Compensation for the mutual coupling effect in uniform circular arrays for 2D DOA estimations employing the maximum likelihood technique

An effective compensation method for the mutual coupling effect in uniform circular arrays (UCAs) employed for two-dimensional (2D) direction-of-arrival (DOA) estimations is introduced. A new 2D DOA searching algorithm using the maximum likelihood technique optimized by the emperor selective genetic algorithm (ML-EMSGA) is introduced for use with UCAs. This method circumvents the difficulty of dealing with coherent signals in 2D DOA estimations. ML-EMSGA is less computationally demanding than the maximum likelihood method (MLM) and statistically more efficient. Our study shows that ML-EMSGA can be effectively combined with the proposed compensation method, which is based on the introduction of a new mutual impedance, to give very accurate and robust 2D DOA estimation results. The structure of mutual impedance matrix for UCAs under the compensation method is fully explained. The theory of the ML-EMSGA for the UCAs is formulated. Computer simulation examples on several synthetic scenarios are presented to demonstrate the effectiveness of the mutual coupling compensation method and the superior performance of the ML-EMSGA for UCAs.