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3879 KiB

Open AccessArticle

COSMO-SkyMed Image Investigation of Snow Features in Alpine Environment

by Simonetta Paloscia, Simone Pettinato, Emanuele Santi and Mauro Valt

Sensors 2017, 17(1), 84; https://doi.org/10.3390/s17010084 - 4 Jan 2017

Cited by 13 | Viewed by 4877

Abstract

In this work, X band images acquired by COSMO-SkyMed (CSK) on alpine environment have been analyzed for investigating snow characteristics and their effect on backscattering variations. Preliminary results confirmed the capability of simultaneous optical and Synthetic Aperture Radar (SAR) images (Landsat-8 and CSK) [...] Read more.

In this work, X band images acquired by COSMO-SkyMed (CSK) on alpine environment have been analyzed for investigating snow characteristics and their effect on backscattering variations. Preliminary results confirmed the capability of simultaneous optical and Synthetic Aperture Radar (SAR) images (Landsat-8 and CSK) in separating snow/no-snow areas and in detecting wet snow. The sensitivity of backscattering to snow depth has not always been confirmed, depending on snow characteristics related to the season. A model based on Dense Media Radiative Transfer theory (DMRT-QMS) was applied for simulating the backscattering response on the X band from snow cover in different conditions of grain size, snow density and depth. By using DMRT-QMS and snow in-situ data collected on Cordevole basin in Italian Alps, the effect of grain size and snow density, beside snow depth and snow water equivalent, was pointed out, showing that the snow features affect the backscatter in different and sometimes opposite ways. Experimental values of backscattering were correctly simulated by using this model and selected intervals of ground parameters. The relationship between simulated and measured backscattering for the entire dataset shows slope >0.9, determination coefficient, R² = 0.77, and root mean square error, RMSE = 1.1 dB, with p-value <0.05. Full article

(This article belongs to the Special Issue Synthetic Aperture Radars: Models, Algorithms, Techniques and Tools for Data Exploitation)

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9502 KiB

Open AccessArticle

Validation and Parameter Sensitivity Tests for Reconstructing Swell Field Based on an Ensemble Kalman Filter

by Xuan Wang, Pierre Tandeo, Ronan Fablet, Romain Husson, Lei Guan and Ge Chen

Sensors 2016, 16(12), 2000; https://doi.org/10.3390/s16122000 - 25 Nov 2016

Viewed by 5668

Abstract

The swell propagation model built on geometric optics is known to work well when simulating radiated swells from a far located storm. Based on this simple approximation, satellites have acquired plenty of large samples on basin-traversing swells induced by fierce storms situated in [...] Read more.

The swell propagation model built on geometric optics is known to work well when simulating radiated swells from a far located storm. Based on this simple approximation, satellites have acquired plenty of large samples on basin-traversing swells induced by fierce storms situated in mid-latitudes. How to routinely reconstruct swell fields with these irregularly sampled observations from space via known swell propagation principle requires more examination. In this study, we apply 3-h interval pseudo SAR observations in the ensemble Kalman filter (EnKF) to reconstruct a swell field in ocean basin, and compare it with buoy swell partitions and polynomial regression results. As validated against in situ measurements, EnKF works well in terms of spatial–temporal consistency in far-field swell propagation scenarios. Using this framework, we further address the influence of EnKF parameters, and perform a sensitivity analysis to evaluate estimations made under different sets of parameters. Such analysis is of key interest with respect to future multiple-source routinely recorded swell field data. Satellite-derived swell data can serve as a valuable complementary dataset to in situ or wave re-analysis datasets. Full article

(This article belongs to the Special Issue Synthetic Aperture Radars: Models, Algorithms, Techniques and Tools for Data Exploitation)

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5619 KiB

Open AccessArticle

Efficient Time-Domain Imaging Processing for One-Stationary Bistatic Forward-Looking SAR Including Motion Errors

by Hongtu Xie, Shaoying Shi, Hui Xiao, Chao Xie, Feng Wang and Qunle Fang

Sensors 2016, 16(11), 1907; https://doi.org/10.3390/s16111907 - 12 Nov 2016

Cited by 16 | Viewed by 4926

Abstract

With the rapid development of the one-stationary bistatic forward-looking synthetic aperture radar (OS-BFSAR) technology, the huge amount of the remote sensing data presents challenges for real-time imaging processing. In this paper, an efficient time-domain algorithm (ETDA) considering the motion errors for the OS-BFSAR [...] Read more.

With the rapid development of the one-stationary bistatic forward-looking synthetic aperture radar (OS-BFSAR) technology, the huge amount of the remote sensing data presents challenges for real-time imaging processing. In this paper, an efficient time-domain algorithm (ETDA) considering the motion errors for the OS-BFSAR imaging processing, is presented. This method can not only precisely handle the large spatial variances, serious range-azimuth coupling and motion errors, but can also greatly improve the imaging efficiency compared with the direct time-domain algorithm (DTDA). Besides, it represents the subimages on polar grids in the ground plane instead of the slant-range plane, and derives the sampling requirements considering motion errors for the polar grids to offer a near-optimum tradeoff between the imaging precision and efficiency. First, OS-BFSAR imaging geometry is built, and the DTDA for the OS-BFSAR imaging is provided. Second, the polar grids of subimages are defined, and the subaperture imaging in the ETDA is derived. The sampling requirements for polar grids are derived from the point of view of the bandwidth. Finally, the implementation and computational load of the proposed ETDA are analyzed. Experimental results based on simulated and measured data validate that the proposed ETDA outperforms the DTDA in terms of the efficiency improvement. Full article

(This article belongs to the Special Issue Synthetic Aperture Radars: Models, Algorithms, Techniques and Tools for Data Exploitation)

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4259 KiB

Open AccessArticle

SAR Ground Moving Target Indication Based on Relative Residue of DPCA Processing

by Jia Xu, Zuzhen Huang, Liang Yan, Xu Zhou, Furu Zhang and Teng Long

Sensors 2016, 16(10), 1676; https://doi.org/10.3390/s16101676 - 12 Oct 2016

Cited by 11 | Viewed by 5494

Abstract

For modern synthetic aperture radar (SAR), it has much more urgent demands on ground moving target indication (GMTI), which includes not only the point moving targets like cars, truck or tanks but also the distributed moving targets like river or ocean surfaces. Among [...] Read more.

