Phase-linking (PL) plays a crucial role in distributed scatterer (DS) InSAR, but conventional approaches often rely on strong prior assumptions about the underlying data distribution and involve solving highly nonlinear optimization problems. In this study, we propose a novel PL framework based on the central limit theorem for circular data (CLTC), which models interferometric phases through trigonometric moments and avoids any prior assumptions about the data distribution. The CLTC-PL formulation transforms the originally nonlinear PL problem into an inherently well-posed and locally linear weighted least-squares estimation, enabling efficient optimization with minimal iterations and error propagation analysis. The proposed method offers clear structural transparency and statistical interpretability, while having strong estimation performance. This work not only improves robust phase estimation, but also introduces a model-free framework where a multivariate normal distribution of trigonometric moments arises naturally via CLTC, allowing statistically grounded inference. Both simulated and real-data experiments validate the effectiveness of the proposed PL mathematical framework.

Our experiment focused on the simulation of high spatial resolution SAR for geometrical matching between very high-resolution UAV images and geometrically precise SAR images. To achieve this, UAV images of the experimental area were acquired, and a three-dimensional photogrammetric model was generated from the UAV data. This photogrammetric model provides source information for the SAR simulation. The following matching experiment is based on several feature matching algorithms, specifically Scale-Invariant Feature Transform (SIFT), Oriented FAST and Rotated BRIEF (ORB), which were used for the co-registration of simulated and real SAR images. The effectiveness of these algorithms was quantified using the matching rate as a key evaluation metric. The experimental results demonstrate that ORB outperforms SIFT primarily owing to its enhanced robustness against rotational variations and noise. Consequently, ORB is established as a versatile and superior choice for high-resolution SAR image registration tasks and is applicable to both real and simulated data.

One of the biggest risks to cultural treasures in the world today is looting. In a matter of hours, treasure hunters are demolishing the cultural historical objects that archaeologists have spent years examining. Thus, it is crucial to find evidence of illicit activity at historical locations. To evaluate the effectiveness of the SAR images on small-scale looting holes, our team carried out a looting experiment in Wuhan. We excavated four distinct-sized simulated looting holes, constructed photogrammetric representations of the holes, and gathered TerraSAR-X data using varying parameters. By using the results of looting experiment, we worked on SAR simulation and assess the different benefits of simulation in this matter. In this study, we will show the SAR simulation results with different experimental cases.

Training samples significantly influence crop classification results; however, issues such as limited quantity, uneven distribution, and unverifiable accuracy of samples are common. In this paper, samples were divided into two categories: visually interpreted samples and randomly generated samples. Harmonic analysis of time series was used to obtain vegetation index time series for all sample points, with the types of randomly generated samples determined by the time-weighted dynamic time warping. Sample refinement was achieved through an iterative process of random forest proximity analysis and bisecting k-means clustering. The classification of the Sanjiang Plain region from 2020 to 2022 was performed using the random forest method by combining the visually interpreted samples and the refined randomly generated samples. The overall classification accuracy of this method was found to be 89.2% to 93.2%, surpassing traditional methods. This approach is ideal for scenarios with limited sample availability, reducing the need for extensive field investigation, and it can be readily applied to diverse landscapes.

In this paper, we present a new method for weighting the wrapped phases of each interferogram to obtain a set of single reference phases, i.e. phase-linking. Unlike existing works that exploit the coupling between interferometric amplitudes and phases, the new method utilizes the principle of circular statistics and focuses only on the interferometric phases. In our method, the only assumption is that the averaged phases are von-Mises distributed. The simplicity of this model allows not to rely on the fully developed speckle assumption and to avoid optimizing additional parameters caused by more generalized speckle models. Simulation experiments show that, compared to conventional PL methods that assume a multivariate complex circular Gaussian model, our method is less accurate when the fully developed speckle assumption is perfectly valid, but more accurate when small deviations from this assumption occur.

