Phase Calibration of an Along-Track Interferometric FMCW SAR

Deng, Huazeng; Farquharson, Gordon; Sahr, John D.; Goncharenko, Yuriy; Mower, John

doi:10.1109/tgrs.2018.2841837

Cited by 9 publications

(5 citation statements)

References 27 publications

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“…Since the phase information is also target-dependent, the influence of the phase noise is not critical for imaging applications with complicated targets such as GPR and near-range MMW imaging [19] [39]. The polluted IF signal with phase noise usually results in reduced imaging resolution and imaging artifacts [44]. Meanwhile, phase information becomes essential for advanced radar techniques such as polarization analysis.…”

Section: Appendix A: Phase Noise In If Signal and Imaging Resultsmentioning

confidence: 99%

See 1 more Smart Citation

Ultra-Wideband Frequency Modulated Continuous Wave Photonic Radar System for Three-Dimensional Terahertz Synthetic Aperture Radar Imaging

Kaname

Mizuno

et al. 2022

J. Lightwave Technol.

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Three-dimensional (3D) imaging remains an expensive and challenging task in the THz band. In this study, a frequency-modulated continuous-wave photonic radar system was presented in the 300-GHz band, instead of using electronic-based devices. The proposed system can obtain a 6-dB bandwidth of 120 GHz to achieve a range resolution of ~1.1 mm. The frequency sweep linearity of a laser source was calibrated with respect to the imaging distance and range resolution, through which a maximum detectable distance of ~800 mm was achieved with the collimated beam. To obtain the desired 3D information, the synthetic aperture radar (SAR) technique was introduced to the proposed system to achieve 3D imaging, which was not bounded by the fixed focal distance of a focus lens. It can provide a spatial resolution of ~1.5 mm within a 3D imaging range up to ~300 mm. The potential and limitations of SAR imaging schemes are discussed based on the theoretical and experimental results.

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Section: Appendix A: Phase Noise In If Signal and Imaging Resultsmentioning

confidence: 99%

“…In this case, observations with different polarization properties and phase calibration are required [45]. In the future, phase calibration will also be introduced to the proposed system to enhance the imaging resolution and/or to obtain doppler information [28] [44].…”

Section: Appendix A: Phase Noise In If Signal and Imaging Resultsmentioning

confidence: 99%

Ultra-Wideband Frequency Modulated Continuous Wave Photonic Radar System for Three-Dimensional Terahertz Synthetic Aperture Radar Imaging

Kaname

Mizuno

et al. 2022

J. Lightwave Technol.

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“…The residual error in the normalization is smaller than 1 dB stdev. The speckle noise [35] was nearly removed by averaging single looks at ∼ 7 m resolution over each field (∼ 800 m × 800 m). The measured backscattering coefficients are compared with the outputs from the data-cubes and also serve as the inputs for the time-series retrieval of the soil moisture, which will be illustrated in the later sections.…”

Section: Smapvex12 Campaignmentioning

confidence: 99%

L-Band Radar Scattering and Soil Moisture Retrieval of Wheat, Canola and Pasture Fields for Smap Active Algorithms

Huang¹,

Liao²,

Kim³

et al. 2021

PIER

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Wheat, canola, and pasture are three of the major vegetation types studied during the Soil Moisture Active Passive Validation Experiment 2012 (SMAPVEX12) conducted to support NASA's Soil Moisture Active Passive (SMAP) mission. The utilized model structure is integrated in the SMAP baseline active retrieval algorithm. Forward lookup tables (data-cubes) for VV and HH backscatters at L-band are developed for wheat and canola fields. The data-cubes have three axes: vegetation water content (VWC), root mean square (RMS) height of rough soil surface, and soil permittivity. The volume scattering and double-bounce scattering of the fields are calculated using the distorted Born approximation and the coherent reflectivity in the double-bounce scattering. The surface scattering is determined by the numerical solutions of Maxwell equations (NMM3D). The results of the datacubes are validated with airborne radar measurements collected during SMAPVEX12 for ten wheat fields, five canola fields, and three pasture fields. The results show good agreement between the datacube simulation and the airborne data. The root mean squared errors (RMSE) were 0.82 dB, 0.78 dB, and 1.62 dB for HH, and 0.97 dB, 1.30 dB, and 1.82 dB for VV of wheat, canola, and pasture fields, respectively. The data-cubes are next used to perform the time-series retrieval of the soil moisture. The RMSEs of the soil moisture retrieval are 0.043 cm 3 /cm 3 , 0.082 cm 3 /cm 3 , and 0.082 cm 3 /cm 3 for wheat, canola, and pasture fields, respectively. The results of this paper expand the scope of the SMAP baseline radar algorithm for wheat, canola, and pastures formed and provide a quantitative validation of its performance. It will also have applications for the upcoming NISAR (NASA-ISRO SAR Mission).

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“…The position (x, y, z) of the point target referenced to the scanning geometry can be estimated by applying the least squares curve fitting approaches [73] to the measured beat signal phase. These approaches directly result in an estimate of the target position by finding the set of parameters, which minimizes the squared error between the modeled and measured phase as {x,ŷ,ẑ} = arg max…”

Section: Mimo Array Calibrationmentioning

confidence: 99%

Development and Demonstration of MIMO-SAR mmWave Imaging Testbeds

2020

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Multiple-input multiple-output (MIMO) radars and synthetic aperture radar (SAR) techniques are well researched and have been effectively combined for many imaging applications ranging from remote sensing to security. Despite numerous studies that apply MIMO concepts to SAR imaging, the design process of a MIMO-SAR system is non-trivial, especially for millimeter-wave (mmWave) imaging systems. Many issues have to be carefully addressed. Besides, compared with conventional monostatic sampling schemes or MIMO-only solutions, efficient image reconstruction methods for MIMO-SAR topologies are more complicated in short-range applications. To address these issues, we present highly-integrated and reconfigurable MIMO-SAR testbeds, along with examples of three-dimensional (3-D) image reconstruction algorithms optimized for MIMO-SAR configurations. The presented testbeds utilize commercially available wideband mmWave sensors and motorized rail platforms. Several aspects of the MIMO-SAR testbed design process, including MIMO array calibration, electrical/mechanical synchronization, system-level verification, and performance evaluation, are described. We present three versions of MIMO-SAR testbeds with different implementation costs and accuracies to provide alternatives for other researchers who want to implement their testbed framework. Several representative examples in various real-world imaging applications are presented to demonstrate the capabilities of the proposed testbeds and algorithms. INDEX TERMS Millimeter-wave (mmWave) radar, multiple-input multiple-output (MIMO) radar, synthetic aperture radar (SAR), frequency-modulated continuous-wave (FMCW), back projection algorithm (BPA), range migration algorithm (RMA), three-dimensional (3-D) imaging, testbed design, calibration.

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Phase Calibration of an Along-Track Interferometric FMCW SAR

Cited by 9 publications

References 27 publications

Ultra-Wideband Frequency Modulated Continuous Wave Photonic Radar System for Three-Dimensional Terahertz Synthetic Aperture Radar Imaging

Ultra-Wideband Frequency Modulated Continuous Wave Photonic Radar System for Three-Dimensional Terahertz Synthetic Aperture Radar Imaging

L-Band Radar Scattering and Soil Moisture Retrieval of Wheat, Canola and Pasture Fields for Smap Active Algorithms

Development and Demonstration of MIMO-SAR mmWave Imaging Testbeds

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