For modern synthetic aperture radar (SAR), it has much more urgent demands on ground moving target indication (GMTI), which includes not only the point moving targets like cars, truck or tanks but also the distributed moving targets like river or ocean surfaces. Among the existing GMTI methods, displaced phase center antenna (DPCA) can effectively cancel the strong ground clutter and has been widely used. However, its detection performance is closely related to the target’s signal-to-clutter ratio (SCR) as well as radial velocity, and it cannot effectively detect the weak large-sized river surfaces in strong ground clutter due to their low SCR caused by specular scattering. This paper proposes a novel method called relative residue of DPCA (RR-DPCA), which jointly utilizes the DPCA cancellation outputs and the multi-look images to improve the detection performance of weak river surfaces. Furthermore, based on the statistics analysis of the RR-DPCA outputs on the homogenous background, the cell average (CA) method can be well applied for subsequent constant false alarm rate (CFAR) detection. The proposed RR-DPCA method can well detect the point moving targets and distributed moving targets simultaneously. Finally, the results of both simulated and real data are provided to demonstrate the effectiveness of the proposed SAR/GMTI method. Full article

(This article belongs to the Special Issue Synthetic Aperture Radars: Models, Algorithms, Techniques and Tools for Data Exploitation)

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13999 KiB

Open AccessArticle

Reference Beam Pattern Design for Frequency Invariant Beamforming Based on Fast Fourier Transform

by Wang Zhang and Tao Su

Sensors 2016, 16(10), 1554; https://doi.org/10.3390/s16101554 - 22 Sep 2016

Cited by 12 | Viewed by 6473

Abstract

In the field of fast Fourier transform (FFT)-based frequency invariant beamforming (FIB), there is still an unsolved problem. That is the selection of the reference beam to make the designed wideband pattern frequency invariant (FI) over a given frequency range. This problem is [...] Read more.

In the field of fast Fourier transform (FFT)-based frequency invariant beamforming (FIB), there is still an unsolved problem. That is the selection of the reference beam to make the designed wideband pattern frequency invariant (FI) over a given frequency range. This problem is studied in this paper. The research shows that for a given array, the selection of the reference beam pattern is determined by the number of sensors and the ratio of the highest frequency to the lowest frequency of the signal (RHL). The length of the weight vector corresponding to a given reference beam pattern depends on the reference frequency. In addition, the upper bound of the weight length to ensure the FI property over the whole frequency band of interest is also given. When the constraints are added to the reference beam, it does not affect the FI property of the designed wideband beam as long as the symmetry of the reference beam is ensured. Based on this conclusion, a scheme for reference beam design is proposed. Full article

(This article belongs to the Special Issue Synthetic Aperture Radars: Models, Algorithms, Techniques and Tools for Data Exploitation)

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6679 KiB

Open AccessArticle

FGG-NUFFT-Based Method for Near-Field 3-D Imaging Using Millimeter Waves

by Yingzhi Kan, Yongfeng Zhu, Liang Tang, Qiang Fu and Hucheng Pei

Sensors 2016, 16(9), 1525; https://doi.org/10.3390/s16091525 - 19 Sep 2016

Cited by 11 | Viewed by 6372

Abstract

In this paper, to deal with the concealed target detection problem, an accurate and efficient algorithm for near-field millimeter wave three-dimensional (3-D) imaging is proposed that uses a two-dimensional (2-D) plane antenna array. First, a two-dimensional fast Fourier transform (FFT) is performed on [...] Read more.

In this paper, to deal with the concealed target detection problem, an accurate and efficient algorithm for near-field millimeter wave three-dimensional (3-D) imaging is proposed that uses a two-dimensional (2-D) plane antenna array. First, a two-dimensional fast Fourier transform (FFT) is performed on the scattered data along the antenna array plane. Then, a phase shift is performed to compensate for the spherical wave effect. Finally, fast Gaussian gridding based nonuniform FFT (FGG-NUFFT) combined with 2-D inverse FFT (IFFT) is performed on the nonuniform 3-D spatial spectrum in the frequency wavenumber domain to achieve 3-D imaging. The conventional method for near-field 3-D imaging uses Stolt interpolation to obtain uniform spatial spectrum samples and performs 3-D IFFT to reconstruct a 3-D image. Compared with the conventional method, our FGG-NUFFT based method is comparable in both efficiency and accuracy in the full sampled case and can obtain more accurate images with less clutter and fewer noisy artifacts in the down-sampled case, which are good properties for practical applications. Both simulation and experimental results demonstrate that the FGG-NUFFT-based near-field 3-D imaging algorithm can have better imaging performance than the conventional method for down-sampled measurements. Full article

(This article belongs to the Special Issue Synthetic Aperture Radars: Models, Algorithms, Techniques and Tools for Data Exploitation)

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9407 KiB

Open AccessArticle

Surface Subsidence Analysis by Multi-Temporal InSAR and GRACE: A Case Study in Beijing

by Jiming Guo, Lv Zhou, Chaolong Yao and Jiyuan Hu

Sensors 2016, 16(9), 1495; https://doi.org/10.3390/s16091495 - 14 Sep 2016

Cited by 46 | Viewed by 6762

Abstract

The aim of this study was to investigate the relationship between surface subsidence and groundwater changes. To investigate this relationship, we first analyzed surface subsidence. This paper presents the results of a case study of surface subsidence in Beijing from 1 August 2007 [...] Read more.

