Effect of digital elevation models on monitoring slope displacements in open-pit mine by differential interferometry synthetic aperture radar

Displacement monitoring in open-pit mines is one of the important tasks for safe management of mining processes.Differential interferometric synthetic aperture radar(DInSAR),mounted on an artificial satellite,has the potential to be a cost-effective method for monitoring surface displacements over extensive areas,such as open-pit mines.DInSAR requires the ground surface elevation data in the process of its analysis as a digital elevation model(DEM).However,since the topography of the ground surface in open-pit mines changes largely due to excavations,measurement errors can occur due to insufficient information on the elevation of mining areas.In this paper,effect of different elevation models on the accuracy of the displacement monitoring results by DInSAR is investigated at a limestone quarry.In addition,validity of the DInSAR results using an appropriate DEM is examined by comparing them with the results obtained by global positioning system(GPS)monitoring conducted for three years at the same limestone quarry.It is found that the uncertainty of DEMs induces large errors in the displacement monitoring results if the baseline length of the satellites between the master and the slave data is longer than a few hundred meters.Comparing the monitoring results of DInSAR and GPS,the root mean square error(RMSE)of the discrepancy between the two sets of results is less than 10 mm if an appropriate DEM,considering the excavation processes,is used.It is proven that DInSAR can be applied for monitoring the displacements of mine slopes with centimeter-level accuracy.

A Mo LC+Mo M-based G^0 distribution parameter estimation method with application to synthetic aperture radar target detection

The accuracy of background clutter model is a key factor which determines the performance of a constant false alarm rate(CFAR) target detection method. G0 distribution is one of the optimal statistic models in the synthetic aperture radar(SAR) image background clutter modeling and can accurately model various complex background clutters in the SAR images. But the application of the distribution is greatly limited by its disadvantages that the parameter estimation is complex and the local detection threshold is difficult to be obtained. In order to solve the above-mentioned problems, an synthetic aperture radar CFAR target detection method using the logarithmic cumulant(Mo LC) + method of moment(Mo M)-based G0 distribution clutter model is proposed. In the method, G0 distribution is used for modeling the background clutters, a new Mo LC+Mo M-based parameter estimation method coupled with a fast iterative algorithm is used for estimating the parameters of G0 distribution and an exquisite dichotomy method is used for obtaining the local detection threshold of CFAR detection, which greatly improves the computational efficiency, detection performance and environmental adaptability of CFAR detection. Experimental results show that the proposed SAR CFAR target detection method has good target detection performance in various complex background clutter environments.

PHASE AUTOFOCUSING ALGORITHM FOR COMPRESSED INVERSE SYNTHETIC APERTURE RADAR IMAGING

As same as the conventional inverse synthetic aperture radar（ISAR）, the compressed ISAR also requires the echo signal based motion compensation, which consists of the range alignment and the phase autofoeusing. A phase autofocusing algorithm for compressed ISAR imaging is presented. In the algorithm, phase autofocusing for the sparse ISAR echoes is accomplished using the eigenvector method. Experimental results validate the effectiveness of the algorithm.

Ground Surface Ruptures and Near-Fault,Large-Scale Displacements Caused by the Wenchuan Ms8.0 Earthquake Derived from Pixel Offset Tracking on Synthetic Aperture Radar Images

The 12 May 2008 Wenchuan Ms8.0 earthquake produced surface displacements along the causative fault, the Yingxiu-Beichuan Fault, which are up to several meters near the fault. Because of the large gradient, satellite synthetic aperture radar （SAR） interferometric data are strongly incoherent; the usual SAR interferometry method does not allow such displacements to be measured. In the present study, we employed another approach, the technique based on pixel offset tracking, to solve this problem. The used image data of six tracks are from the Advanced Land Observing Satellite, Phased Array type L-band Synthetic Aperture Radar （ALOS/PALSAR） dataset of Japan. The results show that the entire surface rupture belt is 238 km long, extending almost linearly in a direction of 42°north-east. It is offset left laterally by a north-west-striking fault at Xiaoyudong, and turns at Gaochuan, where the rupture belt shifts toward the south by 5 km, largely keeping the original trend. In terms of the features of the rupture traces, the rupture belt can be divided into five sections and three types. Among them, the Beichuan-Chaping and Hongkou-Yingxiu sections are relatively complex, with large widths and variable traces along the trend. The Pingtong-Nanba and Qingping-Jingtang sections appear uniform, characterized by straight traces and small widths. West of Yingxiu, the rupture traces are not clear. North of the rupture belt, surface displacements are 2.95 m on average, mostly 2-3.5 m, with 7-9 m the maximum near Beichuan. South of the rupture belt, the average displacement is 1.75 m, dominated by 1-2 m, with 3-4 m at a few sites. In the north, the displacements in the radar line of sight are of subsidence, and in the south, they are uplifted, in accordance with a right-slip motion that moves the northern wall of the fault to the east, and the southern wall to the west, respectively. Along the Guanxian-Jiangyou Fault, there is a uplift zone in the radar line of sight, which is 66 km long, 1.5-6 km wide, and has vertical displacements of approximately 2 m, but no observable rupture traces.

