A new technique is proposed to reduce the computational complexity of the multiple signal classification (MUSIC)\nalgorithm for direction-of-arrival (DOA) estimate using a uniform linear array (ULA). The steering vector of the ULA is\nreconstructed as the Kronecker product of two other steering vectors, and a new cost function with spatial aliasing at\nhand is derived. Thanks to the estimation ambiguity of this spatial aliasing, mirror angles mathematically relating to\nthe true DOAs are generated, based on which the full spectral search involved in the MUSIC algorithm is highly\ncompressed into a limited angular sector accordingly. Further complexity analysis and performance studies are\nconducted by computer simulations, which demonstrate that the proposed estimator requires an extremely reduced\ncomputational burden while it shows a similar accuracy to the standard MUSIC
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