Resolution Enhancement for Large-Scale Real Beam Mapping Based on Adaptive Low-Rank Approximation-Reference-Cited by-同舟云学术

Resolution Enhancement for Large-Scale Real Beam Mapping Based on Adaptive Low-Rank Approximation

Published:2022 Issue: Volume:60 Page:1-21
ISSN:0196-2892
Container-title:IEEE Transactions on Geoscience and Remote Sensing
language:
Short-container-title:IEEE Trans. Geosci. Remote Sensing

Author:

Zhang Yongchao¹^ORCID,Luo Jiawei²^ORCID,Zhang Yongwei²,Huang Yulin¹^ORCID,Cai Xiaochun²,Yang Jianyu²^ORCID,Mao Deqing²^ORCID,Li Jie²^ORCID,Tuo Xingyu²^ORCID,Zhang Yin¹^ORCID

Affiliation:

1. School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, China

2. School of Information and Communication Engineering, University of Electronic Science and Technology of China (UESTC), Chengdu, China

Funder

National Natural Science Foundation of China

Special Science Foundation of Quzhou

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Earth and Planetary Sciences,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/36/9633014/09875209.pdf?arnumber=9875209

Reference65 articles.

1. Low-Complexity RLS Algorithms Using Dichotomous Coordinate Descent Iterations

2. Nonparametric Missing Sample Spectral Analysis and Its Applications to Interrupted SAR

3. Range-Recursive IAA for Scanning Radar Angular Super-Resolution

4. A Fast Iterative Adaptive Approach for Scanning Radar Angular Superresolution

5. Fast Inverse-Scattering Reconstruction for Airborne High-Squint Radar Imagery Based on Doppler Centroid Compensation

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