A synthetic aperture radar sea surface distribution estimation by n-order Bézier curve and its application in ship detection

To dates,most ship detection approaches for single-pol synthetic aperture radar（SAR） imagery try to ensure a constant false-alarm rate（CFAR）.A high performance ship detector relies on two key components：an accurate estimation to a sea surface distribution and a fine designed CFAR algorithm.First,a novel nonparametric sea surface distribution estimation method is developed based on n-order Bézier curve.To estimate the sea surface distribution using n-order Bézier curve,an explicit analytical solution is derived based on a least square optimization,and the optimal selection also is presented to two essential parameters,the order n of Bézier curve and the number m of sample points.Next,to validate the ship detection performance of the estimated sea surface distribution,the estimated sea surface distribution by n-order Bézier curve is combined with a cell averaging CFAR（CA-CFAR）.To eliminate the possible interfering ship targets in background window,an improved automatic censoring method is applied.Comprehensive experiments prove that in terms of sea surface estimation performance,the proposed method is as good as a traditional nonparametric Parzen window kernel method,and in most cases,outperforms two widely used parametric methods,K and G0 models.In terms of computation speed,a major advantage of the proposed estimation method is the time consuming only depended on the number m of sample points while independent of imagery size,which makes it can achieve a significant speed improvement to the Parzen window kernel method,and in some cases,it is even faster than two parametric methods.In terms of ship detection performance,the experiments show that the ship detector which constructed by the proposed sea surface distribution model and the given CA-CFAR algorithm has wide adaptability to different SAR sensors,resolutions and sea surface homogeneities and obtains a leading performance on the test dataset.

An accelerated nonlocal means algorithm for synthetic aperture radar ocean image despeckling

Synthetic aperture radar(SAR)images play an increasingly important role in ocean environmental monitoring and research.However,SAR images are inherently corrupted by speckle noise.SAR ocean images have some unique characteristics.The signatures of ocean phenomena in SAR images mainly exhibit as stripe or plaque shaped features.These features typically have a high degree of self-similarity or redundancy.The nonlocal means(NLM)method can measure the structural similarity between different image patches and take advantage of redundant information in images.Considering that the NLM algorithm is computationally intensive and timeconsuming,an accelerated NLM algorithm for SAR ocean image despeckling is proposed in this paper.A method is used to discriminate between texture and flat pixels in SAR images.Large similarity and search windows are used on texture pixels,whereas small similarity and search windows are used on flat pixels.Furthermore,the improved NLM algorithm is accelerated by a graphic processing unit(GPU)based on the compute unified device architecture(CUDA)parallel computation framework.The computational efficiency is improved by approximately 200 times.

Research on 3D marine electromagnetic interferometry with synthetic sources for suppressing the airwave interference

In order to suppress the airwave noise in marine controlled-source electromagnetic （CSEM） data, we propose a 3D deconvolution （3DD） interferometry method with a synthetic aperture source and obtain the relative anomaly coefficient （RAC） of the EM field reflection responses to show the degree for suppressing the airwave. We analyze the potential of the proposed method for suppressing the airwave, and compare the proposed method with traditional methods in their effectiveness. A method to select synthetic source length is derived and the effect of the water depth on RAC is examined via numerical simulations. The results suggest that 3DD interferometry method with a synthetic source can effectively suppress the airwave and enhance the potential of marine CSEM to hydrocarbon exploration.

