  We present a MUSIC-based Direction of Arrival (DOA) estimation strategy using
small antenna arrays, via employing deep learning for reconstructing the
signals of a virtual large antenna array. Not only does the proposed strategy
deliver significantly better performance than simply plugging the incoming
signals into MUSIC, but surprisingly, the performance is also better than
directly using an actual large antenna array with MUSIC for high angle ranges
and low test SNR values. We further analyze the best choice for the training
SNR as a function of the test SNR, and observe dramatic changes in the behavior
of this function for different angle ranges.
