The Experts below are selected from a list of 97779 Experts worldwide ranked by ideXlab platform

Haiguang Yang - One of the best experts on this subject based on the ideXlab platform.

  • fast factorized backprojection imaging algorithm integrated with motion trajectory estimation for bistatic forward looking sar
    IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2019
    Co-Authors: Yulin Huang, Jianyu Yang, Haiguang Yang
    Abstract:

    A bistatic forward-looking synthetic aperture radar (BFSAR) is increasingly in the focus of study, as it breaks through the limitations of imaging on a forward-looking terrain of a moving platform. Fast factorized backprojection (FFBP) is a reliable BFSAR imaging algorithm, with both imaging precision and efficiency being taken into consideration. In FFBP imaging, compensation of the motion errors is important to obtain a well-Focused Image. To accomplish an accurate motion compensation in Image processing, a high-precision navigation system is needed. However, in many cases, because of the accuracy limit of such systems, motion errors are difficult to be compensated correctly, resulting chiefly in resolution decrease in the final Images. To deal with such a problem, we propose an FFBP imaging algorithm integrated with motion trajectory estimation for BFSAR. First, a coarse-to-fine residual range cell migration (RCM) correction scheme is applied to ensure the residual RCM within a range resolution. Then, an optimization model with respect to motion trajectory estimation under the criterion of maximum Image sharpness is built during FFBP imaging. According to the coarse-to-fine residual RCM correction scheme and the motion trajectory estimation model, a block coordinate descent technique based on steepest descent optimization method integrated with residual RCM correction is proposed to estimate the motion errors in FFBP imaging. We empirically compare the proposed method with several state-of-the-art BFSAR imaging and autofocus algorithms. Simulations on BFSAR data show that the proposed method is more accurate and has similar computational cost.

  • bistatic forward looking sar motion error compensation method based on keystone transform and modified autofocus back projection
    International Geoscience and Remote Sensing Symposium, 2019
    Co-Authors: Qing Yang, Yulin Huang, Haiguang Yang, Zhongyu Li, Junjie Wu, Jianyu Yang
    Abstract:

    With appropriate geometry configurations, bistatic synthetic aperture radar (SAR) can break through the limitations of monostatic SAR on forward-looking imaging. Thanks to such a capability, bistatic forward-looking SAR (BFSAR) has extensive potential applications. In BFSAR, the compensation of the spatially variant motion errors is of great significance to get a well-Focused Image. In this paper, a motion compensation method based on keystone transform and modified autofocus back-projection is presented to deal with this problem. Keystone transform is applied to remove the spatial variation of range cell migration (RCM) and the first-order term of RCM errors simultaneously, prepares for the following modified autofocus back-projection, which can eliminate the high-order term of azimuth phase errors. Simulation results verify the validity and efficiency of the presented method.

  • a rise dimensional modeling and estimation method for flight trajectory error in bistatic forward looking sar
    IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2017
    Co-Authors: Yulin Huang, Jianyu Yang, Haiguang Yang
    Abstract:

    Bistatic forward-looking synthetic aperture radar (BFSAR) is a kind of bistatic SAR system that can Image forward-looking terrain in the flight direction of a moving platform. In BFSAR, compensation of the flight trajectory errors is of great significance to get a well-Focused Image. To accomplish an accurate motion compensation in Image processing, a high-precision navigation system is needed. However, in many cases, due to the accuracy limit of such systems, flight trajectory errors are hard to be compensated correctly, causing mainly the resolution decrease in final Images. In order to cope with such a problem, we propose a rise-dimensional modeling and estimation for flight trajectory error based on raw BFSAR data in this paper. To apply this method, we first carry out a preprocessing named azimuth-slowtime decoupling to deal with the spatially variant flight trajectory error before estimation. Then, an optimization model for flight trajectory estimation under the criterion of maximum Image intensity is built. The solution to the optimization model is the accurate flight trajectory. Then, block coordinate descent technique is used to solve this optimization model. The processing of BFSAR data shows that the algorithm can obtain a more accurate estimation results, and generate better Focused Images compared with the existing trajectory estimation method.