Circular statistics is the mathematical theory for dealing with variables distributed on a circle. The interferometric phase of distributed targets can be modeled with circular statistics due to its wrapped and pseudorandom nature. In this study, we introduce a novel adaptive neighborhood selection (ANS) method and a novel phase-linking (PL) method for distributed scatterer (DS) interferometry, both based on circular statistics principles. The proposed ANS method enables the direct selection of pixels with similar SAR interferometry (InSAR) decorrelation behaviors, called similarly decorrelated pixels (SDP), from the interferometric phases. The proposed PL method: 1) shows significant resistance to the potential departure from the fully developed speckle assumption in the SAR observations (also known as non-Gaussianity) compared to methods that rely on this assumption; 2) does not introduce substantial implementation complexity, computational cost, or numerical solution challenges compared to methods that elaborately model the non-Gaussianity, e.g., through a product model; and 3) can achieve higher consistent wrapped phase estimation precision compared to other methods solely based on interferometric phases. In addition to validating the proposed methods through simulation experiments, we also found that a combination of the two proposed methods can produce interferograms with minimal noise in a real data experiment.

Our study aims to explore the influence of tectonics on deformation in the Islamabad/Rawalpindi (Twin cities) area in Pakistan using the standard PSInSAR technique in conjunction with a tectonic map. While previous research conducted by [4] employed PSInSAR to detect deformation, their study overlooked the consideration of tectonic features in the urban areas despite the presence of several faults in the study area, as evident from historical tectonics maps. Additionally, it is noteworthy that a 4.6 Mw earthquake occurred within the deformation zone in 2017. In our study, we integrated historical earthquake data and tectonic maps of the study area. By applying the standard PSInSAR technique, we have observed a deformation rate of up to 350 mm over the past five years, averaging approximately 70 mm/year and our findings indicate that deformation in the study area cannot be attributed solely to water extraction. The fault lines surrounding the deformation zone play a crucial role, emphasizing the necessity of a detailed analysis of their contribution to deformation patterns.

In distributed scatterer (DS) interferometry, fringes within a multi-looking window can cause bias on coherence estimation and degrade phase-linking precision. Furthermore, fringes might also bias the estimated consistent phases. The problem can be solved by estimating and removing these fringes, i.e., defringing; however, imprecise estimation can significantly affect the results. Thus, a new defringing method for DS time series analysis is proposed. Different from the previous defringing methods, the new method makes use of the information from redundant interferometric combinations under the assumption of Gaussian speckle, and a series of consistent fringes with single reference can be obtained. The basic idea is to establish a framework of weighted least square adjustments with gross error elimination, exploiting the triangular consistency of fringe frequencies as a constraint to estimate fringes. The statistical properties of fringe frequency estimation were exploited to determine the optimum choice for the weight matrix. The quality of the estimated fringes can be improved significantly using the proposed method and therefore the quality of consistent phases in non-stationary areas can be increased. Simulated and real data experiments demonstrate the effectiveness of this new defringing method.

Vessel detection and their activities in the sea can provide updates on latest trends in maritime trade. Space-borne synthetic aperture radar (SAR) can aid in detecting vessels in (almost) all weather conditions. In this study high resolution SAR data are used to analyze the maritime traffic activities, especially the underscored independency in transport trends in Wuhan, the major port-hub on the central Yangtze river in China, before and during the COVID-19 pandemic. Time-series of COSMO-SkyMed SAR images covering Wuhan from 2018 to 2020 were exploited to detect vessels. We applied multi-mode feature and shape (MMFS) image enhancement for fast and accurate vessel detection. Variations in number of vessels were detected, especially a huge drop was observed during the COVID-19 lockdown. HwkEye360 radio frequency monitoring data were used to validate our results.

An unprecedented time series of 293 COSMO-SkyMed StripMap SAR images acquired in 2011–2020 is exploited to investigate land subsidence and vehicle traffic in Wuhan, China. Persistent Scatterer Interferometry using linear and non-linear deformation models suggests that the spatial and temporal evolution of subsidence relates with the dynamic urban development across the main city districts. Traffic patterns along bridges were captured by detecting vehicles based on their azimuth shift caused by their across-track motion, and identified by type based on their radar cross section and speed. The results of vehicle counting confirm an increasing number of vehicles over the last years, which is currently an urban challenge for Wuhan.

