- 标题
- 摘要
- 关键词
- 实验方案
- 产品
-
Phase Difference Measurement of Under-Sampled Sinusoidal Signals for InSAR System Phase Error Calibration
摘要： Phase di?erence measurement of sinusoidal signals can be used for phase error calibration of the spaceborne single-pass interferometric synthetic aperture radar (InSAR) system. However, there are currently very few papers devoted to the discussion of phase di?erence measurement of high-frequency internal calibration signals of the InSAR system, especially the discussion of sampling frequency selection and the corresponding measuring method when the high-frequency signals are sampled under the under-sampling condition. To solve this problem, a phase di?erence measurement method for high-frequency sinusoidal signals is proposed, and the corresponding sampling frequency selection criteria under the under-sampling condition is determined. First, according to the selection criteria, the appropriate under-sampling frequency was chosen to sample the two sinusoidal signals with the same frequency. Then, the sampled signals were ?ltered by limited recursive average ?ltering (LRAF) and coherently accumulated in the cycle of the baseband signal. Third, the ?ltered and accumulated signals were used to calculate the phase di?erence of the two sinusoidal signals using the discrete Fourier transform (DFT), digital correlation (DC), and Hilbert transform (HT)-based methods. Lastly, the measurement accuracy of the three methods were compared respectively by di?erent simulation experiments. Theoretical analysis and experiments veri?ed the e?ectiveness of the proposed method for the phase error calibration of the InSAR system.
关键词： interferometric synthetic aperture radar (InSAR),under-sampling,phase di?erence measurement,coherent accumulation,phase error calibration
更新于2025-09-12 10:27:22
-
[IEEE IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Valencia, Spain (2018.7.22-2018.7.27)] IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Investigation of Tandem-x Penetration Depth Over the Greenland Ice Sheet
摘要： Ongoing global warming causes dramatic changes globally, especially with respect to Polar Regions. In this context, digital elevation data is of high importance for most glaciological applications. In this paper, we investigate TanDEM-X penetration depth over snow and ice on the Greenland ice sheet. In particular, the relation of backscatter intensity and interferometric coherence to penetration depth of the X-band InSAR signal is explored in order to improve the reliability of TanDEM-X elevation data. The analyses showed a distinct relationship of backscatter intensity, coherence and penetration depth. In addition, the influence of the height of ambiguity of the interferometric TanDEM-X data is presented. On an experimental test site in Northern Greenland, we demonstrated the estimation of TanDEM-X penetration depth based on backscatter intensity and interferometric coherence utilizing a linear regression model.
关键词： TanDEM-X,Interferometric Synthetic Aperture Radar (InSAR),Greenland ice sheet,penetration depth
更新于2025-09-10 09:29:36
-
[IEEE IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Valencia, Spain (2018.7.22-2018.7.27)] IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Extended Puma Algorithm for Multibaseline SAR Interferograms
摘要： Phase unwrapping (PU) is one of the key process in reconstructing the digital elevation model (DEM) of a scene from its interferometric synthetic aperture radar (InSAR) data. Compared with traditional single-baseline PU, the multibaseline PU does not need to obey the phase continuity assumption, which can be applicable to reconstruct the DEM where topography varies drastically. However, the performance of the multibaseline PU is directly concerned with noise level. Contrarily, the single-baseline PU algorithm has good noise robustness, since it is based on the globe wrapped phase information, such as PU-max-flow (PUMA) algorithm. In order to improve the noise robustness of the multibaseline, in this paper, we extend single-baseline PUMA algorithm to multibaseline domain, referred to as multibaseline PUMA algorithm, which allows the unwrapping of multibaseline interferograms for the generation of DEM. The proposed algorithm does not need to obey the phase continuity assumption by taking the advantages of multibaseline diversity and improves the noise robustness by using the global wrapped information both from single- and multibaseline domain. The performance of the proposed algorithm is tested on simulated InSAR data experiments, which demonstrate the effectiveness and noise robustness of the proposed algorithm.