The aim of this study was to investigate the relationship between surface subsidence and groundwater changes. To investigate this relationship, we first analyzed surface subsidence. This paper presents the results of a case study of surface subsidence in Beijing from 1 August 2007 to 29 September 2010. The Multi-temporal Interferometric Synthetic Aperture Radar (multi-temporal InSAR) technique, which can simultaneously detect point-like stable reflectors (PSs) and distributed scatterers (DSs), was used to retrieve the subsidence magnitude and distribution in Beijing using 18 ENVISAT ASAR images. The multi-temporal InSAR-derived subsidence was verified by leveling at an accuracy better than 5 mm/year. Based on the verified multi-temporal InSAR results, a prominent uneven subsidence was identified in Beijing. Specifically, most of the subsidence velocities in the downtown area were within 10 mm/year, and the largest subsidence was detected in Tongzhou, with velocities exceeding 140 mm/year. Furthermore, Gravity Recovery and Climate Experiment (GRACE) data were used to derive the groundwater change series and trend. By comparison with the multi-temporal InSAR-derived subsidence results, the long-term decreasing trend between groundwater changes and surface subsidence showed a relatively high consistency, and a significant impact of groundwater changes on the surface subsidence was identified. Additionally, the spatial distribution of the subsidence funnel was partially consistent with that of groundwater depression, i.e., the former possessed a wider range than the latter. Finally, the relationship between surface subsidence and groundwater changes was determined. Full article

(This article belongs to the Special Issue Synthetic Aperture Radars: Models, Algorithms, Techniques and Tools for Data Exploitation)

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5203 KiB

Open AccessArticle

Numerical Analysis of Orbital Perturbation Effects on Inclined Geosynchronous SAR

by Xichao Dong, Cheng Hu, Teng Long and Yuanhao Li

Sensors 2016, 16(9), 1420; https://doi.org/10.3390/s16091420 - 2 Sep 2016

Cited by 11 | Viewed by 7657

Abstract

The geosynchronous synthetic aperture radar (GEO SAR) is susceptible to orbit perturbations, leading to orbit drifts and variations. The influences behave very differently from those in low Earth orbit (LEO) SAR. In this paper, the impacts of perturbations on GEO SAR orbital elements [...] Read more.

The geosynchronous synthetic aperture radar (GEO SAR) is susceptible to orbit perturbations, leading to orbit drifts and variations. The influences behave very differently from those in low Earth orbit (LEO) SAR. In this paper, the impacts of perturbations on GEO SAR orbital elements are modelled based on the perturbed dynamic equations, and then, the focusing is analyzed theoretically and numerically by using the Systems Tool Kit (STK) software. The accurate GEO SAR slant range histories can be calculated according to the perturbed orbit positions in STK. The perturbed slant range errors are mainly the first and second derivatives, leading to image drifts and defocusing. Simulations of the point target imaging are performed to validate the aforementioned analysis. In the GEO SAR with an inclination of 53° and an argument of perigee of 90°, the Doppler parameters and the integration time are different and dependent on the geometry configurations. Thus, the influences are varying at different orbit positions: at the equator, the first-order phase errors should be mainly considered; at the perigee and apogee, the second-order phase errors should be mainly considered; at other positions, first-order and second-order exist simultaneously. Full article

(This article belongs to the Special Issue Synthetic Aperture Radars: Models, Algorithms, Techniques and Tools for Data Exploitation)

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20040 KiB

Open AccessArticle

An Adaptive Ship Detection Scheme for Spaceborne SAR Imagery

by Xiangguang Leng, Kefeng Ji, Shilin Zhou, Xiangwei Xing and Huanxin Zou

Sensors 2016, 16(9), 1345; https://doi.org/10.3390/s16091345 - 23 Aug 2016

Cited by 53 | Viewed by 8901

Abstract

With the rapid development of spaceborne synthetic aperture radar (SAR) and the increasing need of ship detection, research on adaptive ship detection in spaceborne SAR imagery is of great importance. Focusing on practical problems of ship detection, this paper presents a highly adaptive [...] Read more.

With the rapid development of spaceborne synthetic aperture radar (SAR) and the increasing need of ship detection, research on adaptive ship detection in spaceborne SAR imagery is of great importance. Focusing on practical problems of ship detection, this paper presents a highly adaptive ship detection scheme for spaceborne SAR imagery. It is able to process a wide range of sensors, imaging modes and resolutions. Two main stages are identified in this paper, namely: ship candidate detection and ship discrimination. Firstly, this paper proposes an adaptive land masking method using ship size and pixel size. Secondly, taking into account the imaging mode, incidence angle, and polarization channel of SAR imagery, it implements adaptive ship candidate detection in spaceborne SAR imagery by applying different strategies to different resolution SAR images. Finally, aiming at different types of typical false alarms, this paper proposes a comprehensive ship discrimination method in spaceborne SAR imagery based on confidence level and complexity analysis. Experimental results based on RADARSAT-1, RADARSAT-2, TerraSAR-X, RS-1, and RS-3 images demonstrate that the adaptive scheme proposed in this paper is able to detect ship targets in a fast, efficient and robust way. Full article

(This article belongs to the Special Issue Synthetic Aperture Radars: Models, Algorithms, Techniques and Tools for Data Exploitation)

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11106 KiB

Open AccessArticle

Measurement Matrix Optimization and Mismatch Problem Compensation for DLSLA 3-D SAR Cross-Track Reconstruction

by Qian Bao, Chenglong Jiang, Yun Lin, Weixian Tan, Zhirui Wang and Wen Hong

Sensors 2016, 16(8), 1333; https://doi.org/10.3390/s16081333 - 22 Aug 2016

Cited by 10 | Viewed by 5337

Abstract

With a short linear array configured in the cross-track direction, downward looking sparse linear array three-dimensional synthetic aperture radar (DLSLA 3-D SAR) can obtain the 3-D image of an imaging scene. To improve the cross-track resolution, sparse recovery methods have been investigated in [...] Read more.

