Performance Evaluation of 1D DoA Estimation for DECOM and UCLA Using MUSIC Algorithm

Sparse arrays are gaining a lot of consideration due to their ability to increase degrees of freedom of an array, an aspect that allows for resolving of more sources than the number of sensor elements. In this paper direction of arrival estimation for coprime linear arrays using multiple signal classification algorithm is presented. Two super-resolution methods namely decompose and combine as well as unfolded coprime linear array are considered with an aim of putting forth an in-depth performance comparison of the two. Both methods analyses nonuniform linear array by first, decomposing it according to its coprime integer pair to form two independent sub-arrays 1 and 2, proceeded by application of the estimation algorithm. Although decompose and combine method ensures computational simplicity since it considers either of the decomposed sub-arrays separately, its resolution and performance efficiency is lower compared to unfolded coprime linear array method which uses the two sub-array data simultaneously thereby preserving the intrinsic mutual information of the array, an aspect that is lost in the former method.