关键词： Robust,Multibaseline,Phase unwrapping-max-flow (PUMA),Interferometric synthetic aperture radar (InSAR)
更新于2025-09-10 09:29:36
-
Underlying Topography Estimation Over Forest Areas Using Single-Baseline InSAR Data
摘要： In this paper, a method for digital elevation model (DEM) extraction over forest areas from single-baseline interferometric synthetic aperture radar (InSAR) data is proposed. The main idea of this method is that some backscattering variations which are linked to the geometrical structures of forest occur during the radar acquisition. The time–frequency analysis is used to retrieve these variations by dividing the synthesized SAR image into multiple SAR images in the Fourier domain called sublook images. Then, by interferometry, the sublook images characterized by the same Doppler bandwidth and acquired from spatially separated locations at either end of a baseline are used to estimate the sublook coherences and the above backscattering variations are converted into the variations the number of InSAR of sublook coherences. As a result, observations can be increased. The sublook coherences are then interpreted by the two-layer vegetation scattering model and are assumed to follow a near-linear relationship in the complex plane. The ground phase can then be estimated by linear regression of the sublook coherences. The performance of the proposed method was validated by E-SAR L- and P-band SAR data acquired over coniferous and tropical forests. For the coniferous scenario, the underlying DEM estimated by the proposed method has a root-mean-square error (RMSE) of 4.39 m, which is slightly less accurate than the DEM (with an RMSE of 4.07 m) derived by the polarimetric line-?t (LF) method, but represents a signi?cant improvement in DEM accuracy over the HH InSAR method. For the tropical scenario, the DEMs derived by the proposed method and the polarimetric LF method are closer to the ground surface than those derived by the HH InSAR method, and their mean ground height difference is 0.62 m. The two experiments con?rm that it is feasible to extract a DEM by the proposed method, which has a comparable performance in DEM inversion to the polarimetric LF method and only requires single-polarization InSAR data.
关键词： time–frequency (TF) analysis,underlying topography,two-layer vegetation scattering model,Interferometric synthetic aperture radar (InSAR)
更新于2025-09-10 09:29:36
-
[IEEE 2018 China International SAR Symposium (CISS) - Shanghai, China (2018.10.10-2018.10.12)] 2018 China International SAR Symposium (CISS) - A Novel Beam-Steering Method for Spaceborne Interferometric Synthetic Aperture Radar Altimeter
摘要： The Spaceborne altimeter based on Interferometric Synthetic Aperture Radar (InSAR) can achieve high-resolution, wide-swath and high-accuracy height measurement of sea surface. The beam steering of the SAR systems in orbit is designed to access SAR images with the same noise equivalent sigma zero (NESZ) for near-range and far-range observation areas. However, for InSAR altimeters, the conventional method would result in the height accuracy of near-range areas much higher than the far-range ones. To achieve the required height accuracy in far-range areas, the SAR systems have to improve the transmission power or increase the size of antenna, improving the complexity in system designation. In this paper, a novel beam-steering method for spaceborne InSAR altimeters is proposed. The beam-steering angle is optimized according to the height accuracy in the whole scene. The performance of the proposed method over the conventional method is validated by the simulation.
关键词： Beam steering,Radar altimeter,Interferometric Synthetic Aperture Radar (InSAR)
更新于2025-09-09 09:28:46
-
Interferometric Angular Decorrelation Analysis of 1-D Rough Surface With Pencil Beam Incidence
摘要： Interferometric synthetic aperture radar (InSAR) uses phase difference of radar echoes, either from multiple passes along the same trajectory or from multiple displaced phase centers on a single pass, to generate interferogram. Scattering correlation in the angular dimension is a critical factor determining the quality of InSAR interferogram. It can be modeled with the angular correlation function (ACF). In this letter, the ACF of a 1-D rough surface under incidence of a tapered wave, namely, a pencil beam, is studied numerically for correlation analysis of InSAR. An analytic ACF is ?rst derived based on the ?rst-order small perturbation method. It is then validated statistically by the method of moment of electromagnetic scattering. Analysis of the ACF simulations indicate that the ACF of backscattering from a randomly rough surface exhibits a shape of sinc function, which depends on tapering parameter g, interferometric incidence angles θ1 and θ2. Several numerical simulations of different rough surface spectrums demonstrate that the analytical ACF ?ts well with numerical results as long as g is the larger several correlation lengths l.
关键词： interferometric synthetic aperture radar (InSAR),Angular correlation function (ACF),small perturbation method (SPM),surface roughness
更新于2025-09-09 09:28:46
-
[Lecture Notes in Computer Science] Neural Information Processing Volume 11301 (25th International Conference, ICONIP 2018, Siem Reap, Cambodia, December 13-16, 2018, Proceedings, Part I) || Proposal of Complex-Valued Convolutional Neural Networks for Similar Land-Shape Discovery in Interferometric Synthetic Aperture Radar
摘要： We propose a complex-valued convolutional neural network to extract the areas having land shapes similar to samples in interferometric synthetic aperture radar (InSAR). InSAR extends its application to various earth observations such as volcano monitoring and earthquake damage estimation. Since the amount of data is increasing drastically in these years, it is necessary to structurize them in a big data framework. In this paper, experiments demonstrate that similar small volcanoes are grouped into a single class. We ?nd that the neural network is capable of discovering unidenti?ed lands similar to prepared samples successfully.
关键词： Complex-valued neural network (CVNN),Interferometric synthetic aperture radar (InSAR),Feature discovery
更新于2025-09-04 15:30:14