Article: An In-Orbit Measurement Method for Elevation Antenna Pattern of MEO Synthetic Aperture Radar Based on Nano Calibration Satellite
Remote Sensing. 2022 Feb. 05, v. 14, no. 3
2022
Abstract: The medium-Earth-orbit synthetic aperture radar (MEO-SAR) is deployed at orbit altitude above low-Earth-orbit synthetic aperture radar (LEO-SAR, around 2000 km) and below the geosynchronous orbit SAR (GEO-SAR, near 35786 km) to cover a wide swath, which ... ...
Abstract | The medium-Earth-orbit synthetic aperture radar (MEO-SAR) is deployed at orbit altitude above low-Earth-orbit synthetic aperture radar (LEO-SAR, around 2000 km) and below the geosynchronous orbit SAR (GEO-SAR, near 35786 km) to cover a wide swath, which is four to five times larger than LEO-SAR. Therefore, the measurement method for the LEO-SAR elevation antenna pattern using the SAR data acquired over the Amazon tropical rainforest (ground-based method), where the typical width of rainforest area is approximately 150 km, can hardly meet the requirement of a wide swath to determine the MEO-SAR antenna elevation pattern. Moreover, several new MEO-SAR systems are now proposed that will use low frequency, and the low frequency penetration characteristics may affect the elevation antenna pattern determination using homogenous distributed targets such as the Amazon rainforest. This paper proposes a novel space-based method for the in-orbit measurement of the elevation antenna pattern of MEO-SAR based on one nano calibration satellite mounted with a receiver. Through appropriate orbit design, the nano calibration satellite can fly across the entire MEO-SAR swath along the range direction, and the elevation antenna pattern envelope can be extracted from the data recorded by the receiver. Simulation work is performed to verify the feasibility of the proposed space-based method, and the measurement accuracy of this method is analyzed. |
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Keywords | altitude ; calibration ; satellites ; synthetic aperture radar ; tropical rain forests ; Amazonia |
Language | English |
Dates of publication | 2022-0205 |
Publishing place | Multidisciplinary Digital Publishing Institute |
Document type | Article |
ZDB-ID | 2513863-7 |
ISSN | 2072-4292 |
ISSN | 2072-4292 |
DOI | 10.3390/rs14030741 |
Database | NAL-Catalogue (AGRICOLA) |
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