A review of different Sparse Arrays for DOA estimation using Subspace based algorithm

In this paper, a detailed review is carried out for different sparse array structures for direction-of-arrival (DOA) estimation. We know that there are different sparse arrays like the minimum redundancy array, minimum hole array, nested array, supernested array, coprime array, Cantor array etc. for DOA estimation. Here, we employ the spatial smoothing MUltiple SIgnal Classification (MUSIC) algorithm for DOA estimation. The spatial smoothing technique can be applied to the hole-free part of the difference coarray of the sparse array. We discuss the configuration of each of these arrays and look into the main properties of the arrays with their advantages and disadvantages. We also analyze the environment in which a particular array can be used to give its optimum performance. We then carry out the simulations to compare the performances of the arrays.