With a short linear array configured in the cross-track direction, downward looking sparse linear array three-dimensional synthetic aperture radar (DLSLA 3-D SAR) can obtain the 3-D image of an imaging scene. To improve the cross-track resolution, sparse recovery methods have been investigated in recent years. In the compressive sensing (CS) framework, the reconstruction performance depends on the property of measurement matrix. This paper concerns the technique to optimize the measurement matrix and deal with the mismatch problem of measurement matrix caused by the off-grid scatterers. In the model of cross-track reconstruction, the measurement matrix is mainly affected by the configuration of antenna phase centers (APC), thus, two mutual coherence based criteria are proposed to optimize the configuration of APCs. On the other hand, to compensate the mismatch problem of the measurement matrix, the sparse Bayesian inference based method is introduced into the cross-track reconstruction by jointly estimate the scatterers and the off-grid error. Experiments demonstrate the performance of the proposed APCs’ configuration schemes and the proposed cross-track reconstruction method. Full article

(This article belongs to the Special Issue Synthetic Aperture Radars: Models, Algorithms, Techniques and Tools for Data Exploitation)

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2361 KiB

Open AccessArticle

Near-Space TOPSAR Large-Scene Full-Aperture Imaging Scheme Based on Two-Step Processing

by Qianghui Zhang, Junjie Wu, Wenchao Li, Yulin Huang, Jianyu Yang and Haiguang Yang

Sensors 2016, 16(8), 1177; https://doi.org/10.3390/s16081177 - 27 Jul 2016

Cited by 4 | Viewed by 5795

Abstract

Free of the constraints of orbit mechanisms, weather conditions and minimum antenna area, synthetic aperture radar (SAR) equipped on near-space platform is more suitable for sustained large-scene imaging compared with the spaceborne and airborne counterparts. Terrain observation by progressive scans (TOPS), which is [...] Read more.

Free of the constraints of orbit mechanisms, weather conditions and minimum antenna area, synthetic aperture radar (SAR) equipped on near-space platform is more suitable for sustained large-scene imaging compared with the spaceborne and airborne counterparts. Terrain observation by progressive scans (TOPS), which is a novel wide-swath imaging mode and allows the beam of SAR to scan along the azimuth, can reduce the time of echo acquisition for large scene. Thus, near-space TOPS-mode SAR (NS-TOPSAR) provides a new opportunity for sustained large-scene imaging. An efficient full-aperture imaging scheme for NS-TOPSAR is proposed in this paper. In this scheme, firstly, two-step processing (TSP) is adopted to eliminate the Doppler aliasing of the echo. Then, the data is focused in two-dimensional frequency domain (FD) based on Stolt interpolation. Finally, a modified TSP (MTSP) is performed to remove the azimuth aliasing. Simulations are presented to demonstrate the validity of the proposed imaging scheme for near-space large-scene imaging application. Full article

(This article belongs to the Special Issue Synthetic Aperture Radars: Models, Algorithms, Techniques and Tools for Data Exploitation)

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6560 KiB

Open AccessArticle

A Likelihood-Based SLIC Superpixel Algorithm for SAR Images Using Generalized Gamma Distribution

by Huanxin Zou, Xianxiang Qin, Shilin Zhou and Kefeng Ji

Sensors 2016, 16(7), 1107; https://doi.org/10.3390/s16071107 - 18 Jul 2016

Cited by 34 | Viewed by 6262

Abstract

The simple linear iterative clustering (SLIC) method is a recently proposed popular superpixel algorithm. However, this method may generate bad superpixels for synthetic aperture radar (SAR) images due to effects of speckle and the large dynamic range of pixel intensity. In this paper, [...] Read more.

The simple linear iterative clustering (SLIC) method is a recently proposed popular superpixel algorithm. However, this method may generate bad superpixels for synthetic aperture radar (SAR) images due to effects of speckle and the large dynamic range of pixel intensity. In this paper, an improved SLIC algorithm for SAR images is proposed. This algorithm exploits the likelihood information of SAR image pixel clusters. Specifically, a local clustering scheme combining intensity similarity with spatial proximity is proposed. Additionally, for post-processing, a local edge-evolving scheme that combines spatial context and likelihood information is introduced as an alternative to the connected components algorithm. To estimate the likelihood information of SAR image clusters, we incorporated a generalized gamma distribution (GГD). Finally, the superiority of the proposed algorithm was validated using both simulated and real-world SAR images. Full article

(This article belongs to the Special Issue Synthetic Aperture Radars: Models, Algorithms, Techniques and Tools for Data Exploitation)

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6095 KiB

Open AccessArticle

Correcting Spatial Variance of RCM for GEO SAR Imaging Based on Time-Frequency Scaling

by Ze Yu, Peng Lin, Peng Xiao, Lihong Kang and Chunsheng Li

Sensors 2016, 16(7), 1091; https://doi.org/10.3390/s16071091 - 14 Jul 2016

Cited by 9 | Viewed by 5356

Abstract

Compared with low-Earth orbit synthetic aperture radar (SAR), a geosynchronous (GEO) SAR can have a shorter revisit period and vaster coverage. However, relative motion between this SAR and targets is more complicated, which makes range cell migration (RCM) spatially variant along both range [...] Read more.

