Spaceborne SAR Research Articles

VS-LSDet: A Multiscale Ship Detector for Spaceborne SAR Images Based on Visual Saliency and Lightweight CNN

VS-LSDet: A Multiscale Ship Detector for Spaceborne SAR Images Based on Visual Saliency and Lightweight CNN

GROUND MOVEMENT ANALYSIS IN POST-MINING CITY USING MTINSAR WITH HELP OF EUROPEAN GROUND MOTION SERVICE

Abstract. Ground movement is a critical concern for urban safety, and understanding its causes and consequences is essential. Mining of hard coal in the Ruhr area of Germany has caused long-term subsidence, leading to building damage and sinkholes in affected cities. The multi-temporal interferometric synthetic aperture radar (MTInSAR) technique has been widely adopted for estimating ground movement at millimetre-level accuracy using spaceborne SAR data. Although many European government institutes have implemented this technique for monitoring purposes, the European Ground Motion Service (EGMS) provides up-to-date ground movement products (until the end of 2020) across 31 countries. However, these products may not always meet the requirements for local use due to being untimely or missing important features. This paper demonstrates how we estimated ground movement in Ahlen, around the Ruhr area of Germany, using EGMS data as a priori and reference source. We implemented MTInSAR using Sentinel-1 data from 2018 to 2021 and compared our results with those of EGMS. Our results reveal the movement one year ahead, contain more measurement points, and cover natural areas such as cropland and bare soil. We interpreted several movement scenarios in detail, and our work highlights the benefits of EGMS as an open-source overview for local monitoring applications. We also explored the influence of soil conditions on ground movement. Our findings suggest that the overall uplift trend observed during the post-mining phase has been mitigated or even reversed, likely due to soil shrinkage resulting from drought conditions, particularly in areas with high organic soil content.

Optimized SAR imaging algorithm with SSL constraints for the Azimuth direction

In order to address the low azimuth imaging problem of traditional Range Doppler (RD) algorithm, a high-resolution imaging algorithm with optimal azimuth sampling sequence length (SSL) constraints is hereby proposed. According to this algorithm, efforts are made to design a formula for the calculation of the initial azimuth SSL on the basis of SAR azimuth imaging parameters. Having obtained the initial SSL and the criteria for the evaluation of SAR imaging performance, we continue to figure out the extreme values of the curve within a reasonable range of variation. On the basis of these values, the optimal azimuth SSL can be determined to provide data support for global azimuth imaging. Measurement data from imaging experiments on airborne and spaceborne SARs show that, compared with traditional RD algorithm, the proposed algorithm reveals outstanding advantages as indicated by a number of factors critical for the evaluation of imaging performance, such as resolution, peak sidelobe ratio (PSLR) and integral sidelobe ratio (ISLR). Compared with reference methods with local optimal imaging performance, the proposed algorithm can help to obtain global optimal SAR imaging data.

Wave Attenuation by Sea Ice in the Arctic Marginal Ice Zone Observed by Spaceborne SAR

AbstractAttenuation of ocean waves by ice is a crucial process of the interaction between waves and sea ice in marginal ice zone (MIZ), while such interaction can contribute to the retreating of sea ice in the Arctic. Based on the retrieved two‐dimensional ocean wave spectra by spaceborne Synthetic Aperture Radar, we investigated the attenuation of ocean waves in the MIZ in Svalbard and Greenland. The results show that the energy attenuation rate ranges from 0.126 × 10−4/m to 0.618 × 10−4/m. Quantitative analysis suggests that the attenuation rate is significantly related to wave height and peak wave period of coming waves. It is further found that the waves decay faster in the area with ice thickness exceeding 0.5 m. We compared the derived wave attenuation rates in the present study with those in previous studies based on in situ measurements, which reveals that waves are becoming less attenuated by sea ice in the Arctic.

