@article{WANG2025, 
author = {Liyuan WANG and Huafeng HE and Yaomin HE and Xiaofei HAN and Zhen LI},
title = {Three-dimensional polarization filtering method of generalized oblique projection based on SVT},
year = {2025},
journal = {Journal of Beijing University of Aeronautics and Astronautics},
volume = {51},
number = {2},
pages = {633-643},
keywords = {array signal processing, oblique projection, low-rank matrix recovery, linearly constrained minimum variance, singular value thresholding operator},
url = {https://www.sciopen.com/article/10.13700/j.bh.1001-5965.2023.0019},
doi = {10.13700/j.bh.1001-5965.2023.0019},
abstract = {The generalized oblique projection filter has a “blind area of filtering” and is easily influenced by the estimation error of the noise covariance matrix in different noise backgrounds. To address these issues, a generalized oblique projection polarization-spatial domain joint filtering method based on singular value thresholding (SVT) was proposed. Firstly, based on the uniform circular array polarization-sensitive array, the received signal model of the array was established. Secondly, the three-dimensional polarization filter of the generalized oblique projection was designed by using the minimized interference constrained generalized oblique projection operator with minimal interference constraints. Then, under the condition of unknown interference parameters, a filtering weight vector calculation method based on SVT was proposed. Finally, through the theoretical analysis of the filter performance and the simulation comparison with three similar algorithms, the results show that the three-dimensional polarization filtering method of generalized oblique projection based on SVT can suppress interference and recover the target signal without estimating the noise covariance matrix.}
}