Share Email Print

Journal of Applied Remote Sensing

Multiple mainlobe interferences suppression based on subspace matrix filtering and covariance matrix reconstruction
Author(s): Yasen Wang; Qinglong Bao; Zengping Chen
Format Member Price Non-Member Price
PDF $20.00 $25.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper 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.

Paper Details

Date Published: 1 August 2016
PDF: 8 pages
J. Appl. Rem. Sens. 10(3) 035008 doi: 10.1117/1.JRS.10.035008
Published in: Journal of Applied Remote Sensing Volume 10, Issue 3
Show Author Affiliations
Yasen Wang, National Univ. of Defense Technology (China)
Qinglong Bao, National Univ. of Defense Technology (China)
Zengping Chen, National Univ. of Defense Technology (China)

© SPIE. Terms of Use
Back to Top