High-Resolution and Wide-Swath 3D Imaging for Urban Areas Based on Distributed Spaceborne SAR

Tomographic synthetic aperture radar (TomoSAR) obtains elevation resolution by adding multiple baselines successively in the direction perpendicular to the line of sight, thereby realizing three-dimensional (3D) reconstruction of complex scenes and significantly promoting the development of the 3D application field. However, a large data redundancy and long mapping time in traditional 3D imaging lead to a large data transmission burden, low efficiency, and high costs. To solve the above problems, this paper proposes a distributed SAR high-resolution and wide-swath (HRWS) 3D imaging technology scheme. The proposed scheme overcomes the size limitation of traditional single-satellite antennas through the multi-channel arrangement of multiple satellites in the elevation direction to achieve HRWS imaging; meanwhile, the distributed SAR system is integrated with tomographic processing technology to realize 3D imaging of difficult areas by using the elevation directional resolution of TomoSAR systems. HRWS 3D SAR increases the baseline length and channel number by transmission in turn, which leads to excessive pulse repetition frequency and causes echoes of different pulse signals to overlap in the same receiving cycle, resulting in range ambiguity and thus seriously affecting the quality of the 3D reconstruction. To solve this problem, this paper proposes a range ambiguity resolution algorithm based on multi-beam forming and verifies it on the measured data from airborne array SAR. Compared with the traditional TomoSAR, the distributed HRWS 3D SAR scheme proposed in this paper can obtain a greater mapping bandwidth with the same resolution in a single flight, thereby enhancing the time correlation, reducing data redundancy, and greatly improving mapping efficiency.

Mechanics of the Kalabagh Fault, northwest Himalayan fold and thrust belt (convergence zone of India and Eurasia), using SAR interferometry and CFS

The Kalabagh strike–slip fault, which is characterized by right-lateral movement, is part of the northwestern Himalayan foreland fold and thrust belt in Pakistan. This structure marks the western and eastern terminations of the Salt Range and Surghar Ranges, respectively. No significant (>M6) earthquakes have been reported along the Kalabagh Fault in recent decades. Here, we take advantage of space-borne Sentinel-1A SAR interferometry to gain insight into the mechanics of faulting, aseismic creeping, and stress loading of the seismic cycle on the Kalabagh Fault spanning over approximately 7 years. In this study, we also removed the tropospheric effects using the Generic Atmospheric Correction Online Service data from the rate map. We further resolved the LOS deformation into both horizontal and vertical deformations. Our Bayesian inversion indicates that the fault experiences significant horizontal and vertical displacements. The fault’s southern and northern segments exhibit a creeping rate of approximately ∼4.2 ± 1.3 to 4.8 ± 1.6 mm/year, respectively, while the central section does not display any horizontal creeping. We found that the creeping is confined between 0 and ∼2.7 ± 1.1 km depth at the northern section and 0 and ∼3.9 ± 1.1 km on the southern section of the faults. Nevertheless, we found that the vertical creeping of ∼10 mm/year is confined between 0.5 and 6 km depth in the central segment of the fault. Moreover, our model does not resolve the interseismic slip at depth on the Kalabagh Fault. Our results affirm that Kalabagh Fault is creeping, and the internal deformation due to the presence of a thick salt layer over the decollement facilitates the creeping on this fault. In addition, Coulomb stress modeling depicts that the creeping on the Kalabagh Fault increases the Coulomb stress changes in the northern section of the KBF.

The Demand for Satellite Attitude Error for High-Resolution Spaceborne SAR Image Quality

Because of the prominent problem of insufficient index decomposition of satellite-earth integration indicators and attitude control demand analysis for spaceborne SAR, this paper made studies on the effect of attitude measurement error and attitude pointing error for spaceborne SAR images. The attitude error model of azimuth and range antennae was constructed. The quantitative transfer relationships, which contain the attitude measurement error model determined by azimuth Doppler parameters and the attitude pointing error model determined by ambiguity and system sensitivity, were analyzed. Theoretical analysis and simulation results are shown as follows: for the X-band SAR satellite, the attitude measurement error should be better than 0.01° for 0.5 m azimuth resolution, and the attitude pointing error should be better than 0.03°. The research results can provide theoretical support for the error allocation phase of the satellite scheme and the analysis of attitude control requirements.