Compared with low-Earth orbit synthetic aperture radar (SAR), a geosynchronous (GEO) SAR can have a shorter revisit period and vaster coverage. However, relative motion between this SAR and targets is more complicated, which makes range cell migration (RCM) spatially variant along both range and azimuth. As a result, efficient and precise imaging becomes difficult. This paper analyzes and models spatial variance for GEO SAR in the time and frequency domains. A novel algorithm for GEO SAR imaging with a resolution of 2 m in both the ground cross-range and range directions is proposed, which is composed of five steps. The first is to eliminate linear azimuth variance through the first azimuth time scaling. The second is to achieve RCM correction and range compression. The third is to correct residual azimuth variance by the second azimuth time-frequency scaling. The fourth and final steps are to accomplish azimuth focusing and correct geometric distortion. The most important innovation of this algorithm is implementation of the time-frequency scaling to correct high-order azimuth variance. As demonstrated by simulation results, this algorithm can accomplish GEO SAR imaging with good and uniform imaging quality over the entire swath. Full article

(This article belongs to the Special Issue Synthetic Aperture Radars: Models, Algorithms, Techniques and Tools for Data Exploitation)

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9133 KiB

Open AccessArticle

A Robust and Multi-Weighted Approach to Estimating Topographically Correlated Tropospheric Delays in Radar Interferograms

by Bangyan Zhu, Jiancheng Li, Zhengwei Chu, Wei Tang, Bin Wang and Dawei Li

Sensors 2016, 16(7), 1078; https://doi.org/10.3390/s16071078 - 12 Jul 2016

Cited by 7 | Viewed by 5642

Abstract

Spatial and temporal variations in the vertical stratification of the troposphere introduce significant propagation delays in interferometric synthetic aperture radar (InSAR) observations. Observations of small amplitude surface deformations and regional subsidence rates are plagued by tropospheric delays, and strongly correlated with topographic height [...] Read more.

Spatial and temporal variations in the vertical stratification of the troposphere introduce significant propagation delays in interferometric synthetic aperture radar (InSAR) observations. Observations of small amplitude surface deformations and regional subsidence rates are plagued by tropospheric delays, and strongly correlated with topographic height variations. Phase-based tropospheric correction techniques assuming a linear relationship between interferometric phase and topography have been exploited and developed, with mixed success. Producing robust estimates of tropospheric phase delay however plays a critical role in increasing the accuracy of InSAR measurements. Meanwhile, few phase-based correction methods account for the spatially variable tropospheric delay over lager study regions. Here, we present a robust and multi-weighted approach to estimate the correlation between phase and topography that is relatively insensitive to confounding processes such as regional subsidence over larger regions as well as under varying tropospheric conditions. An expanded form of robust least squares is introduced to estimate the spatially variable correlation between phase and topography by splitting the interferograms into multiple blocks. Within each block, correlation is robustly estimated from the band-filtered phase and topography. Phase-elevation ratios are multiply- weighted and extrapolated to each persistent scatter (PS) pixel. We applied the proposed method to Envisat ASAR images over the Southern California area, USA, and found that our method mitigated the atmospheric noise better than the conventional phase-based method. The corrected ground surface deformation agreed better with those measured from GPS. Full article

(This article belongs to the Special Issue Synthetic Aperture Radars: Models, Algorithms, Techniques and Tools for Data Exploitation)

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4177 KiB

Open AccessArticle

Comparison and Analysis of Geometric Correction Models of Spaceborne SAR

by Weihao Jiang, Anxi Yu, Zhen Dong and Qingsong Wang

Sensors 2016, 16(7), 973; https://doi.org/10.3390/s16070973 - 25 Jun 2016

Cited by 19 | Viewed by 5406

Abstract

Following the development of synthetic aperture radar (SAR), SAR images have become increasingly common. Many researchers have conducted large studies on geolocation models, but little work has been conducted on the available models for the geometric correction of SAR images of different terrain. [...] Read more.

Following the development of synthetic aperture radar (SAR), SAR images have become increasingly common. Many researchers have conducted large studies on geolocation models, but little work has been conducted on the available models for the geometric correction of SAR images of different terrain. To address the terrain issue, four different models were compared and are described in this paper: a rigorous range-doppler (RD) model, a rational polynomial coefficients (RPC) model, a revised polynomial (PM) model and an elevation derivation (EDM) model. The results of comparisons of the geolocation capabilities of the models show that a proper model for a SAR image of a specific terrain can be determined. A solution table was obtained to recommend a suitable model for users. Three TerraSAR-X images, two ALOS-PALSAR images and one Envisat-ASAR image were used for the experiment, including flat terrain and mountain terrain SAR images as well as two large area images. Geolocation accuracies of the models for different terrain SAR images were computed and analyzed. The comparisons of the models show that the RD model was accurate but was the least efficient; therefore, it is not the ideal model for real-time implementations. The RPC model is sufficiently accurate and efficient for the geometric correction of SAR images of flat terrain, whose precision is below 0.001 pixels. The EDM model is suitable for the geolocation of SAR images of mountainous terrain, and its precision can reach 0.007 pixels. Although the PM model does not produce results as precise as the other models, its efficiency is excellent and its potential should not be underestimated. With respect to the geometric correction of SAR images over large areas, the EDM model has higher accuracy under one pixel, whereas the RPC model consumes one third of the time of the EDM model. Full article

(This article belongs to the Special Issue Synthetic Aperture Radars: Models, Algorithms, Techniques and Tools for Data Exploitation)

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8315 KiB

Open AccessArticle

Sensitivity Analysis of the Scattering-Based SARBM3D Despeckling Algorithm

by Alessio Di Simone

Sensors 2016, 16(7), 971; https://doi.org/10.3390/s16070971 - 25 Jun 2016

Cited by 5 | Viewed by 4638

Abstract

Synthetic Aperture Radar (SAR) imagery greatly suffers from multiplicative speckle noise, typical of coherent image acquisition sensors, such as SAR systems. Therefore, a proper and accurate despeckling preprocessing step is almost mandatory to aid the interpretation and processing of SAR data by human [...] Read more.