  • motion errors and compensation for bistatic forward looking sar with cubic order processing
    IEEE Transactions on Geoscience and Remote Sensing, 2016
    Co-Authors: Yulin Huang, Zhichao Sun, Jianyu Yang, Haiguang Yang
    Abstract:

    With appropriate geometry configurations, bistatic synthetic aperture radar (SAR) can break through the limitations of monostatic SAR on forward-looking imaging. Owing to such a capability, bistatic forward-looking SAR (BFSAR) has extensive potential applications. In BFSAR, the compensation of the spatially variant motion errors is of great significance to get a well-Focused Image. In this paper, first, the spatial-variance properties of motion errors are analyzed analytically and quantitatively. Different from the side-looking monostatic and bistatic SAR, 2-D space-variant motion errors should be taken into consideration in BFSAR. The 2-D spatial variance of the motion errors can be categorized into two parts, range-variant motion errors of the transmitter and azimuth-variant motion errors of the receiver. Moreover, these two parts are independent of each other. Based on this property analysis, second, a motion compensation (MoCo) approach with cubic-order processing is proposed to deal with the spatially variant motion errors in BFSAR. In the cubic-order processing, the first-order MoCo is performed to correct the spatially independent motion errors on the raw data. The second-order MoCo is accomplished on the non-range-cell-migration (RCM) data to deal with the range-variant errors. After the second-order MoCo, since the signal direction of the non-RCM data coincides with the variant direction of the uncompensated phase errors, the azimuth-variant motion errors and slow time signal are coupled together. To cope with such a problem, the slow time signal is transformed into the direction perpendicular to the azimuth by a novel procedure named azimuth–slow time decoupling. At this stage, the coupling between the azimuth-variant motion errors and slow time signal has been eliminated. Azimuth-variant motion errors can be corrected precisely. Simulation and experimental results verify the effectiveness of the proposed method.

Yulin Huang - One of the best experts on this subject based on the ideXlab platform.

  • fast factorized backprojection imaging algorithm integrated with motion trajectory estimation for bistatic forward looking sar
    IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2019
    Co-Authors: Yulin Huang, Jianyu Yang, Haiguang Yang
    Abstract:

    A bistatic forward-looking synthetic aperture radar (BFSAR) is increasingly in the focus of study, as it breaks through the limitations of imaging on a forward-looking terrain of a moving platform. Fast factorized backprojection (FFBP) is a reliable BFSAR imaging algorithm, with both imaging precision and efficiency being taken into consideration. In FFBP imaging, compensation of the motion errors is important to obtain a well-Focused Image. To accomplish an accurate motion compensation in Image processing, a high-precision navigation system is needed. However, in many cases, because of the accuracy limit of such systems, motion errors are difficult to be compensated correctly, resulting chiefly in resolution decrease in the final Images. To deal with such a problem, we propose an FFBP imaging algorithm integrated with motion trajectory estimation for BFSAR. First, a coarse-to-fine residual range cell migration (RCM) correction scheme is applied to ensure the residual RCM within a range resolution. Then, an optimization model with respect to motion trajectory estimation under the criterion of maximum Image sharpness is built during FFBP imaging. According to the coarse-to-fine residual RCM correction scheme and the motion trajectory estimation model, a block coordinate descent technique based on steepest descent optimization method integrated with residual RCM correction is proposed to estimate the motion errors in FFBP imaging. We empirically compare the proposed method with several state-of-the-art BFSAR imaging and autofocus algorithms. Simulations on BFSAR data show that the proposed method is more accurate and has similar computational cost.