Active optimization adjustment for the surface accuracy of spaceborne SAR antennas

Inevitable disturbances in the spatial thermal environment will seriously degrade the surface accuracy of satellite antennas. Unfortunately, the ground pre-adjustment cannot adaptively guarantee the antenna performance under alternating thermal loadings. To tackle the challenge, this study proposes an active optimization adjustment method to achieve the required surface accuracy for spaceborne antennas. Starting from the comprehensive analysis of external thermal fluxes in outer space, the heat transfer model is firstly established to acquire the temperature field of the antenna system. Subsequently, considering the thermoelastic effect and the geometrical nonlinearity, the antenna surface accuracy is predicted. In particular, the thermoelastic forces induced from temperature changes and dimensional deviations are precisely determined by the absolute nodal coordinate formulation. Moreover, an efficient computational method with invariant matrices is developed to accelerate the prediction. On this basis, we construct the on-orbit active adjustment model to compensate for the effect of thermally induced deformation on the surface accuracy. A mixed-variable optimization algorithm is further put forward to find the optimal strategy of dimensional adjustment. Finally, a case study with simulation analysis and experiment verification demonstrates the feasibility and superiority of the proposed surface adjustment method.

Mangrove changes over the past decade in South and Southeast Brazil using spaceborne optical and SAR imagery.

Mangroves occur in the tropics and subtropics. This region is constantly covered by clouds and therefore highly challenging to map and monitor. Technological advances in remote sensing have increased the flexibility of performing such analyses. In this study, mapping and change detection were carried out for mangrove areas of the South and Southeast regions of Brazil between 2008 and 2016 using multisensor data and geographical object-based image analysis (GEOBIA). The 823.03 km² mangrove areas in study site in 2008 were reduced to 789.00 km² in 2016, representing a net loss of ~34 km². A change detection analysis of the mangrove areas showed a total gain of 138.21 km², a total loss of 172.24 km² and no change for 650.79 km². The GEOBIA classification accuracy was assessed by performing a statistical analysis of confusion matrix: (2008): global accuracy = 0.92, Kappa index = 0.84 and Tau index = 0.84; and (2016): global accuracy = 0.93, Kappa index = 0.86 and Tau index = 0.86. These results demonstrate the effectiveness of the GEOBIA to map and analyze mangrove dynamics. The results exhibit an excellent accuracy. Furthermore, mangrove areas in the south and southeast Brazil were mapped from the same methodological approach.

An Improved Real-Time Echo Separation Processing Scheme in Intermediate Frequency Domain

Space-time waveform-encoding (STWE) SAR has great potential to improve the performance of the future spaceborne SAR system. With the aim of solving the problem of overlapped echoes, one effective approach involves the use of digital beamforming (DBF) in elevation combined with the null-steering techniques. However, the traditional real-time echo separation scheme with single-null steering techniques occupies huge digital resources. In this letter, a novel real-time echo separation processing scheme in intermediate frequency domain is proposed to overcome the disadvantage of the conventional scheme. Based on the two-dimensional simulation results, the proposed scheme has the same accuracy of separating the overlapped echoes as the traditional scheme. Detailed analysis of the system complexity indicates that the proposed scheme can greatly reduce the resource occupation. Moreover, the effectiveness of the proposed scheme is further verified and demonstrated by the experimental results on the X-band 16-channel DBF-SAR system.

Block Optimization and Outlier Detection in GEO SAR Turbulent Tropospheric Error Compensation

Geosynchronous Synthetic Aperture Radar (GEO SAR) has important potential applications in the fields of atmospheric water cycle and digital weather forecast, and establishing the connection between GEO SAR imaging and atmospheric water vapor inversion is a key step. The turbulent variation of atmospheric phase delay will cause the SAR image defocus, and turbulent tropospheric delay phase estimation based on block autofocus method in low-orbit high resolution space-borne SAR can be used for reference, but this method is very sensitive to the data block selection, modulation frequency (FM) outlier detection and correction. This Letter gives some considerations to these two problems of block selection and outlier correction. Based on the idea of Extreme Learning Machine (ELM), a mathematical model with nonlinearity as the core and linear model as easy to solve is established. When the parameters affecting the turbulent troposphere are known, the model can be directly used to obtain the block optimization selection, namely, the number and size of blocks. When the parameters are unknown, the model can be used to roughly inverse the parameters and provide initial values for iteration. For the second problem, using the prior information of the correlation of the FM estimated by the adjacent sub-blocks, we proposes a Local Outlier Factor (LOF) method to identify the error point by defining the distance threshold. The effectiveness of the proposed algorithm is verified by Sentinel-1 data injected with tropospheric error.

Estimation of Aboveground Biomass in Agroforestry Systems over Three Climatic Regions in West Africa Using Sentinel-1, Sentinel-2, ALOS, and GEDI Data.

