On the Efficient Implementation of Sparse Bayesian Learning-Based STAP Algorithms

On the Efficient Implementation of Sparse Bayesian Learning-Based STAP Algorithms

Sparse Bayesian learning-based space–time adaptive processing (SBL-STAP) algorithms can achieve superior clutter suppression performance with limited training sample support in practical heterogeneous and non-stationary clutter environments. However, when the system has high degrees of freedom (DOFs...

Full description

Bibliographic Details
Main Authors: Kun Liu, Tong Wang, Jianxin Wu, Cheng Liu, Weichen Cui
Format: Article
Language:English
Published: MDPI AG 2022-08-01
Series:Remote Sensing
Subjects:
clutter suppression
Gohberg–Semencul factorization
space–time adaptive processing
sparse Bayesian learning
Online Access:https://www.mdpi.com/2072-4292/14/16/3931

Internet

https://www.mdpi.com/2072-4292/14/16/3931

Similar Items