PRI-IGSS uses receive-power-based pre-rotation to an optimal initial direction followed by fixed-array iterative greedy search that accumulates sample covariance matrices to achieve lower complexity and mean-squared error closer to the CRLB than RR-Root-MUSIC.
Co-learning-aided multi-modal-deep-learni ng framework of passive doa estimators for a heterogeneous hybrid massiv e mimo receiver,
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Enhanced Direction-Sensing Methods and Performance Analysis in Low-Altitude Wireless Network via a Rotating Antenna Array
PRI-IGSS uses receive-power-based pre-rotation to an optimal initial direction followed by fixed-array iterative greedy search that accumulates sample covariance matrices to achieve lower complexity and mean-squared error closer to the CRLB than RR-Root-MUSIC.