Precise Three-Dimensional Deformation Retrieval in Large and Complex Deformation Areas via Integration of Offset-Based Unwrapping and Improved Multiple-Aperture SAR Interferometry:Application to the 2016 Kumamoto Earthquake

Conventional synthetic aperture radar(SAR)interferometry(InSAR)has been successfully used to precisely measure surface deformation in the line-of-sight(LOS)direction,while multiple-aperture SAR interferometry(MAI)has provided precise surface deformation in the along-track(AT)direction.Integration of the InSAR and MAI methods enables precise measurement of the two-dimensional(2D)deformation from an interferometric pair;recently,the integration of ascending and descending pairs has allowed the observation of precise three-dimensional(3D)deformation.Precise 3D deformation measurement has been applied to better understand geological events such as earthquakes and volcanic eruptions.The surface deformation related to the 2016 Kumamoto earthquake was large and complex near the fault line;hence,precise 3D deformation retrieval had not yet been attempted.The objectives of this study were to①perform a feasibility test of precise 3D deformation retrieval in large and complex deformation areas through the integration of offset-based unwrapped and improved multiple-aperture SAR interferograms and②observe the 3D deformation field related to the 2016 Kumamoto earthquake,even near the fault lines.Two ascending pairs and one descending the Advanced Land Observing Satellite-2(ALOS-2)Phased Array-type L-band Synthetic Aperture Radar-2(PALSAR-2)pair were used for the 3D deformation retrieval.Eleven in situ Global Positioning System(GPS)measurements were used to validate the 3D deformation measurement accuracy.The achieved accuracy was approximately 2.96,3.75,and 2.86 cm in the east,north,and up directions,respectively.The results show the feasibility of precise 3D deformation measured through the integration of the improved methods,even in a case of large and complex deformation.

An empirical method for joint inversion of wave and wind parameters based on SAR and wave spectrometer data

Synthetic aperture radar(SAR)and wave spectrometers,crucial in microwave remote sensing,play an essential role in monitoring sea surface wind and wave conditions.However,they face inherent limitations in observing sea surface phenomena.SAR systems,for instance,are hindered by an azimuth cut-off phenomenon in sea surface wind field observation.Wave spectrometers,while unaffected by the azimuth cutoff phenomenon,struggle with low azimuth resolution,impacting the capture of detailed wave and wind field data.This study utilizes SAR and surface wave investigation and monitoring(SWIM)data to initially extract key feature parameters,which are then prioritized using the extreme gradient boosting(XGBoost)algorithm.The research further addresses feature collinearity through a combined analysis of feature importance and correlation,leading to the development of an inversion model for wave and wind parameters based on XGBoost.A comparative analysis of this model with ERA5 reanalysis and buoy data for of significant wave height,mean wave period,wind direction,and wind speed reveals root mean square errors of 0.212 m,0.525 s,27.446°,and 1.092 m/s,compared to 0.314 m,0.888 s,27.698°,and 1.315 m/s from buoy data,respectively.These results demonstrate the model’s effective retrieval of wave and wind parameters.Finally,the model,incorporating altimeter and scatterometer data,is evaluated against SAR/SWIM single and dual payload inversion methods across different wind speeds.This comparison highlights the model’s superior inversion accuracy over other methods.

Method of Monitoring Three-dimensional Mining Surface Deformation Based on InSAR

In order to solve the problems of small monitoring range,long time and high cost of existing sedimentation observation methods,based on two-view sentinel No.1 radar images of Guqiao mining area in Huainan City from November 4,2017 to November 28,2017,surface change information was obtained in combination with D-InSAR,and the three-dimensional surface deformation was monitored by two-pass method and single line of sight D-InSAR method.The results show that during the research period of 24 d,the maximum deformation of the mining area reached 71 mm,and the southern subsidence was the most obvious,which was in line with the mining subsidence law.The maximum displacement from the north to the south was about 250 mm,while the maximum displacement from the east to the west was about 80 mm,and the maximum subsidence in the center was 110 mm.It is concluded that D-InSAR technique has a good effect on the inversion of the mining subsidence,and this method is suitable for three-dimensional surface monitoring in areas with similar geological conditions.The monitoring results have certain reference value.