  • bistatic forward looking sar motion error compensation method based on keystone transform and modified autofocus back projection
    International Geoscience and Remote Sensing Symposium, 2019
    Co-Authors: Qing Yang, Yulin Huang, Haiguang Yang, Zhongyu Li, Junjie Wu, Jianyu Yang
    Abstract:

    With appropriate geometry configurations, bistatic synthetic aperture radar (SAR) can break through the limitations of monostatic SAR on forward-looking imaging. Thanks to such a capability, bistatic forward-looking SAR (BFSAR) has extensive potential applications. In BFSAR, the compensation of the spatially variant motion errors is of great significance to get a well-Focused Image. In this paper, a motion compensation method based on keystone transform and modified autofocus back-projection is presented to deal with this problem. Keystone transform is applied to remove the spatial variation of range cell migration (RCM) and the first-order term of RCM errors simultaneously, prepares for the following modified autofocus back-projection, which can eliminate the high-order term of azimuth phase errors. Simulation results verify the validity and efficiency of the presented method.

  • a rise dimensional modeling and estimation method for flight trajectory error in bistatic forward looking sar
    IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2017
    Co-Authors: Yulin Huang, Jianyu Yang, Haiguang Yang
    Abstract:

    Bistatic forward-looking synthetic aperture radar (BFSAR) is a kind of bistatic SAR system that can Image forward-looking terrain in the flight direction of a moving platform. In BFSAR, compensation of the flight trajectory errors is of great significance to get a well-Focused Image. To accomplish an accurate motion compensation in Image processing, a high-precision navigation system is needed. However, in many cases, due to the accuracy limit of such systems, flight trajectory errors are hard to be compensated correctly, causing mainly the resolution decrease in final Images. In order to cope with such a problem, we propose a rise-dimensional modeling and estimation for flight trajectory error based on raw BFSAR data in this paper. To apply this method, we first carry out a preprocessing named azimuth-slowtime decoupling to deal with the spatially variant flight trajectory error before estimation. Then, an optimization model for flight trajectory estimation under the criterion of maximum Image intensity is built. The solution to the optimization model is the accurate flight trajectory. Then, block coordinate descent technique is used to solve this optimization model. The processing of BFSAR data shows that the algorithm can obtain a more accurate estimation results, and generate better Focused Images compared with the existing trajectory estimation method.

  • focusing translational variant bistatic forward looking sar using keystone transform and extended nonlinear chirp scaling
    Remote Sensing, 2016
    Co-Authors: Zhichao Sun, Yulin Huang, Jianyu Yang, Zhe Liu
    Abstract:

    Bistatic Synthetic Aperture Radar (SAR) has attracted increasing attention in recent years due to its unique advantages, such as the ability of forward-looking imaging. In translational variant bistatic forward-looking SAR (TV-BFSAR), it is difficult to get a well Focused Image due to large range cell migration (RCM) and 2-D variation of both Doppler characteristics and RCM. In this paper, an extended azimuth nonlinear chirp scaling (NLCS) algorithm is proposed to deal with these problems. Firstly, Keystone Transform (KT) is introduced to remove the spatial-variant linear RCM, which is of great significance in TV-BFSAR. Secondly, a correction factor is multiplied to the signal in range frequency domain to compensate for the residual RCM. At last, a fourth-order filtering together with azimuth NLCS is performed in every range gate to equalize both the azimuth-variant Doppler centroid and frequency modulation rate based on the azimuth numerical fitting. The proposed method is verified by simulation and real data processing. Multiple targets are generated and Focused by the method, of which the peak sidelobe ratio (PSLR) is around −13 dB and integrated sidelobe ratio (ISLR) is around −10 dB. The method is accurate and can achieve high-resolution focusing for TV-BFSAR data.

  • motion errors and compensation for bistatic forward looking sar with cubic order processing
    IEEE Transactions on Geoscience and Remote Sensing, 2016
    Co-Authors: Yulin Huang, Zhichao Sun, Jianyu Yang, Haiguang Yang
    Abstract:

    With appropriate geometry configurations, bistatic synthetic aperture radar (SAR) can break through the limitations of monostatic SAR on forward-looking imaging. Owing to such a capability, bistatic forward-looking SAR (BFSAR) has extensive potential applications. In BFSAR, the compensation of the spatially variant motion errors is of great significance to get a well-Focused Image. In this paper, first, the spatial-variance properties of motion errors are analyzed analytically and quantitatively. Different from the side-looking monostatic and bistatic SAR, 2-D space-variant motion errors should be taken into consideration in BFSAR. The 2-D spatial variance of the motion errors can be categorized into two parts, range-variant motion errors of the transmitter and azimuth-variant motion errors of the receiver. Moreover, these two parts are independent of each other. Based on this property analysis, second, a motion compensation (MoCo) approach with cubic-order processing is proposed to deal with the spatially variant motion errors in BFSAR. In the cubic-order processing, the first-order MoCo is performed to correct the spatially independent motion errors on the raw data. The second-order MoCo is accomplished on the non-range-cell-migration (RCM) data to deal with the range-variant errors. After the second-order MoCo, since the signal direction of the non-RCM data coincides with the variant direction of the uncompensated phase errors, the azimuth-variant motion errors and slow time signal are coupled together. To cope with such a problem, the slow time signal is transformed into the direction perpendicular to the azimuth by a novel procedure named azimuth–slow time decoupling. At this stage, the coupling between the azimuth-variant motion errors and slow time signal has been eliminated. Azimuth-variant motion errors can be corrected precisely. Simulation and experimental results verify the effectiveness of the proposed method.

A. Miniussi - One of the best experts on this subject based on the ideXlab platform.

  • On the role of density and attenuation in three-dimensional multiparameter viscoacoustic VTI frequency-domain FWI: an OBC case study from the North Sea
    Geophysical Journal International, 2018
    Co-Authors: S. Operto, A. Miniussi
    Abstract:

    3-D frequency-domain full waveform inversion (FWI) is applied on North Sea wide-azimuth ocean-bottom cable data at low frequencies (≤10 Hz) to jointly update vertical wave speed, density and quality factor Q in the viscoacoustic VTI approximation. We assess whether density and Q should be viewed as proxy to absorb artefacts resulting from approximate wave physics or are valuable for interpretation in the presence of soft sediments and gas cloud. FWI is performed in the frequency domain to account for attenuation easily. Multiparameter frequency-domain FWI is efficiently performed with a few discrete frequencies following a multiscale frequency continuation. However, grouping a few frequencies during each multiscale step is necessary to mitigate acquisition footprint and match dispersive shallow guided waves. Q and density absorb a significant part of the acquisition footprint hence cleaning the velocity model from this pollution. Low Q perturbations correlate with low-velocity zones associated with soft sediments and gas cloud. However, the amplitudes of the Q perturbations show significant variations when the inversion tuning is modified. This dispersion in the Q reconstructions is however not passed on the velocity parameter suggesting that cross-talks between first-order kinematic and second-order dynamic parameters are limited. The density model shows a good match with a well log at shallow depths. Moreover, the impedance built a posteriori from the FWI velocity and density models shows a well-Focused Image with however local differences with the velocity model near the sea bed where density might have absorbed elastic effects. The FWI models are finally assessed against time-domain synthetic seismogram modelling performed with the same frequency-domain modelling engine used for FWI.

Jianyu Yang - One of the best experts on this subject based on the ideXlab platform.

  • fast factorized backprojection imaging algorithm integrated with motion trajectory estimation for bistatic forward looking sar
    IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2019
    Co-Authors: Yulin Huang, Jianyu Yang, Haiguang Yang
    Abstract:

    A bistatic forward-looking synthetic aperture radar (BFSAR) is increasingly in the focus of study, as it breaks through the limitations of imaging on a forward-looking terrain of a moving platform. Fast factorized backprojection (FFBP) is a reliable BFSAR imaging algorithm, with both imaging precision and efficiency being taken into consideration. In FFBP imaging, compensation of the motion errors is important to obtain a well-Focused Image. To accomplish an accurate motion compensation in Image processing, a high-precision navigation system is needed. However, in many cases, because of the accuracy limit of such systems, motion errors are difficult to be compensated correctly, resulting chiefly in resolution decrease in the final Images. To deal with such a problem, we propose an FFBP imaging algorithm integrated with motion trajectory estimation for BFSAR. First, a coarse-to-fine residual range cell migration (RCM) correction scheme is applied to ensure the residual RCM within a range resolution. Then, an optimization model with respect to motion trajectory estimation under the criterion of maximum Image sharpness is built during FFBP imaging. According to the coarse-to-fine residual RCM correction scheme and the motion trajectory estimation model, a block coordinate descent technique based on steepest descent optimization method integrated with residual RCM correction is proposed to estimate the motion errors in FFBP imaging. We empirically compare the proposed method with several state-of-the-art BFSAR imaging and autofocus algorithms. Simulations on BFSAR data show that the proposed method is more accurate and has similar computational cost.