The orbit of TerraSAR-X is strictly controlled and well known. Based on this information, a very high absolute accuracy in geo-locating TerraSAR-X data is possible and has been demonstrated before. In this manuscript, we present an experimental validation of this, demonstrating the very high level of accuracy achievable using only the atmospheric phase delay information provided in the header files of TerraSAR-X.

Urbanization is an ongoing process that need constant monitoring and observation. In this manuscript we showcase the build-up changes within and around the city of Shanghai by using space-borne microwave remote sensing data. Specifically, we employ a small baseline time series analysis using coherence change detection from two consecutive image stacks from 2003 to 2015 with data from ENVISAT ASAR and TerraSAR-X. Coherence is a measurement of relative phase change and serves as an indication for changes on the surface. We have generated a set of maps that show the spreading of the urban build-up area and its changes within.

Terrain measurement and surface motion estimation are key applications for SAR missions. These applications drive several SAR satellite missions in the Dragon partner countries in Europe and China. In this context, we present our work in the Dragon program on terrain measurements with results from several test sites in China.

For the next generation of spaceborne synthetic aperture radar remote sensing satellites, high resolution and wide coverage are important goals. Digital beam-forming (DBF) with multichannels in elevation is a great and promising candidate to cover wide swaths. In this letter, we focus on onboard digital processing for DBF in elevation. It is generally believed that the onboard processing for DBF is challenging due to the limitations in flight-hardware availability, the heavy computational load, and the high resource occupation. In order to reduce the computational load of DBF, one novel processing scheme is proposed. This proposed scheme performs a modified time-variant weighting on a real intermediate frequency signal of each subchannel, and the weighted signals of all channels are summed to two real data streams. To obtain a correct DBF output, a modified quadrature demodulation process is presented. Then, the scheme is extended to apply FIR filters for overcoming pulse extension loss. Furthermore, improved time-variant weighting coefficients are derived to compensate the phase errors brought by the FIR filtering process. Compared with the present processing flow, the proposed scheme could significantly reduce the computational load and resource occupation.

This letter focuses on a modified complex-valued Markov random field (CMRF) modeling filter to improve the performance in the filtering of the synthetic aperture radar interferometric phase. In the reference CMRF modeling phase map filter, the CMRF model was employed to update residues and their neighbors. By this, the residues were reduced, and phase jumps were preserved simultaneously. However, residue reduction was still insufficient. Furthermore, incorrect model parameter estimation leads to wrong filtering in some blocks. To solve the two aforementioned problems, we propose a modified CMRF modeling filter, where the original interferogram is divided into overlapped blocks. In addition, the adaptive weighted neighbor values are used to estimate the CMRF model parameters. Both simulated and real data experiments are performed to validate this method.

As an advanced technique, synthetic aperture radar (SAR) tomography makes it possible to overcome the layover problem induced by the intrinsic side-looking geometry of SAR sensors. However, traditional nonparametric spectral estimators, e.g., truncated singular value decomposition, are limited by their poor elevation resolution. On the other hand, the compressive-sensing-based approaches using the basis-pursuit strategy to find an L1-norm minimization solution for SAR tomography (TomoSAR) are extremely time consuming. Therefore, a fast and robust tomographic algorithm with super-resolution capability is needed. In this letter, we propose a new approach for TomoSAR based on two-step iterative shrinkage/thresholding (TWIST). TWIST uses a two-step strategy to speed up the L1-norm minimization procedure and can achieve an exceptionally fast convergence speed for TomoSAR. Experimental studies with simulated signals and a spotlight-mode TerraSAR-X data set were carried out to demonstrate the merits of the proposed TWIST approach in terms of robustness, fast convergence speed, and super-resolution capability.

