- 标题
- 摘要
- 关键词
- 实验方案
- 产品
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Polarimetric Interferometric SAR Change Detection Discrimination
摘要： A coherent change detection (CCD) image, computed from a geometrically matched, temporally separated pair of complex-valued synthetic aperture radar (SAR) image sets, conveys the pixel-level equivalence between the two observations. Low-coherence values in a CCD image are typically due to either some physical change in the corresponding pixels or a low signal-to-noise observation. A CCD image does not directly convey the nature of the change that occurred to cause low coherence. In this paper, we introduce a mathematical framework for discriminating between different types of change within a CCD image. We utilize the extra degrees of freedom and information from polarimetric interferometric SAR (PolInSAR) data and PolInSAR processing techniques to define a 29-dimensional feature vector that contains information capable of discriminating between different types of change in a scene. We also propose two change-type discrimination functions that can be trained with feature vector training data and demonstrate change-type discrimination on an example image set for three different types of change. Furthermore, we also describe and characterize the performance of the two proposed change-type discrimination functions by way of receiver operating characteristic curves, confusion matrices, and pass matrices.
关键词： polarimetric interferometric synthetic aperture radar (PolInSAR),H/A/α filter,probabilistic feature fusion (PFF) model,feature vector,Coherent change detection (CCD),optimum coherence (OC),H/A/α decomposition
更新于2025-09-23 15:23:52
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Phasor Quaternion Neural Networks for Singular Point Compensation in Polarimetric-Interferometric Synthetic Aperture Radar
摘要： Interferograms obtained by synthetic aperture radar often include many singular points (SPs), which makes it difficult to generate an accurate digital elevation model. This paper proposes a filtering method to compensate SPs adaptively by using polarization and phase information around the SPs. Phase value is essentially related to polarization changes in scattering as well as propagation. In order to handle the polarization and phase information simultaneously in a consistent manner, we define a new number, phasor quaternion (PQ), by combining quaternion and complex amplitude, with which we construct the theory of PQ neural networks (PQNNs). Experiments demonstrate that the proposed PQNN filter compensates SPs very effectively. Even in the situations where the conventional methods deteriorate in their performance, it realizes accurate compensation, thanks to its good generalization characteristics in integrated Poincare-sphere polarization space and the complex-amplitude space. We find that PQNN is an excellent framework to deal with the polarization and phase of electromagnetic wave adaptively and consistently.
关键词： Complex-valued neural network (CVNN),phase singular point,polarimetric interferometric synthetic aperture radar (PolInSAR),quaternion neural network (QNN),digital elevation model (DEM)
更新于2025-09-23 15:22:29
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[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 - Polinsar and Tomographic Results Over the Gabonese Forest
摘要： The ESA-sponsored AfriSAR campaign took place in Gabon between 2015 and 2016. It was designed to collect data from tropical forests in order to support the future ESA-BIOMASS mission. This paper addresses the potential of P-band PolIn-SAR and tomography for retrieving vegetation parameters from the multi-baseline airborne data acquired by ONERA over the forest of Lopé. It is shown that a correction of phase disturbances (phase screens) is necessary. A correction procedure based on recent works from the litterature is applied. The PolInSAR and tomographic results are presented and compared with the available LIDAR data.
关键词： SAR Tomography,Phase Calibration,Multi-baseline Synthetic Aperture Radar,PolInSAR
更新于2025-09-10 09:29:36
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[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 - Experimental Validation of Compact Tomosar for Vegetation Characterization
摘要： The study aims to explore the potentials of compact TomoSAR for vegetation characterization. The compact mode transmits either in linear or circular polarized waves and receives at horizontal and vertical polarization providing a different perspective to the understanding of the target. The goal of this study is to assess and evaluate the performance of compact polarimetric SAR modes to reconstruct the 3D reflectivity of forest volume and estimate the vertical structure in comparison with FP modes. Preliminary investigation of compact TomoSAR is conducted using L-band BIOSAR 2008 dataset consisting of six flight tracks acquired over Krycklan in northern Sweden.
关键词： SAR Tomography,Reflectivity,Vegetation Structure,Compact Polarimetry,PolInSAR
更新于2025-09-09 09:28:46
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[IEEE 2018 China International SAR Symposium (CISS) - Shanghai, China (2018.10.10-2018.10.12)] 2018 China International SAR Symposium (CISS) - Polarimetric System Design Requirement of PolinSAR for Forest Parameter Inversion
摘要： Polarimetric SAR images acquired by practical polarimetric radar systems are inevitably contaminated by cross-talk and channel imbalance. To ensure the successful estimation of forest heights from forthcoming PolinSAR campaigns, a critical study on the polarimetric system requirements of PolinSAR for forest height inversion must be carried out. In this paper, a triple-factor analysis of cross-talk, channel imbalance and noise of PolinSAR system is conducted to understand the polarimetric system requirements for PolinSAR forest height inversion. A model relationship between height estimation error and polarimetric system parameters is established through theoretical analysis. The numerical relationships are obtained by artificially adding different calibration errors and noise to simulated SAR images. The experiment result validates the correctness of our established model relationship very well.
关键词： PolinSAR,polarimetric system requirement,estimation errors of forest height
更新于2025-09-09 09:28:46
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Estimation of Pine Forest Height and Underlying DEM Using Multi-Baseline P-Band PolInSAR Data
摘要： On the basis of the Gaussian vertical backscatter (GVB) model, this paper proposes a new method for extracting pine forest height and forest underlying digital elevation model (FUDEM) from multi-baseline (MB) P-band polarimetric-interferometric radar (PolInSAR) data. Considering the linear ground-to-volume relationship, the GVB is linked to the interferometric coherences of different polarizations. Subsequently, an inversion algorithm, weighted complex least squares adjustment (WCLSA), is formulated, including the mathematical model, the stochastic model and the parameter estimation method. The WCLSA method can take full advantage of the redundant observations, adjust the contributions of different observations and avoid null ground-to-volume ratio (GVR) assumption. The simulated experiment demonstrates that the WCLSA method is feasible to estimate the pure ground and volume scattering contributions. Finally, the WCLSA method is applied to E-SAR P-band data acquired over Krycklan Catchment covered with mixed pine forest. It is shown that the FUDEM highly agrees with those derived by LiDAR, with a root mean square error (RMSE) of 3.45 m, improved by 23.0% in comparison to the three-stage method. The difference between the extracted forest height and LiDAR forest height is assessed with a RMSE of 1.45 m, improved by 37.5% and 26.0%, respectively, for model and inversion aspects in comparison to three-stage inversion based on random volume over ground (RVoG) model.
关键词： digital terrain model,complex least squares,P-band polarimetric-interferometric radar (PolInSAR),forest vertical structure
更新于2025-09-09 09:28:46