Real-valued MUSIC with Mirrored Angles Suppression for Direction of Arrival Estimation

MUSIC (MUltiple Signal Classification) algorithm is one of directions of arrival (DOAs) methods which has been the most widely studies and has many variants due to easy implementation, applicable to a variety of array geometries and ability to resolve closely spaced signals. However, the trade-off is that it involves complex-valued computation, especially, in the task of a matrix decomposition. To overcome the high complexity problem, the real-valued spatial search function called the mirrored angles mitigation MUSIC (MAM-MUSIC) is formulated. The unitary transformation method is used to transform the complex to real computation. The proposed MAM-MUSIC can mitigate the mirror peaks caused by the virtual array transformation (VAT-MUSIC) method. Thresholding the MAM-MUSIC spectrum is to suppress the mitigated mirror peaks providing a new search function named as the mirrored angles suppression MUSIC (MAS-MUSIC). Furthermore, complexity analysis comparison is given. Simulations are conducted to demonstrate the advantages of the proposed MAS-MUSIC algorithm which has lower computational complexity and similar performance to classical MUSIC and other existing methods, particularly without virtual mirrored angles.