Improved Variational Bayes for Space-Time Adaptive Processing
To tackle the challenge of enhancing moving target detection performance in environments characterized by small sample sizes and non-uniformity, methods rooted in sparse signal reconstruction have been incorporated into Space-Time Adaptive Processing (STAP) algorithms. Given the prominent sparse nat...
Saved in:
| Main Authors: | Kun Li, Jinyang Luo, Peng Li, Guisheng Liao, Zhixiang Huang, Lixia Yang |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-02-01
|
| Series: | Entropy |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1099-4300/27/3/242 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
A Factor Graph Approach to Variational Sparse Gaussian Processes
by: Hoang Minh Huu Nguyen, et al.
Published: (2025-01-01) -
Electromagnetic Source Imaging With a Combination of Sparse Bayesian Learning and Deep Neural Network
by: Jiawen Liang, et al.
Published: (2023-01-01) -
Distributed variational sparse Bayesian compressed sensing based on factor graphs
by: Cui-tao ZHU, et al.
Published: (2014-01-01) -
Integrated Model Selection and Scalability in Functional Data Analysis Through Bayesian Learning
by: Wenzheng Tao, et al.
Published: (2025-04-01) -
Rapid, comprehensive search of crystalline phases from X-ray diffraction in seconds via GPU-accelerated Bayesian variational inference
by: Ryo Murakami, et al.
Published: (2025-12-01)