Antenna Range Measurements for Airborne Remote Sensing Antennas

Gabler, Bernd; Kosc, Alicja; Limbach, Markus

doi:10.1049/cp.2018.1227

Cited by 2 publications

(3 citation statements)

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“…These per-element diagrams are assumed known. They will typically have been derived from the precise on-ground characterization of the antenna array [22]. The power of the complex diagram is the antenna gain.…”

Section: Acquisition Geometry and Response Modelmentioning

confidence: 99%

“…In each iteration,Ψ is pre-computed on the basis of the currently available parameter estimatesÔ. Ψ is then treated as a constant in the solution of (22) and new, refined model parameter estimates are obtained. This process is repeated for a fixed number of iterations (e.g., 10) or until the model parameters have converged.…”

Section: Model-based Calibrationmentioning

confidence: 99%

“…These derivatives are obtained numerically from the change in ∆Gain s e (az) when the current estimate G s e (az) is perturbed in each dimension. The system of Equation (22) used for minimization comprises three equations for each antenna element e, with one equation for each angular axis. In addition, it includes one equation corresponding to the constant unknown gain offset in each channel pq.…”

Section: Antenna Mispointingmentioning

confidence: 99%

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Robust, Model-Based External Calibration of Multi-Channel Airborne SAR Sensors Using Range Compressed Raw Data

2019

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The paper describes a method for the accurate calibration of multi-channel SAR instruments, such as those required to support SAR polarimetry, single-pass interferometry and digital beam-forming (DBF), on the basis of dedicated SAR acquisitions containing reference targets with known properties. Unlike conventional approaches, the method is based entirely on the analysis of range-compressed raw data. It leverages the pulse-by-pulse analysis of amplitude, phase and delay variations observed within the range histories of reference targets to fully characterize and correct propagation direction dependent calibration issues such as those related to antenna pointing or antenna phase center positions. The fact that the approach does not require SAR image focusing in azimuth is especially relevant in the context of DBF, where individual channels need to be calibrated but are, by themselves, under-sampled. The calibration techniques presented are illustrated and validated using multi-channel polarimetric and single-pass interferometric SAR data acquired by DLR’s airborne F-SAR and DBFSAR instruments.

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Section: Acquisition Geometry and Response Modelmentioning

confidence: 99%

Section: Model-based Calibrationmentioning

confidence: 99%

Section: Antenna Mispointingmentioning

confidence: 99%

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Robust, Model-Based External Calibration of Multi-Channel Airborne SAR Sensors Using Range Compressed Raw Data

2019

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Development of a device for monitoring and tuning radio-technical parameters of a satellite communications Earth station

Gladyshev

Дмитриев

Tyapkin

et al. 2020

J. Phys.: Conf. Ser.

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The article describes the existing methods for studying the characteristics of the antennas that are used in satellite earth stations. A variant of the device based on a spherical scanner is proposed. The spherical scanner uses the method of measuring the field in the near field. It has been established that for high efficiency and reduction of measurement time, it is necessary to use the spiral scanning method. The composition and block diagram of the device is presented. Recommendations on the use of software for processing measurement results are given.

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Antenna Range Measurements for Airborne Remote Sensing Antennas

Cited by 2 publications

References 0 publications

Robust, Model-Based External Calibration of Multi-Channel Airborne SAR Sensors Using Range Compressed Raw Data

Robust, Model-Based External Calibration of Multi-Channel Airborne SAR Sensors Using Range Compressed Raw Data

Development of a device for monitoring and tuning radio-technical parameters of a satellite communications Earth station

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