Agroforestry systems (AFS) offer viable solutions for climate change because of the aboveground biomass (AGB) that is maintained by the tree component. Therefore, spatially explicit estimation of their AGB is crucial for reporting emission reduction efforts, which can be enabled using remote sensing (RS) data and methods. However, multiple factors including the spatial distributions within the AFS, their structure, their composition, and their variable extents hinder an accurate RS-assisted estimation of the AGB across AFS. The aim of this study is to (i) evaluate the potential of spaceborne optical, SAR and LiDAR data for AGB estimations in AFS and (ii) estimate the AGB of different AFS in various climatic regions. The study was carried out in three climatic regions covering Côte d'Ivoire and Burkina Faso. Two AGB reference data sources were assessed: (i) AGB estimations derived from field measurements using allometric equations and (ii) AGB predictions from the GEDI level 4A (L4A) product. Vegetation indices and texture parameters were generated from optical (Sentinel-2) and SAR data (Sentinel-1 and ALOS-2) respectively and were used as predictors. Machine learning regression models were trained and evaluated by means of the coefficient of determination (R2) and the RMSE. It was found that the prediction error was reduced by 31.2% after the stratification based on the climatic conditions. For the AGB prediction, the combination of random forest algorithm and Sentinel-1 and -2 data returned the best score. The GEDI L4A product was applicable only in the Guineo-Congolian region, but the prediction error was approx. nine times higher than the ground truth. Moreover, the AGB level varied across AFS including cocoa (7.51 ± 0.6 Mg ha-1) and rubber (7.33 ± 0.33 Mg ha-1) in the Guineo-Congolian region, cashew (13.78 ± 0.98 Mg ha-1) and mango (12.82 ± 0.65 Mg ha-1) in the Guinean region. The AFS farms in the Sudanian region showed the highest AGB level (6.59 to 82.11 Mg ha-1). AGB in an AFS was mainly determined by the diameter (R2 = 0.45), the height (R2 = 0.13) and the tree density (R2 = 0.10). Nevertheless, RS-based estimation of AGB remain challenging because of the spectral similarities between AFS. Therefore, spatial assessment of the prediction uncertainties should complement AGB maps in AFS.

A Framework for Distributed LEO SAR Air Moving Target 3D Imaging via Spectral Estimation

This paper aims to perform imaging and detect moving targets in a 3D scene for space-borne air moving target indication (AMTI). Specifically, we propose a feasible framework for distributed LEO space-borne SAR air moving target 3D imaging via spectral estimation. This framework contains four subsystems: the distributed LEO satellite and radar modeling, moving target information processing, baseline design framework, and spectrum estimation 3D imaging. Firstly in our method, we develop a relative motion model between the satellite platform and the 3D moving target for satellite and radar modeling. In a very short time, the relative motion between the platform and the target is approximated as a uniform motion. We then establish the space-borne distributed SAR moving target 3D imaging model based on the motion model. After that, we analyze the influencing factors, including the Doppler parameters, the three-dimensional velocity, acceleration, and baseline intervals, and further investigate the performance of the 3D imaging of the moving target. The moving target spectrum estimation 3D imaging finally obtains the 3D imaging results of the target, which preliminarily solves the imaging and resolution problems of slow air moving targets. Simulations are conducted to verify the effectiveness of the proposed distributed LEO space-borne SAR moving target 3D imaging framework.

Automatic Delineation of Water Bodies in SAR Images with a Novel Stochastic Distance Approach

Coastal regions and surface waters are among the fundamental biological and social development resources worldwide. For this reason, it is essential to thoroughly monitor these regions to determine and characterize their geographical features and environmental health. These geographical regions, however, present several monitoring challenges when using remotely sensed imagery. Small water bodies tend to be surrounded by swamps, marshes, or vegetation, making accurate border detection difficult. Coastal waters, in turn, experience several phenomena due to winds, undercurrents, and waves, which also hamper the detection of environmental hazards like oil spills. In this work, we propose an automated segmentation algorithm that can be applied to these targets in airborne and spaceborne SAR images. The method is based on pointwise detection in fuzzy borders using a parameter estimation of the G0 distribution, which has been successfully used in similar contexts. The underlying assumption is that the sought-for border separates regions with different textures, each having different distribution parameters. Then, stochastic distances can identify the most likely point where this parameter change occurs. A curve interpolation algorithm then estimates the actual contour of the body given the detected points. We assess the adequacy of eight stochastic distances that are mostly applied in the literature. We evaluate the performance of our method in terms of similarity between true and detected boundaries on simulated and actual SAR images, achieving promising results. The performance of our proposal is assessed by Hausdorff distance and Intersection over Union. In the case of synthetic data, the selection of the best stochastic distance depends on the parameters of the GI0 distribution. In contrast, the harmonic-mean and triangular distances produced the best results in detecting borders in three actual SAR images of lagoons. Finally, we present the results of our proposal applied to an image with oil spills using Bhattacharyya, Hellinger, and Jensen–Shannon distances.