  • bistatic forward looking sar motion error compensation method based on keystone transform and modified autofocus back projection
    International Geoscience and Remote Sensing Symposium, 2019
    Co-Authors: Qing Yang, Yulin Huang, Haiguang Yang, Zhongyu Li, Junjie Wu, Jianyu Yang
    Abstract:

    With appropriate geometry configurations, bistatic synthetic aperture radar (SAR) can break through the limitations of monostatic SAR on forward-looking imaging. Thanks to such a capability, bistatic forward-looking SAR (BFSAR) has extensive potential applications. In BFSAR, the compensation of the spatially variant motion errors is of great significance to get a well-Focused Image. In this paper, a motion compensation method based on keystone transform and modified autofocus back-projection is presented to deal with this problem. Keystone transform is applied to remove the spatial variation of range cell migration (RCM) and the first-order term of RCM errors simultaneously, prepares for the following modified autofocus back-projection, which can eliminate the high-order term of azimuth phase errors. Simulation results verify the validity and efficiency of the presented method.

  • a rise dimensional modeling and estimation method for flight trajectory error in bistatic forward looking sar
    IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2017
    Co-Authors: Yulin Huang, Jianyu Yang, Haiguang Yang
    Abstract:

    Bistatic forward-looking synthetic aperture radar (BFSAR) is a kind of bistatic SAR system that can Image forward-looking terrain in the flight direction of a moving platform. In BFSAR, compensation of the flight trajectory errors is of great significance to get a well-Focused Image. To accomplish an accurate motion compensation in Image processing, a high-precision navigation system is needed. However, in many cases, due to the accuracy limit of such systems, flight trajectory errors are hard to be compensated correctly, causing mainly the resolution decrease in final Images. In order to cope with such a problem, we propose a rise-dimensional modeling and estimation for flight trajectory error based on raw BFSAR data in this paper. To apply this method, we first carry out a preprocessing named azimuth-slowtime decoupling to deal with the spatially variant flight trajectory error before estimation. Then, an optimization model for flight trajectory estimation under the criterion of maximum Image intensity is built. The solution to the optimization model is the accurate flight trajectory. Then, block coordinate descent technique is used to solve this optimization model. The processing of BFSAR data shows that the algorithm can obtain a more accurate estimation results, and generate better Focused Images compared with the existing trajectory estimation method.

  • focusing translational variant bistatic forward looking sar using keystone transform and extended nonlinear chirp scaling
    Remote Sensing, 2016
    Co-Authors: Zhichao Sun, Yulin Huang, Jianyu Yang, Zhe Liu
    Abstract:

    Bistatic Synthetic Aperture Radar (SAR) has attracted increasing attention in recent years due to its unique advantages, such as the ability of forward-looking imaging. In translational variant bistatic forward-looking SAR (TV-BFSAR), it is difficult to get a well Focused Image due to large range cell migration (RCM) and 2-D variation of both Doppler characteristics and RCM. In this paper, an extended azimuth nonlinear chirp scaling (NLCS) algorithm is proposed to deal with these problems. Firstly, Keystone Transform (KT) is introduced to remove the spatial-variant linear RCM, which is of great significance in TV-BFSAR. Secondly, a correction factor is multiplied to the signal in range frequency domain to compensate for the residual RCM. At last, a fourth-order filtering together with azimuth NLCS is performed in every range gate to equalize both the azimuth-variant Doppler centroid and frequency modulation rate based on the azimuth numerical fitting. The proposed method is verified by simulation and real data processing. Multiple targets are generated and Focused by the method, of which the peak sidelobe ratio (PSLR) is around −13 dB and integrated sidelobe ratio (ISLR) is around −10 dB. The method is accurate and can achieve high-resolution focusing for TV-BFSAR data.

