1 August 2016 Multiple mainlobe interferences suppression based on subspace matrix filtering and covariance matrix reconstruction
Author Affiliations +
Abstract
In order to suppress multiple mainlobe interferences and sidelobe interferences simultaneously, a mainlobe interference suppression algorithm is proposed. In this algorithm, the number of mainlobe interferences is estimated through a matrix filter at first. Then, the eigenvectors associated with mainlobe interference are determined and the eigen-projection matrix can be calculated. Next, the sidelobe-interference-plus-noise covariance matrix is reconstructed through eigenvalue replacement procedure. Finally, we can get the adaptive weight vector. Simulation results demonstrate the effectiveness of the proposed method when multiple mainlobe interferences exist.
© 2016 Society of Photo-Optical Instrumentation Engineers (SPIE)
Yasen Wang, Yasen Wang, Qinglong Bao, Qinglong Bao, Zengping Chen, Zengping Chen, } "Multiple mainlobe interferences suppression based on subspace matrix filtering and covariance matrix reconstruction," Journal of Applied Remote Sensing 10(3), 035008 (1 August 2016). https://doi.org/10.1117/1.JRS.10.035008 . Submission:
JOURNAL ARTICLE
8 PAGES


SHARE
Back to Top