Open AccessMainlobe Interference Suppression via Eigen-Projection Processing and Covariance Matrix Reconstruction in Array Antenna
Author(s) -
Bin Yang,
Weihua Li,
Si Li
Publication year - 2021
Publication title -
applied computational electromagnetics society journal
Language(s) - English
Resource type - Journals
eISSN - 1943-5711
pISSN - 1054-4887
DOI - 10.13052/2021.aces.j.361111
Subject(s) - covariance matrix , interference (communication) , algorithm , projection (relational algebra) , computer science , antenna (radio) , noise (video) , antenna array , array processing , matrix (chemical analysis) , signal (programming language) , signal processing , electronic engineering , telecommunications , engineering , artificial intelligence , channel (broadcasting) , radar , materials science , composite material , image (mathematics) , programming language
When the received data contains the desired signal, the performance of most mainlobe interference suppression methods is seriously degraded. To solve this problem, a novel mainlobe interference suppression method based on eigen-projection processing and covariance matrix reconstruction for array antenna is proposed in this paper. The method constructs the sidelobe interference plus noise covariance matrix (SINCM) and remove the mainlobe data of the covariance matrix. Then, it uses eigen-projection technology to remove the mainlobe interference in the received data and correct the SINCM to make the proposed method has better ability to suppress the mainlobe interference and sidelobe interference when the received data contains the desired signal. Simulation results demonstrate the superior performance of the proposed beamformer relative to other existing methods.