Direction of Arrival Estimation using Uniform Linear Sensor Array with Salp Swarm Optimizer.

Direction of arrival (DOA) estimation is a key problem in array signal processing and wireless communication. In this paper, the maximum likelihood estimation problem in wireless sensor networks is investigated using a recently reported yet popular meta-heuristic Salp Swarm Algorithm (SSA). The SSA was reported by Mirjalili et al in the year 2017, which is inspired by the hunting strategy adopted by the Salp Swarm to find their food source. This algorithm offers good accuracy in DOA estimation by maintaining an effective balance between the exploration and exploitation phases. Comparative analysis is carried out with other nature-inspired algorithms: Grey Wolf Optimizer (GWO), Moth Flame Optimizer (MFO), and Particle Swarm Optimizer (PSO). Superior results are reported by SSA for DOA estimation under different noisy scenarios compared to the benchmark algorithms in terms of RMSE values, convergence curves and box plots.