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A High-Resolution SAR Focusing Experiment Based on GF-3 Staring Data
- Source :
- Sensors, Vol 18, Iss 4, p 943 (2018), Sensors; Volume 18; Issue 4; Pages: 943, Sensors (Basel, Switzerland)
- Publication Year :
- 2018
- Publisher :
- MDPI AG, 2018.
-
Abstract
- Spotlight synthetic aperture radar (SAR) is a proven technique, which can provide high-resolution images as compared to those produced by traditional stripmap SAR. This paper addresses a high-resolution SAR focusing experiment based on Gaofen-3 satellite (GF-3) staring data with about 55 cm azimuth resolution and 240 MHz range bandwidth. In staring spotlight (ST) mode, the antenna always illuminates the same scene on the ground, which can extend the synthetic aperture. Based on a two-step processing algorithm, some special aspects such as curved-orbit model error correction, stop-and-go correction, and antenna pattern demodulation must be considered in image focusing. We provide detailed descriptions of all these aspects and put forward corresponding solutions. Using these suggested methods directly in an imaging module without any modification for other data processing software can make the most of the existing ground data processor. Finally, actual data acquired in GF-3 ST mode is used to validate these methodologies, and a well-focused, high-resolution image is obtained as a result of this focusing experiment.
- Subjects :
- Synthetic aperture radar
stop-and-go
Computer science
0211 other engineering and technologies
SAR
GF-3
staring spotlight
two-step algorithm
curved orbit
antenna pattern
high-resolution
02 engineering and technology
lcsh:Chemical technology
01 natural sciences
Biochemistry
Article
Analytical Chemistry
Radiation pattern
Data processing system
Staring
Demodulation
lcsh:TP1-1185
Computer vision
Electrical and Electronic Engineering
Instrumentation
021101 geological & geomatics engineering
business.industry
010401 analytical chemistry
Bandwidth (signal processing)
Atomic and Molecular Physics, and Optics
0104 chemical sciences
Artificial intelligence
business
Subjects
Details
- ISSN :
- 14248220
- Volume :
- 18
- Database :
- OpenAIRE
- Journal :
- Sensors
- Accession number :
- edsair.doi.dedup.....6eb08caeb7839b9d1496285fcbdac98c