Assessment of L-Band SAOCOM InSAR Coherence and Its Comparison with C-Band: A Case Study over Managed Forests in Argentina

The objective of this work is to analyze the behavior of short temporal baseline interferometric coherence in forested areas for L-band spaceborne SAR data. Hence, an exploratory assessment of the impacts of temporal and spatial baselines on coherence, with emphasis on how these effects vary between SAOCOM-1 L-band and Sentinel-1 C-band data is presented. The interferometric coherence is analyzed according to different imaging parameters. In the case of SAOCOM-1, the impacts of the variation of the incidence angle and the ascending and descending orbits over forested areas are also assessed. Finally, short-term 8-day interferometric coherence maps derived from SAOCOM-1 are especially addressed, since this is the first L-band spaceborne mission that allows us to acquire SAR images with such a short temporal span. The analysis is reported over two forest-production areas in Argentina, one of which is part of the most important region in terms of forest plantations at the national level. In the case of SAOCOM, interferometric configurations are characterized by a lack of control on the spatial baseline, so a zero-baseline orbital tube cannot be guaranteed. Nevertheless, this spatial baseline variability is crucial to exploit volume decorrelation for forest monitoring. The results from this exploratory analysis demonstrates that SAOCOM-1 short temporal baseline interferograms, 8 to 16 days, must be considered in order to mitigate temporal decorrelation effects and to be able to experiment with different spatial baseline configurations, in order to allow appropriate forest monitoring.

Design of f-SCAN Acquisition Mode for Synthetic Aperture Radar

This paper presents the design and processing of the SAR acquisition technique named frequency scanning (f-SCAN), aimed to obtain high sensitivity to targets with low backscattering and to improve the signal-to-noise ratio (SNR) in wide-swath systems. The f-SCAN is an interesting alternative to the scanning on receive method (SCORE), which needs multiple phase centres achieved using the digital beam forming (DBF) technique. f-SCAN requires less hardware complexity than SCORE; at the same time, it improves the sidelobes and ambiguities’ suppression. The elements used in f-SCAN to generate the pencil beam are the true time delay lines (TTDLs) and the phase shifters (PSs). The general methodology to design an f-SCAN spaceborne SAR high-resolution wide-swath (HRWS) system is introduced; emphasis is put on the mathematical definition of the timing parameters and on a novel method of using TTDLs to achieve the full spanning of wide swaths. The processing of f-SCAN data is also considered: we introduce a novel algorithm to limit the data volume and to guarantee an almost invariant slant range impulse response function (IRF) by removing spectral distortions. Eventually, new definitions, specific for f-SCAN, of the well-known SAR performance parameters, are provided. Simulation results and performances are presented. The advantages and disadvantages with respect to SCORE are discussed using the design of a real case system.

Ground Positioning Method of Spaceborne SAR High-Resolution Sliding-Spot Mode Based on Antenna Pointing Vector

As a new high-resolution spaceborne SAR observation mode, sliding-spot imaging has the characteristics of a large squint, long aperture time, and azimuth aliasing, and because of the dechirp operation in the imaging algorithm of this mode, it is difficult to construct a direct range–Doppler equation for its geometric processing. In this paper a conformation model based on an antenna pointing vector is presented, which fully considers the influence of the dechirp operation on the range image, starts from the relative position of the dechirped range image points and the satellite, and establishes a strict conversion model between the image coordinates and geographic coordinates using the accurate satellite–ground geometric conditions. Then the forward and reverse formulas for geometric processing of the sliding-spot mode are given based on this model. Finally, geometric calibration and positioning experiments under different conditions and field spaceborne SAR data are executed. Results show that after geometric errors caused by the SAR payload have been calibrated and other factors such as atmospheric delay, platform position, and elevation error have been compensated, the uncontrolled geometric positioning accuracy can reach within 1 m–2 m, which fully proves the effectiveness of this method in the geometric positioning of high-resolution sliding-spot images.

