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Bayesian Deconvolution for Angular Super-Resolution in Forward-Looking Scanning Radar

  • Published:2015-03-23 Issue:3 Volume:15 Page:6924-6946
  • ISSN:1424-8220
  • Container-title:Sensors
  • language:en
  • Short-container-title:Sensors

Author:

Zha Yuebo,Huang Yulin,Sun Zhichao,Wang Yue,Yang Jianyu

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Biochemistry,Instrumentation,Atomic and Molecular Physics, and Optics,Analytical Chemistry

Reference52 articles.

1. Two-Dimensional TSVD to Enhance the Spatial Resolution of Radiometer Data;Lenti;IEEE Trans. Geosci. Remote Sens,2014

2. Reconstruction of the Normalized Radar Cross Section Field From GNSS-R Delay-Doppler Map;Schiavulli;IEEE J. Sel.Top. Appl. Earth Obs. Remote Sens,2014

3. Using GNSS-R imaging of the ocean surface for oil slick detection;Valencia;IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens,2013

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2. A Parameter-Free Estimation Method Based on Low-Rank and Sparse Hybrid Constraints for Scanning Radar Forward-Looking Imaging;IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium;2024-07-07

3. Radar Forward-Looking Super-Resolution Imaging Algorithm of ITR-DTV Based on Renyi Entropy;IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing;2024

4. Scanning Radar Forward-Looking Imaging Under High-Speed Platform by Accurate Profile-Phase Deconvolution Method;IEEE Transactions on Geoscience and Remote Sensing;2024

5. Scanning Radar Super-Resolution Imaging for Sea Surface Target Based on a Novel Observation Model;2023 3rd International Conference on Electronic Information Engineering and Computer Science (EIECS);2023-09-22
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