Harmonic Frequency Estimation Algorithm based on ESPRIT and MSWF in Power System

This paper points out the deficiency in the current harmonic frequency estimation algorithm in power system. In order to improve the accuracy of detection and reduce the computational complexity, the study combined the ESPRIT algorithm with multistage Wiener filter (MSWF) recurrence to achieve fast estimation of harmonic frequency. Theoretical analysis and simulation experiment show that the algorithm had relatively low requirement for the amount of data, and demonstrated good frequency resolution characteristics and anti-jamming capability, which made it ideally suitable for harmonic analysis in power system.

Low-Complexity Robust Capon Beamforming Based on Reduced-Rank Technique

Existing robust Capon beamformers achieve robustness against steering vector errors at a high cost in terms of computational complexity. Computationally efficient robust Capon beamforming approach based on the reduced-rank technique is proposed in this paper. The proposed method projects the received data snapshots onto a lower dimensional subspace consisting of the matched filters of the multistage Wiener filter (MSWF). The subsequent adaptive beamforming will then be performed within this subspace. The combination of the benefit of the robust adaptive beamforming and the reduced-rank technique improves the performance on combating steering vector errors and lowering the computational complexity.