SAR interferometry has long been regarded as an effective tool for wide-area topographic mapping in hilly and mountainous areas. However, quality of InSAR DEM product is usually affected by atmospheric disturbances and decorrelation-induced voids, especially for data acquired in repeat-pass mode. In this paper, we proposed an approach for improved topographic mapping by optimal fusion of multi-orbit InSAR DEMs with correction of atmospheric phase screen (APS). An experimental study with highresolution TerraSAR-X and COSMO-SkyMed datasets covering a mountainous area was carried out to demonstrate the effectiveness of the proposed approach. Validation with a reference DEM of scale 1:50,000 indicated that vertical accuracy of the fused DEM can be better than 5 m.

The conditions in the Altai Mountains make it a difficult area for archaeological on-ground surveys. Automatic surveying could facilitate decision making and planning as well as the building of a comprehensive database of archaeological monuments. We have tried three different approaches towards automatic detection of grave mounds in high-resolution optical data and found an object-class specific Hough forest algorithm the most suitable for the purpose. Through adaption and testing of the algorithm on IKONOS-2 data we created a tool for mapping archaeological features in the Altai Mountains, hence contributing to future steps towards a sustainable cultural heritage management.

Modern spaceborne SAR sensors provide geometric resolutions well below one meter. In data of this kind, many features of urban objects become visible. However, because of the intrinsic side-looking geometry of SAR sensors, layover and foreshortening issues inevitably arise, especially in dense urban areas. SAR tomography provides a new way of overcoming these problems by exploiting the back-scattering property for each pixel. However, traditional non-parametric spectral estimators are limited by their poor elevation resolution, which is not comparable to the azimuth and slant-range resolution. In order to improve the estimated elevation resolution, super-resolution techniques, like compressive sensing, are introduced to SAR tomographic processing. In this paper, we analyze the performance of the compressive sensing approach in SAR tomographic analysis. Numerical experiments on simulated signals and real TerraSAR-X spotlight data are given, which demonstrate the robustness and super-resolution power of compressive sensing.

A fully polarimetric response of landslide areas at X-band was studied by a Chinese high-resolution airborne synthetic aperture radar system. Polarimetric decompositions, including the Yamaguchi four-component decomposition and the Cloude decomposition, are used to analyze the scattering mechanisms of several typical landslides caused by the 2008 Wenchuan Earthquake in southwestern China. The experimental results indicate that areas affected by large-scale landslides show complicated scattering mechanisms at X-band, which are a mixture of surface, double bounce, and volume scattering. Simple classification results based on supervised Wishart classifier and polarimetric scattering similarity parameters are also presented, which can distinguish landslide areas from others, such as forest and water, very well. However, it does not perform well for urban areas. Additional information, such as prelandslide imagery, is needed to distinguish landslide areas from urban areas or bare soil. From these results, we can conclude that landslide mapping using fully polarimetric data has great potential for rapid response and management of landslide disasters.

In this letter, we propose an approach for multichannel spaceborne/stationary synthetic aperture radar (SAR) interferometry based on maximum a posteriori (MAP). Spaceborne/stationary SAR is a typical bistatic SAR configuration. In order to solve the phase disconnection problem while working with a low signal-to-noise ratio and a limited number of baselines as well as having large look angle variations, we use the height estimation results derived from iterative multibaseline unwrapping as the initial heights for the MAP estimation. The method presented here is highly experimental. An experiment is carried out to verify the effectiveness of the proposed approach. In this experiment, TerraSAR-X, working in the high-resolution spotlight mode with a 300-MHz bandwidth, acts as the transmitter. The receivers with three echo channels are placed on the ground to receive the reflected waveform. As proof of concept, we demonstrate the height estimation of several buildings.

Energy is the major limiting factor for high-performance computing. Nowadays, modern Graphics Processing Units (GPU) use less power per floating-point operation. With the CUDA on ARM architecture, a low-power high performance architecture is available and we present first results on using this architecture for fast SAR geocoding and demonstrate the use of fast SAR geo-coding on GPU for a flexible SAR stereo-radargrammetry approach. We demonstrate the speed-up of SAR geo-coding with GPU implementations on an NVIDIA Tesla C2070 and the CARMA DevKit.

