MUSIC like algorithms for fast Direction of Arrival estimation

This paper proposes two Unitary MUSIC-like algorithms, requiring only linear operations, for Directions of Arrival (DoAs) estimation problem. The constraints on the proposed algorithms are the same imposed onto the standard MUSIC algorithm allowing high resolution localisation capabilities with a reduced computation cost and lower processing time as compared to the existing schemes. We demonstrate that the introduced Orthogonal Decompositions (OD) technique, for noise subspace estimation, can efficiently replace the requirement of Singular Value Decomposition (SVD) or Eigenvalue Decomposition (EVD) which leads to a reduced computational complexity and makes the DoAs estimation faster while maintaining comparable estimation accuracy. The simulation results confirm that high resolution DoAs estimation can be achieved by the developed methods and prove the validity of our approach.