating deployment different quantities base stations noise situation. method obtain more consistent precise locations unknown target nodes others.