  • motion errors and compensation for bistatic forward looking sar with cubic order processing
    IEEE Transactions on Geoscience and Remote Sensing, 2016
    Co-Authors: Yulin Huang, Zhichao Sun, Jianyu Yang, Haiguang Yang
    Abstract:

    With appropriate geometry configurations, bistatic synthetic aperture radar (SAR) can break through the limitations of monostatic SAR on forward-looking imaging. Owing to such a capability, bistatic forward-looking SAR (BFSAR) has extensive potential applications. In BFSAR, the compensation of the spatially variant motion errors is of great significance to get a well-Focused Image. In this paper, first, the spatial-variance properties of motion errors are analyzed analytically and quantitatively. Different from the side-looking monostatic and bistatic SAR, 2-D space-variant motion errors should be taken into consideration in BFSAR. The 2-D spatial variance of the motion errors can be categorized into two parts, range-variant motion errors of the transmitter and azimuth-variant motion errors of the receiver. Moreover, these two parts are independent of each other. Based on this property analysis, second, a motion compensation (MoCo) approach with cubic-order processing is proposed to deal with the spatially variant motion errors in BFSAR. In the cubic-order processing, the first-order MoCo is performed to correct the spatially independent motion errors on the raw data. The second-order MoCo is accomplished on the non-range-cell-migration (RCM) data to deal with the range-variant errors. After the second-order MoCo, since the signal direction of the non-RCM data coincides with the variant direction of the uncompensated phase errors, the azimuth-variant motion errors and slow time signal are coupled together. To cope with such a problem, the slow time signal is transformed into the direction perpendicular to the azimuth by a novel procedure named azimuth–slow time decoupling. At this stage, the coupling between the azimuth-variant motion errors and slow time signal has been eliminated. Azimuth-variant motion errors can be corrected precisely. Simulation and experimental results verify the effectiveness of the proposed method.

Yakov Kuzyakov - One of the best experts on this subject based on the ideXlab platform.

  • spatial distribution and catalytic mechanisms of β glucosidase activity at the root soil interface
    Biology and Fertility of Soils, 2016
    Co-Authors: Muhammad Sanaullah, Bahar S Razavi, Evgenia Blagodatskaya, Yakov Kuzyakov
    Abstract:

    We compared modifications of soil zymography, a new in situ technique to visualize enzyme activities, based on contact of fluorgenic substrate-saturated membranes with soil either through the gel layer (gel zymography) or without gel application (direct zymography). We coupled zymography with quantitative measurements of enzyme kinetics to characterize catalytic mechanisms of β-glucosidase activity at the plant-soil interface including root surface (rhizoplane), rhizosphere, and bulk soil. Direct zymography refined and Focused Image resolution. The area of hotspots (i.e., spots with most intensive enzyme activity) as well as color intensity ratios estimated using direct zymography exceeded by a factor of 2 the corresponding values obtained with gel zymography. As determined by direct zymography, the percentage of hotspots associated to root surfaces was 58–68 % of total hotspot area. Hotspot area comprised only 6.8 ± 0.1 % of the total area of an Image and 9.0 ± 3 % of the root surface area. The intensity of β-glucosidase activity, however, was up to 20 times higher in the hotspots versus bulk soil. The contribution of rhizosphere to β-glucosidase activity of the whole Image (77–82 %) was four times higher than the contribution of the root surface. Enzyme kinetic parameters indicated different enzyme systems in bulk and rhizosphere soil. Higher substrate affinity and catalytic efficiency in bulk than in rhizosphere soil suggested relative domination of microorganisms with more efficient enzyme systems in the former. Coupling direct zymography and kinetic assays enabled mapping the two-dimensional (2D) distribution of enzyme activity at the root-soil interface and estimating the catalytic properties of root-associated and soil-associated enzymes.