利用InSAR技术反演甘肃积石山M_(S)6.2地震同震破裂模型及形变时间序列

使用升降轨Sentinel-1A卫星数据,利用差分干涉技术获取甘肃积石山M_(S)6.2地震高精度同震形变场,并以此为约束反演同震破裂模型,然后采用SBAS-InSAR技术获取震中附近区域近6个月的累积形变时间序列。结果表明,本次地震地表形变以抬升为主,升降轨数据视线向最大同震形变量分别约为6.8 cm和7.3 cm,破裂主要集中在7~15 km深度范围内,最大滑动量约为0.55 m;震后2个月内,震中近场及西北侧的抬升形变呈扩大趋势。综合分析认为,此次积石山地震发震断层走向NW、倾向NE,隶属于拉脊山南缘断裂带东南侧的隐伏分支断层;震后的大面积突发形变可能与孔隙压力释放有关,地表稳定状态有待进一步观察。

基于多源数据的甘肃积石山Ms6.2级地震地表形变对比研究

针对北京时间2023年12月18日,甘肃省临夏回族自治州积石山县发生了Ms6.2级地震,本次地震给当地造成了严重灾害损失。本研究主要使用欧空局2014年发射的Sentinel-1A卫星C波段雷达影像数据,采用合成孔径雷达干涉测量技术处理研究区范围内的同震形变场,通过不同升降轨数据的同震形变场的反演干涉结果进行对比,并结合其它数据反演结果进行验证,最后得出此次地震造成的地表形变变化,得到研究区内由于地震造成的地表抬升以及沉降结果。

Ground settlement of Chek Lap Kok Airport,Hong Kong,detected by satellite synthetic aperture radar interferometry

Satellite synthetic aperture radar (SAR) inter-ferometry is used to investigate the slowly accumulating ground settlement at the new Chek Lap Kok Airport in Hong Kong. Most of the land occupied by the airport was reclaimed from the sea and therefore certain ground settlement in the area has been expected. A pair of ERS-2 SAR images spanning nearly a year is used in the study. The high spatial resolution (20 m×20 m) ground settlement map derived indicates that the settlement that occurred in the area over the time period is as large as 50 mm. The SAR measurement results agree with the levelling measurements at some benchmarks in the area to well within 1 cm(rms error),and the overall correlation between the two types of results is 0.89. The paper presents some brief background of inter-ferometric SAR, and outlines the data processing methods and results.

Parameterized first-guess spectrum method for retrieving directional spectrum of swell-dominated waves and huge waves from SAR images

A method to retrieve ocean wave spectra from SAR images, named Parameterized First-guess Spectrum Method （PFSM）, was proposed after interpretation of the theory to ocean wave imaging and analysis of the drawbacks of the retrieving model generally used. In this method, with additional information and satellite parameters, the separating wave-number is first calculated to determine the maximum wave-number beyond which the linear relation can be used. The separating wave-number can be calculated using the additional information on wind velocity and parameters of SAR satellite. And then the SAR spectrum can be divided into SAR spectrum of wind wave and of swell according to the result of separating wave-number. The portion of SAR spectrum generated by wind wave, is used to search for the most suitable parameters of ocean wind wave spectrum, including propagation direction of ocean wave, phase speed of dominating wave and the angle spreading coefficient. The swell spectrum is acquired by directly inversing the linear relation of ocean wave spectrum to SAR spectrum given the portion of SAR spectrum generated by swell. We used the proposed method to retrieve the ocean wave spectrum from ERS-SAR data from the South China Sea and compared the result with altimeter data. The agreement indicates that the PFSM is reliable.

Grating lobes suppression method for stepped frequency GB-SAR system

A grating lobes suppression method for chirp-subpulse stepped frequency（CSSF） signals is proposed, which is applied to deformation monitoring using the ground based synthetic aperture radar（GB-SAR） system. This method is based on accurate estimation and correction of the phase and amplitude error along two dimensions（range and azimuth）, i.e., the error estimation inside the subpulse（in-subpulse error） and across the stepped frequency subpulses（cross-subpulse error） of transmitted CSSF signals. Validated both with simulated data and experimental data recorded in the deformation monitoring campaign, it can be seen that the method as well as the relative conclusions can be fully and effectively applied to most of the stepped frequency systems.

Autofocus technique for ISAR imaging of uniformly rotating targets based on the ExCoV method

The inverse synthetic aperture radar (ISAR) imaging can be converted into a sparse reconstruction problem and solved by the l1norm minimization algorithm. The basis matrix in sparse ISAR imaging is usually characterized by the unknown rotation rate of a moving target, thus the rotation rate and the sparse signal should be jointly estimated. Especially due to the imperfect coarse motion compensation, we consider the phase error correction problem in the context of the sparse signal reconstruction. To address this issue, we propose an iterative reweighted method, which jointly estimates the rotation rate, corrects the phase error and reconstructs a high resolution ISAR image. The proposed method gives a gradual and interweaved iterative process to refine the unknown parameters to achieve the best sparse representation for the ISAR signals. Particularly, in ISAR image reconstruction, the l1norm minimization algorithm is sensitive to user parameters. Setting these user parameters are not trivial and the reconstruction performance depends significantly on their choices. Then, we consider an expansion-compression variance-component (ExCoV) based method, which is automatic and demands no prior knowledge about signal-sparsity or measurement-noise levels. Both numerical and electromagnetic data experiments are implemented to show the effectiveness of the proposed method. It is shown that the proposed method can estimate the rotation rate and correct the phase errors simultaneously, and its superior performance is proved in terms of high resolution ISAR image. © 2017 Beijing Institute of Aerospace Information.

