Low-Complexity Robust Adaptive Beamforming Based on INCM Reconstruction via Subspace Projection

Adaptive beamforming is sensitive to steering vector (SV) and covariance matrix mismatches, especially when the signal of interest (SOI) component exists in the training sequence. In this paper, we present a low-complexity robust adaptive beamforming (RAB) method based on an interference–noise covariance matrix (INCM) reconstruction and SOI SV estimation. First, the proposed method employs the minimum mean square error criterion to construct the blocking matrix. Then, the projection matrix is obtained by projecting the blocking matrix onto the signal subspace of the sample covariance matrix (SCM). The INCM is reconstructed by replacing part of the eigenvector columns of the SCM with the corresponding eigenvectors of the projection matrix. On the other hand, the SOI SV is estimated via the iterative mismatch approximation method. The proposed method only needs to know the priori-knowledge of the array geometry and angular region where the SOI is located. The simulation results showed that the proposed method can deal with multiple types of mismatches, while taking into account both low complexity and high robustness.

Dual-Mic Speech Enhancement Based on TF-GSC with Leakage Suppression and Signal Recovery

The transfer function-generalized sidelobe canceller (TF-GSC) is one of the most popular structures for the adaptive beamformer used in multi-channel speech enhancement. Although the TF-GSC has shown decent performance, a certain amount of steering error is inevitable, which causes leakage of speech components through the blocking matrix (BM) and distortion in the fixed beamformer (FBF) output. In this paper, we propose to suppress the leaked signal in the output of the BM and restore the desired signal in the FBF output of the TF-GSC. To reduce the risk of attenuating speech in the adaptive noise canceller (ANC), the speech component in the output of the BM is suppressed by applying a gain function similar to the square-root Wiener filter, assuming that a certain portion of the desired speech should be leaked into the BM output. Additionally, we propose to restore the attenuated desired signal in the FBF output by adding some of the microphone signal components back, depending on how microphone signals are related to the FBF and BM outputs. The experimental results showed that the proposed TF-GSC outperformed conventional TF-GSC in terms of the perceptual evaluation of speech quality (PESQ) scores under various noise conditions and the direction of arrivals for the desired and interfering sources.

Research on Space-time Blocking Matrix Algorithm Based on Frequency Diverse Array

Because the beam pattern of the conventional phased array or MIMO radar is only related to the angle dimension, it is difficult to suppress the incident interference when it is in the mainlobe or at the same angle of the desired signal. According to the development demand of mainlobe anti-interference technology. In this paper, a space - time blocking matrix processing algorithm based on FDA is proposed. The algorithm gives the specific structure of the blocking matrix, which can not only avoid the interference of the same angle and different distances, but also eliminate the interference signal in the direction of the mainlobe without affecting the energy of other incident signals, so as to ensure the good shape of the beam pattern. The simulation results show that the algorithm can successfully suppress the mainlobe interference and has good beam-conformal.