Focusing-Based Wideband Adaptive Beamforming Using Covariance Matrix Reconstruction
Peng Chen, Wei Wang, Jingjie Gao
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Most focusing-based beamforming methods are devoted to solely focusing matrix designing, which aims to minimize the overall focusing error. However, these methods may suffer from performance degradation when steering vector (SV) error exists. To maximize the overall performance of focusing-based beamformer, this paper presents an adaptive focusing transformation-based beamforming algorithm using covariance matrix reconstruction. We first design a data-based focusing matrix of each frequency bin by assuming the Capon spectrum as the probability density function (PDF) of the incident signals. Then, the focused interference-plus-noise covariance matrix (INCM) can be reconstructed and the SV of desired signal is corrected. The above procedure not only decrease the focusing error based on the received signal, but also enhance the beamformer performance when there are SV mismatches, especially when the signal-to-noise ratio (SNR) is high.
Chairs:
Nuria Gonzalez Prelcic