In this letter, we suggest using multiple azimuth channels (MACs) for synthetic aperture radar in the sliding spotlight mode. First, we analyze the scene size constraints of conventional sliding spotlight mode, showing that a large scene size requires long scene illumination time. However, while using multiple channels in azimuth, this could be changed. Dividing a long antenna into small antennas, we can increase the azimuth resolution improvement fact, where the range size will not be reduced. Therefore, with the same illumination time, the azimuth imaging width can be enlarged for a given azimuth resolution. However, using the MAC sliding spotlight mode, the nonuniform sampling problem occurs. Unlike the processing in the MAC stripmap mode, in the MAC sliding spotlight mode, the unambigous reconstruction should be performed after the deramping in azimuth. Finally, an example is given to validate the proposed new configuration and the corresponding algorithms.

The flexible geometry configuration of the bistatic synthetic aperture radar (SAR) has many advantages. However, it causes serious measurement error in the bistatic SAR system, which degrades the quality of the SAR images and the precision of the digital elevation model (DEM) obtained using stereoscopy bistatic SAR. In this paper, the influence of the scene height estimation error, trigger delay, transmitter position measurement error, receiver position measurement error, and transmission line length measurement error are analyzed. These analyses are very useful in bistatic SAR system design. The scene height estimation error, trigger delay, transmitter position measurement error, and synchronization receiver position measurement error affect both the quality of the images and the precision of the DEM obtained by stereoscopy bistatic SAR slightly. The echo receiver position measurement error and transmission line length measurement error affect the quality of the imaging only slightly, but seriously affect the precision of the DEM obtained by stereoscopy bistatic SAR. Luckily, their measurement precision can be quite satisfactory. Simulations and real bistatic experimental results verify the proposed theoretical analysis.

In the above titled paper (ibid., vol. 51, no. 8, pp. 4518-4543, Aug. 2013), some important details concerning the used data, experimental area, and cooperation partner are missing by accident. The details are presented here.

Using high-resolution SAR data stacks, a large amount of persistent scatterers (PS) can be found in urban areas, which are used for very detailed surface deformation monitoring. However, in dense urban areas, many of these points consist of more than one dominant scatterer in elevation direction. Using tomographic SAR, points with more than one scatterer are detected.

Persistent Scatterer Interferometry (PS-InSAR) is applied to derive displacement information with millimetric precision. Analyzing stable persistent scatterers from a large stack of SAR images,helps to overcome the geometrical and temporal decorrelation, which occur when using differential interferometry. The removal of the topographic phase with an external DEM seems to cause problems. In our experiment, we select three different DEMs: ASTER GDEM, a DEM derived from a digitized topographic map, and SRTM-3 in order to analyze the influence of the input DEMs for PS-InSAR processing in the Three Gorges area. We find that differential interferogram generation is related to the topographic influence for the PS-InSAR processing and different DEMs get us different PS-InSAR results.

The RPC (Rational Polynomial Coefficient) model can be used as a replacement sensor model for geo-coding spaceborne SAR data. A hybrid method, combining the L-curve and the IMCCV (Iteration method by correcting characteristic value) method, for solving ill-conditioned equations in the RPC model is proposed. The hybrid method can get higher accuracy at low cost of calculation time. Based on an example in Malaysia, the application for fast RPC geocoding for stereo radargrammetry is shown.

A method for building height determination via a deterministic approach is tested using three TerraSAR-X images from Barcelona, Spain. Using this method, the height of a building wall can be determined based on the strength of the double-bounce backscattering. The approach requires knowledge of the material properties of the measured building wall and the area in near range of the building wall. For certain test buildings the approach provides good results, while for other buildings the results are erroneous.

In this paper, a new hybrid graphics-processing-unit (GPU)-based real-time synthetic aperture radar (SAR) simulation system is presented. Previous real-time SAR simulators only supported single-bounce simulation in real time. The new hybrid system uses the rasterization approach for real-time single-bounce simulation and a new image-based GPU ray-tracing approach for monostatic SAR double-bounce simulation. This approach provides fast simulation results even while simulating complex and extended scenes. The simulation results are compared to a high-resolution airborne SAR image, and the limitations of the approach are discussed.