Application of sparse antenna arrays for increasing the degrees of freedom of direction-finding equipment

The sparse antenna arrays are started to receive the great attention nowadays. The virtualization algorithm, based on computation of difference co-array offers significant advantage in degrees-of-freedom and angular resolution of direction finding equipment. The difference co-array based method also can be applied to estimate direction of arrival of multiple signal sources, which number exceeds the number of antenna elements of array. This paper performs the comparative analysis of different types of linear sparse antenna arrays such as well-known minimum redundancy (MRA), minimum hole (MHA) and recently studied co-prime (CA) and Nested (NA) arrays. The analysis focuses on performance comparison of array factor and DOA estimation with spatial smoothing MUSIC algorithm for 8 antenna elements structures. Simulation results shown than sparse configurations considerably outperform classical uniform linear array (ULA) in array factor beamwidth but at the cost of increased sidelobe level. The consi¬dered types of sparse arrays also demonstrate significant difference of performance in DOA estimation: only half of types are capable of resolving 7 signal sources with angular separation of 5 degrees. As the result, the optimal array configuration is highlighted, as compromise between array dimensions and resolution capabilities.