This work presents a field implementation of acoustic energy-based positioning, using Elephant Herding Optimization algorithm to solve the NP-hard optimization problem. Measurements are used to validate and adjust the decay acoustic model, and simulations are performed with an outdoor environment setup, where the implementation is fulfilled and compared with real acoustic measurements. The performance in both scenarios is studied, in terms of accuracy, with the variation of the number of sensors nodes used in the model. The field implementation shows that results are aligned with simulation ones, validating the acoustic model and the use of metaheuristic methods such as Elephant Herding Optimization for solving the localization problem.