Synthetic Aperture Radar (SAR) imagery greatly suffers from multiplicative speckle noise, typical of coherent image acquisition sensors, such as SAR systems. Therefore, a proper and accurate despeckling preprocessing step is almost mandatory to aid the interpretation and processing of SAR data by human users and computer algorithms, respectively. Very recently, a scattering-oriented version of the popular SAR Block-Matching 3D (SARBM3D) despeckling filter, named Scattering-Based (SB)-SARBM3D, was proposed. The new filter is based on the a priori knowledge of the local topography of the scene. In this paper, an experimental sensitivity analysis of the above-mentioned despeckling algorithm is carried out, and the main results are shown and discussed. In particular, the role of both electromagnetic and geometrical parameters of the surface and the impact of its scattering behavior are investigated. Furthermore, a comprehensive sensitivity analysis of the SB-SARBM3D filter against the Digital Elevation Model (DEM) resolution and the SAR image-DEM coregistration step is also provided. The sensitivity analysis shows a significant robustness of the algorithm against most of the surface parameters, while the DEM resolution plays a key role in the despeckling process. Furthermore, the SB-SARBM3D algorithm outperforms the original SARBM3D in the presence of the most realistic scattering behaviors of the surface. An actual scenario is also presented to assess the DEM role in real-life conditions. Full article

(This article belongs to the Special Issue Synthetic Aperture Radars: Models, Algorithms, Techniques and Tools for Data Exploitation)

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2908 KiB

Open AccessArticle

GMTI for Squint Looking XTI-SAR with Rotatable Forward-Looking Array

by Kai Jing, Jia Xu, Zuzhen Huang, Di Yao and Teng Long

Sensors 2016, 16(6), 873; https://doi.org/10.3390/s16060873 - 14 Jun 2016

Cited by 4 | Viewed by 6661

Abstract

To realize ground moving target indication (GMTI) for a forward-looking array, we propose a novel synthetic aperture radar (SAR) system, called rotatable cross-track interferometry SAR (Ro-XTI-SAR), for squint-looking application in this paper. By changing the angle of the cross-track baseline, the interferometry phase [...] Read more.

To realize ground moving target indication (GMTI) for a forward-looking array, we propose a novel synthetic aperture radar (SAR) system, called rotatable cross-track interferometry SAR (Ro-XTI-SAR), for squint-looking application in this paper. By changing the angle of the cross-track baseline, the interferometry phase component of squint-looking Ro-XTI-SAR caused by the terrain height can be approximately adjusted to zero, and then the interferometry phase of Ro-XTI-SAR is only sensitive to targets’ motion and can be equivalent to the along track interferometry SAR (ATI-SAR). Furthermore, the conventional displaced phase center array (DPCA) method and constant false alarm (CFAR) processing can be used to accomplish the successive clutter suppression, moving targets detection and relocation. Furthermore, the clutter suppressing performance is discussed with respect to different system parameters. Finally, some results of numerical experiments are provided to demonstrate the effectiveness of the proposed system. Full article

(This article belongs to the Special Issue Synthetic Aperture Radars: Models, Algorithms, Techniques and Tools for Data Exploitation)

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3747 KiB

Open AccessArticle

A Novel Azimuth Super-Resolution Method by Synthesizing Azimuth Bandwidth of Multiple Tracks of Airborne Stripmap SAR Data

by Yan Wang, Jingwen Li, Bing Sun and Jian Yang

Sensors 2016, 16(6), 869; https://doi.org/10.3390/s16060869 - 13 Jun 2016

Cited by 4 | Viewed by 6539

Abstract

Azimuth resolution of airborne stripmap synthetic aperture radar (SAR) is restricted by the azimuth antenna size. Conventionally, a higher azimuth resolution should be achieved by employing alternate modes that steer the beam in azimuth to enlarge the synthetic antenna aperture. However, if a [...] Read more.

Azimuth resolution of airborne stripmap synthetic aperture radar (SAR) is restricted by the azimuth antenna size. Conventionally, a higher azimuth resolution should be achieved by employing alternate modes that steer the beam in azimuth to enlarge the synthetic antenna aperture. However, if a data set of a certain region, consisting of multiple tracks of airborne stripmap SAR data, is available, the azimuth resolution of specific small region of interest (ROI) can be conveniently improved by a novel azimuth super-resolution method as introduced by this paper. The proposed azimuth super-resolution method synthesize the azimuth bandwidth of the data selected from multiple discontinuous tracks and contributes to a magnifier-like function with which the ROI can be further zoomed in with a higher azimuth resolution than that of the original stripmap images. Detailed derivation of the azimuth super-resolution method, including the steps of two-dimensional dechirping, residual video phase (RVP) removal, data stitching and data correction, is provided. The restrictions of the proposed method are also discussed. Lastly, the presented approach is evaluated via both the single- and multi-target computer simulations. Full article

(This article belongs to the Special Issue Synthetic Aperture Radars: Models, Algorithms, Techniques and Tools for Data Exploitation)

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Open AccessArticle

Estimating Forest Aboveground Biomass by Combining Optical and SAR Data: A Case Study in Genhe, Inner Mongolia, China

by Zhenfeng Shao and Linjing Zhang

Sensors 2016, 16(6), 834; https://doi.org/10.3390/s16060834 - 7 Jun 2016

Cited by 88 | Viewed by 8329

Abstract

Estimation of forest aboveground biomass is critical for regional carbon policies and sustainable forest management. Passive optical remote sensing and active microwave remote sensing both play an important role in the monitoring of forest biomass. However, optical spectral reflectance is saturated in relatively [...] Read more.