A joint method to retrieve directional ocean wave spectra from SAR and wave spectrometer data

This paper proposes a joint method to simultaneously retrieve wave spectra at dif ferent scales from spaceborne Synthetic Aperture Radar(SAR) and wave spectrometer data. The method combines the output from the two dif ferent sensors to overcome retrieval limitations that occur in some sea states. The wave spectrometer sensitivity coeffi cient is estimated using an ef fective signifi cant wave height(SWH), which is an average of SAR-derived and wave spectrometer-derived SWH. This averaging extends the area of the sea surface sampled by the nadir beam of the wave spectrometer to improve the accuracy of the estimated sensitivity coeffi cient in inhomogeneous sea states. Wave spectra are then retrieved from SAR data using wave spectrometer-derived spectra as fi rst guess spectra to complement the short waves lost in SAR data retrieval. In addition, the problem of 180° ambiguity in retrieved spectra is overcome using SAR imaginary cross spectra. Simulated data were used to validate the joint method. The simulations demonstrated that retrieved wave parameters, including SWH, peak wave length(PWL), and peak wave direction(PWD), agree well with reference parameters. Collocated data from ENVISAT advanced SAR(ASAR), the airborne wave spectrometer STORM, the PHAROS buoy, and the European Centre for Medium-Range Weather Forecasting(ECMWF) were then used to verify the proposed method. Wave parameters retrieved from STORM and two ASAR images were compared to buoy and ECMWF wave data. Most of the retrieved parameters were comparable to reference parameters. The results of this study show that the proposed joint retrieval method could be a valuable complement to traditional methods used to retrieve directional ocean wave spectra, particularly in inhomogeneous sea states.

Designing and implementation of variance-dependent Goldstein radar interferogram filtering

The variance-dependent Goldstein radar interferogram filter takes into account the information of both interferometric coherence and multilook factors,and can produce very consistent results for interferograms generated under a wide variety of multilook factors and with very different noise level.However,the filter is a bit complicated and its application is still very limited.We present the designing and implementation of the variance-dependent Goldstein radar interferogram filtering,emphasizing on the logic flow,the generation of look-up table,the determination of filtering parameter,and the handling of edge information loss.Experiments with real interferograms are provided to demonstrate the applications of the designed filtering.Comparisons with the result of the coherence-dependent Goldstein filter show that improvements from 18.4% to 36.9% are achieved when the variance-dependent filter is used,and the noisier the interferogram,the greater the improvement.

Multi-static InISAR imaging for ships under sparse aperture

This paper concentrates on super-resolution imaging of the ship target under the sparse aperture situation.Firstly,a multi-static configuration is utilized to solve the coherent processing interval(CPI)problem caused by the slow-speed motion of ship targets.Then,we realize signal restoration and image reconstruction with the alternating direction method of multipliers(ADMM).Furthermore,we adopt the interferometric technique to produce the three-dimensional(3D)images of ship targets,namely interferometric inverse synthetic aperture radar(InISAR)imaging.Experiments based on the simulated data are utilized to verify the validity of the proposed method.

SAR imaging method for sea scene target based on improved phase retrieval algorithm

Due to the influence of the platform random motion and electromagnetic propagation in turbulent media, the synthetic aperture radar (SAR) high resolution imaging for the sea scenes where there are large amounts of water returns with some target (land) returns is very difficult. To solve this problem, a SAR imaging method based on the improved phase retrieval (PR) algorithm is proposed. First, a filter is added to the conventional PR algorithm which can reduce the influence of water returns on the reconstruction of the targets and improve the reconstruction result of the targets. Then, the corrupted phase of the Fourier transform of the intensity image in the iterative process, which can improve the stability of the iterative algorithm, is used to reduce the recovery errors, and a better recovery performance is achieved. Finally, several experiments are performed to demonstrate the advantages of the proposed method. © 2016 Beijing Institute of Aerospace Information.