Multiple Mainlobe Interferences Suppression Based on Eigen-Subspace and Eigen-Oblique Projection

Sensors (Basel). 2022 Nov 4;22(21):8494. doi: 10.3390/s22218494.

Abstract

When the desired signal and multiple mainlobe interferences coexist in the received data, the performance of the current mainlobe interference suppression algorithms is severely challenged. This paper proposes a multiple mainlobe interference suppression method based on eigen-subspace and eigen-oblique projection to solve this problem. First, use the spatial spectrum algorithm to calculate interference power and direction. Next, reconstruct the eigen-subspace to accurately calculate the interference eigenvector, then generate the eigen-oblique projection matrix to suppress mainlobe interference and output the desired signal without distortion. Finally, the adaptive weight vector is calculated to suppress sidelobe interference. Through the above steps, the proposed method solves the problem that the mainlobe interference eigenvector is difficult to select, caused by the desired signal and the mismatch of the mainlobe interference steering vector and its eigenvector. The simulation result proves that our method could suppress interference more successfully than the former methods.

Keywords: adaptive beamforming; eigen-oblique; eigen-subspace; mainlobe interference suppression.

Grants and funding

This research received no external funding.