Estimation of forest aboveground biomass is critical for regional carbon policies and sustainable forest management. Passive optical remote sensing and active microwave remote sensing both play an important role in the monitoring of forest biomass. However, optical spectral reflectance is saturated in relatively dense vegetation areas, and microwave backscattering is significantly influenced by the underlying soil when the vegetation coverage is low. Both of these conditions decrease the estimation accuracy of forest biomass. A new optical and microwave integrated vegetation index (VI) was proposed based on observations from both field experiments and satellite (Landsat 8 Operational Land Imager (OLI) and RADARSAT-2) data. According to the difference in interaction between the multispectral reflectance and microwave backscattering signatures with biomass, the combined VI (COVI) was designed using the weighted optical optimized soil-adjusted vegetation index (OSAVI) and microwave horizontally transmitted and vertically received signal (HV) to overcome the disadvantages of both data types. The performance of the COVI was evaluated by comparison with those of the sole optical data, Synthetic Aperture Radar (SAR) data, and the simple combination of independent optical and SAR variables. The most accurate performance was obtained by the models based on the COVI and optical and microwave optimal variables excluding OSAVI and HV, in combination with a random forest algorithm and the largest number of reference samples. The results also revealed that the predictive accuracy depended highly on the statistical method and the number of sample units. The validation indicated that this integrated method of determining the new VI is a good synergistic way to combine both optical and microwave information for the accurate estimation of forest biomass. Full article

(This article belongs to the Special Issue Synthetic Aperture Radars: Models, Algorithms, Techniques and Tools for Data Exploitation)

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Open AccessArticle

Logarithmic Laplacian Prior Based Bayesian Inverse Synthetic Aperture Radar Imaging

by Shuanghui Zhang, Yongxiang Liu, Xiang Li and Guoan Bi

Sensors 2016, 16(5), 611; https://doi.org/10.3390/s16050611 - 28 Apr 2016

Cited by 5 | Viewed by 5486

Abstract

This paper presents a novel Inverse Synthetic Aperture Radar Imaging (ISAR) algorithm based on a new sparse prior, known as the logarithmic Laplacian prior. The newly proposed logarithmic Laplacian prior has a narrower main lobe with higher tail values than the Laplacian prior, [...] Read more.

This paper presents a novel Inverse Synthetic Aperture Radar Imaging (ISAR) algorithm based on a new sparse prior, known as the logarithmic Laplacian prior. The newly proposed logarithmic Laplacian prior has a narrower main lobe with higher tail values than the Laplacian prior, which helps to achieve performance improvement on sparse representation. The logarithmic Laplacian prior is used for ISAR imaging within the Bayesian framework to achieve better focused radar image. In the proposed method of ISAR imaging, the phase errors are jointly estimated based on the minimum entropy criterion to accomplish autofocusing. The maximum a posterior (MAP) estimation and the maximum likelihood estimation (MLE) are utilized to estimate the model parameters to avoid manually tuning process. Additionally, the fast Fourier Transform (FFT) and Hadamard product are used to minimize the required computational efficiency. Experimental results based on both simulated and measured data validate that the proposed algorithm outperforms the traditional sparse ISAR imaging algorithms in terms of resolution improvement and noise suppression. Full article

(This article belongs to the Special Issue Synthetic Aperture Radars: Models, Algorithms, Techniques and Tools for Data Exploitation)

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Open AccessArticle

Accelerating Spaceborne SAR Imaging Using Multiple CPU/GPU Deep Collaborative Computing

by Fan Zhang, Guojun Li, Wei Li, Wei Hu and Yuxin Hu

Sensors 2016, 16(4), 494; https://doi.org/10.3390/s16040494 - 7 Apr 2016

Cited by 29 | Viewed by 8184

Abstract

With the development of synthetic aperture radar (SAR) technologies in recent years, the huge amount of remote sensing data brings challenges for real-time imaging processing. Therefore, high performance computing (HPC) methods have been presented to accelerate SAR imaging, especially the GPU based methods. [...] Read more.

With the development of synthetic aperture radar (SAR) technologies in recent years, the huge amount of remote sensing data brings challenges for real-time imaging processing. Therefore, high performance computing (HPC) methods have been presented to accelerate SAR imaging, especially the GPU based methods. In the classical GPU based imaging algorithm, GPU is employed to accelerate image processing by massive parallel computing, and CPU is only used to perform the auxiliary work such as data input/output (IO). However, the computing capability of CPU is ignored and underestimated. In this work, a new deep collaborative SAR imaging method based on multiple CPU/GPU is proposed to achieve real-time SAR imaging. Through the proposed tasks partitioning and scheduling strategy, the whole image can be generated with deep collaborative multiple CPU/GPU computing. In the part of CPU parallel imaging, the advanced vector extension (AVX) method is firstly introduced into the multi-core CPU parallel method for higher efficiency. As for the GPU parallel imaging, not only the bottlenecks of memory limitation and frequent data transferring are broken, but also kinds of optimized strategies are applied, such as streaming, parallel pipeline and so on. Experimental results demonstrate that the deep CPU/GPU collaborative imaging method enhances the efficiency of SAR imaging on single-core CPU by 270 times and realizes the real-time imaging in that the imaging rate outperforms the raw data generation rate. Full article