Multi-Scale Analysis for Coherent Change Detection: A Method for Extracting Typical Changed Area

Coherent change detection is a technology that utilizes phase information in complex-valued synthetic aperture radar images. It is mostly used to detect subtle changes that cannot be detected by amplitude images on the ground, and it also has excellent detection performance when it comes to low-coherence typical changed areas. However, due to its high sensitivity to changes, this technology will falsely detect areas of natural change such as vegetation disturbance, river flow, and low signal-to-noise ratio areas (e.g., uninteresting areas) as changes, resulting in false-alarm interference areas. In order to tackle this problem, this paper studies a coherent change detection method based on multi-scale analysis to extract typical changed areas in complicated scenes. The method uses an equal variance coherence estimator to calculate the coherence value, separates the interference areas and the typical changed areas using a multi-scale method, and then extracts a binary image of the typical changed areas through noise filtering and threshold segmentation. The method in this paper is experimentally verified with publicly available Airbus spaceborne SAR data, and ESAR airborne data, which is provided by the ESA. The experimental results are visualized and quantitatively evaluated. Through the results, by calculating the probability of correct classification and false-positive and other performance parameters, as well as drawing the receiver operating characteristic curve and the kappa coefficient curve of different threshold values, we find that the method has the capability to suppress the interference areas and the high detection performance of the typical changed areas. The experimental data are complicated scenes that include various types of ground object changes. The results show that the method is effective and universal and can provide reference value for the application of coherent change detection.

An Advanced Approach to Improve Synchronization Phase Accuracy with Compressive Sensing for LT-1 Bistatic Spaceborne SAR

In the bistatic synthetic aperture radar (BiSAR) system, the unavoidable frequency deviation between the oscillators (USOs) will result in additional phase modulation in the demodulated radar signal, which significantly degrades the quality of the SAR image and digital elevation model (DEM) product. The innovative L-band spaceborne BiSAR system LuTan-1 (LT-1) employs a non-interrupted synchronization scheme to acquire the synchronization phase error. This advanced phase synchronization scheme avoids interrupting the normal BiSAR data acquisition and further increases the synchronization frequency. However, some non-ideal factors in the transmission link like attenuation, multipath effect, interference, etc., may cause the synchronization phase to be polluted by noise. A phase denoising approach based on compressive sensing (CS) is proposed to improve the accuracy of synchronization phase. The imaging phase with high signal-to-noise ratio (SNR) is input into the K-SVD algorithm to learn the prior information, and then the noise of the synchronization compensation phase is eliminated by maximum a posteriori (MAP) estimation. The data acquired from the ground validation system of the LT-1 synchronization module are adopted for the validation experiment. The proposed phase denoising method achieves higher phase synchronization accuracy compared with traditional ones. The processing results verify the effectiveness of the proposed method and demonstrate its potential for future on-orbit applications of the LT-1 mission.

An improved method of GB-SAR phase unwrapping for landslide monitoring

The ground-based Synthetic Aperture Radar (GB-SAR) technique can be applied to the safety monitoring and early warning of geo-hazards, especially for monitoring displacement of various types of landslide masses. One of the key techniques of processing GB-SAR monitoring data is phase unwrapping, which can be dramatically affected by atmospheric humidity, atmospheric pressure, sampling interval, etc. In high mountains and valleys where environmental change is drastic, GB-SAR monitoring data is vulnerable to incoherence both spatially and temporally. Therefore, an improved phase unwrapping method of GB-SAR data for landslide monitoring is proposed in this paper, which can realize three-dimensional phase unwrapping in time and space. The method adopts the idea of sparse data processing and realizes phase unwrapping of monitoring data in two steps. Firstly, taking full advantage of the high temporal resolution of GB-SAR monitoring data, the one-dimensional phase unwrapping method in the spatial domain is applied to the time domain, and the interference phases of PS points are unwrapped in the time domain. Then, the PS network is constructed based on the time-phase unwrapping results, the double-difference phases of the network baselines are obtained and the spatial consistency adjustment is applied to them, and the spatial phase unwrapping can be realized by the indirect least square adjustment method. This method successfully solves the problem of path dependence, island isolation and large computation of the common method of space-borne SAR phase unwrapping, which can process GB-SAR data with high accuracy and efficiency.