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A Robust Image-Domain Subspace-Based Channel Error Calibration and Postimaging Reconstruction Algorithm for Multiple Azimuth Channels SAR
A Robust Image-Domain Subspace-Based Channel Error Calibration and Postimaging Reconstruction Algorithm for Multiple Azimuth Channels SAR
- Source :
- IEEE Transactions on Geoscience and Remote Sensing. 60:1-18
- Publication Year :
- 2022
- Publisher :
- Institute of Electrical and Electronics Engineers (IEEE), 2022.
-
Abstract
- High resolution and wide-swath imaging always suffer channel errors of the multiple azimuth channels (MACs) SAR. This paper presents an image-domain channel error estimation algorithm based on image subspace least square (ISPLS) method, and a post-imaging reconstruction algorithm for MACs SAR. The proposed method mainly consists of three parts: firstly, preprocessing and SAR imaging; secondly, the ISP-LSbased channel error estimation and calibration algorithm; thirdly, post-imaging reconstruction and ambiguity suppression. The channel phase and baseline errors are joint-estimated based on image subspace after SAR imaging, providing advantages that the higher SNR regions SAR images and the subspace method can be used to achieve a more accurate estimate with a relatively low computational load. We also propose a post-imaging reconstruction method for ambiguity suppression, which can realize imaging each channel data and then combining the multichannel SAR images. Simulated and acquired airborne SAR data are processed to demonstrate the effectiveness of the proposed method.
- Subjects :
- Computer science
business.industry
ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION
Phase (waves)
Reconstruction algorithm
Image (mathematics)
Azimuth
Computer Science::Computer Vision and Pattern Recognition
Calibration
General Earth and Planetary Sciences
Preprocessor
Computer vision
Artificial intelligence
Electrical and Electronic Engineering
business
Subspace topology
Communication channel
Subjects
Details
- ISSN :
- 15580644 and 01962892
- Volume :
- 60
- Database :
- OpenAIRE
- Journal :
- IEEE Transactions on Geoscience and Remote Sensing
- Accession number :
- edsair.doi...........71f3830ee8ef97f841494bea4d6ebe7b
- Full Text :
- https://doi.org/10.1109/tgrs.2021.3119457