(This article belongs to the Special Issue Synthetic Aperture Radars: Models, Algorithms, Techniques and Tools for Data Exploitation)

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Open AccessArticle

Three-Dimensional ISAR Imaging Method for High-Speed Targets in Short-Range Using Impulse Radar Based on SIMO Array

by Xinpeng Zhou, Guohua Wei, Siliang Wu and Dawei Wang

Sensors 2016, 16(3), 364; https://doi.org/10.3390/s16030364 - 11 Mar 2016

Cited by 6 | Viewed by 5448

Abstract

This paper proposes a three-dimensional inverse synthetic aperture radar (ISAR) imaging method for high-speed targets in short-range using an impulse radar. According to the requirements for high-speed target measurement in short-range, this paper establishes the single-input multiple-output (SIMO) antenna array, and further proposes [...] Read more.

This paper proposes a three-dimensional inverse synthetic aperture radar (ISAR) imaging method for high-speed targets in short-range using an impulse radar. According to the requirements for high-speed target measurement in short-range, this paper establishes the single-input multiple-output (SIMO) antenna array, and further proposes a missile motion parameter estimation method based on impulse radar. By analyzing the motion geometry relationship of the warhead scattering center after translational compensation, this paper derives the receiving antenna position and the time delay after translational compensation, and thus overcomes the shortcomings of conventional translational compensation methods. By analyzing the motion characteristics of the missile, this paper estimates the missile’s rotation angle and the rotation matrix by establishing a new coordinate system. Simulation results validate the performance of the proposed algorithm. Full article

(This article belongs to the Special Issue Synthetic Aperture Radars: Models, Algorithms, Techniques and Tools for Data Exploitation)

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1952 KiB

Open AccessTechnical Note

Comparison of Orbit-Based and Time-Offset-Based Geometric Correction Models for SAR Satellite Imagery Based on Error Simulation

by Seunghwan Hong, Yoonjo Choi, Ilsuk Park and Hong-Gyoo Sohn

Sensors 2017, 17(1), 170; https://doi.org/10.3390/s17010170 - 17 Jan 2017

Cited by 9 | Viewed by 5203

Abstract

Geometric correction of SAR satellite imagery is the process to adjust the model parameters that define the relationship between ground and image coordinates. To achieve sub-pixel geolocation accuracy, the adoption of the appropriate geometric correction model and parameters is important. Until now, various [...] Read more.

Geometric correction of SAR satellite imagery is the process to adjust the model parameters that define the relationship between ground and image coordinates. To achieve sub-pixel geolocation accuracy, the adoption of the appropriate geometric correction model and parameters is important. Until now, various geometric correction models have been developed and applied. However, it is still difficult for general users to adopt a suitable geometric correction models having sufficient precision. In this regard, this paper evaluated the orbit-based and time-offset-based models with an error simulation. To evaluate the geometric correction models, Radarsat-1 images that have large errors in satellite orbit information and TerraSAR-X images that have a reportedly high accuracy in satellite orbit and sensor information were utilized. For Radarsat-1 imagery, the geometric correction model based on the satellite position parameters has a better performance than the model based on time-offset parameters. In the case of the TerraSAR-X imagery, two geometric correction models had similar performance and could ensure sub-pixel geolocation accuracy. Full article

(This article belongs to the Special Issue Synthetic Aperture Radars: Models, Algorithms, Techniques and Tools for Data Exploitation)

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Open AccessConcept Paper

Advanced Unsupervised Classification Methods to Detect Anomalies on Earthen Levees Using Polarimetric SAR Imagery

by Ramakalavathi Marapareddy, James V. Aanstoos and Nicolas H. Younan

Sensors 2016, 16(6), 898; https://doi.org/10.3390/s16060898 - 16 Jun 2016

Cited by 3 | Viewed by 6258

Abstract

Fully polarimetric Synthetic Aperture Radar (polSAR) data analysis has wide applications for terrain and ground cover classification. The dynamics of surface and subsurface water events can lead to slope instability resulting in slough slides on earthen levees. Early detection of these anomalies by [...] Read more.

Fully polarimetric Synthetic Aperture Radar (polSAR) data analysis has wide applications for terrain and ground cover classification. The dynamics of surface and subsurface water events can lead to slope instability resulting in slough slides on earthen levees. Early detection of these anomalies by a remote sensing approach could save time versus direct assessment. We used L-band Synthetic Aperture Radar (SAR) to screen levees for anomalies. SAR technology, due to its high spatial resolution and soil penetration capability, is a good choice for identifying problematic areas on earthen levees. Using the parameters entropy (H), anisotropy (A), alpha (α), and eigenvalues (λ, λ₁, λ₂, and λ₃), we implemented several unsupervised classification algorithms for the identification of anomalies on the levee. The classification techniques applied are H/α, H/A, A/α, Wishart H/α, Wishart H/A/α, and H/α/λ classification algorithms. In this work, the effectiveness of the algorithms was demonstrated using quad-polarimetric L-band SAR imagery from the NASA Jet Propulsion Laboratory’s (JPL’s) Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR). The study area is a section of the lower Mississippi River valley in the Southern USA, where earthen flood control levees are maintained by the US Army Corps of Engineers. Full article

(This article belongs to the Special Issue Synthetic Aperture Radars: Models, Algorithms, Techniques and Tools for Data Exploitation)

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