Direction of Arrival Estimation in Automotive Radar with Sailfish Optimization Algorithm

Direction of arrival (DOA) estimation in array signal processing has been studied extensively due to its potential applications. One key application is automotive radar, in which a only few snapshots or a single snapshot is applied for DOA estimation. In this paper, DOA estimation with a single snapshot is investigated using a recently reported meta-heuristics sailfish optimization algorithm. The sailfish optimization is influenced by the natural hunting process of sailfish to catch the prey (sardines). The objective is to maximize the maximum likelihood estimator fitness function with the sailfish optimization algorithm. The comparative analysis has been carried out with benchmark algorithms like Genetic Algorithm, Particle Swarm Optimization, and Differential Evolution under identical environments. Superior performance is reported by the sailfish algorithm in terms of convergence curve, box plot of accuracy, RMSE vs SNR plot compared to the other meta-heuristics.