InSAR System Research Articles

Characterization and Mitigation of Radio Frequency Interference Signatures in L-Band LuTan-1 InSAR System: First Results and Assessment

Characterization and Mitigation of Radio Frequency Interference Signatures in L-Band LuTan-1 InSAR System: First Results and Assessment

Conceptual Study and Performance Analysis of Tandem Multi-Antenna Spaceborne SAR Interferometry

Multi-baseline synthetic aperture radar interferometry (InSAR), capable of mapping 3D surface model with high precision, is able to overcome the ill-posed problem in the single-baseline InSAR. Current tandem SAR mission utilizes a two-stage global coverage to get the dual-baseline interferograms, which achieves the trade-off between the unwrapping errors and height precision. However, the baseline adjustment will decrease the timeliness of the data acquisition, which is not suitable for monitoring temporal changes of the ground targets. Designing a SAR mission with the single-pass multi-baseline acquisition will improve the practical capability in fast 3D reconstruction. Following the asymptotic 3D phase unwrapping proposed for the airborne array InSAR system, it is possible to get a reliable 3D reconstruction using very sparse acquisitions but the interferograms should follow the optimal baseline configuration. In this article, a new concept of tandem multi-antenna SAR interferometry system for acquiring optimal single-pass multi-baseline interferograms is proposed. Two indicators, i.e., expected relative height precision and successful phase unwrapping rate, are selected to optimize the system parameters. Additionally, taking the satellites with two antennas as an example, the performances of various baseline configurations in typical scenarios and the impact of different error sources are investigated correspondingly. The simulation-based experiments demonstrate that the proposed system acquires the optimal MB interferograms for asymptotic 3D phase unwrapping, and thus enables good performance in both urban and forest area in a single flight. This system has the potential applications in accurate digital surface model acquisition, 3D target recognition, and biomass estimation.

A High-Precision Baseline Calibration Method Based on Estimation of Azimuth Fringe Frequency with THz Interferometry SAR

In this study, repeat-pass synthetic aperture radar interferometry (repeat-pass THz InSAR) is first extended to the terahertz band, and it has tremendous potential in the application of high-resolution three-dimensional (3D) imaging due to its shorter wavelength, larger bandwidth, and greater sensitivity to elevation variation. The super-resolution and high sensitivity of THz InSAR pose greater demands on the baseline calibration for high-precision digital elevation model (DEM) generation. To meet the elevation accuracy requirement of THz InSAR, we propose a baseline calibration method relying on the estimation of the azimuth fringe frequency (EAFF) of the interferometric phase. Initially, a model for non-parallel sampling path errors within the squint SAR repeat-pass interferometry was established, and then, we conducted the theoretical analysis of the phase errors induced by the non-parallel errors. Following this, using a reference DEM, the relationship between the fringe frequency of the error phase and the bias in the repeat-path positioning was established. This allowed the estimation of the position errors to be transformed into the frequency spectrum estimation based on the FFT, which would mitigate the impact of unknown SAR sampling positions. Ultimately, we investigated the accuracy of the proposed EAFF calibration method, and the simulation showed that it can achieve the theoretical accuracy when the correlation coefficient exceeds 0.3. Furthermore, we configured the repeat-pass THz InSAR system with the 0.3 THz stepped-frequency radar. Compared to the conventional calibration based on ground control points (GCPs), the 3D reconstruction of both a knife and a terrain model, calibrated using the proposed EAFF algorithm, demonstrated that the elevation accuracy can achieve millimeter-level precision across the entire image swath. The above results also proved the great potential of THz InSAR in high-precision 3D imaging and remote sensing.

Interferometric SAR Coherence Magnitude Estimation by Machine Learning

Current interferometric wide area ground motion services require the estimation of the coherence magnitude as accurately and computationally effectively as possible. However, a precise and at the same time computationally efficient method is missing. Therefore, the objective of this article is to improve the empirical Bayesian coherence magnitude estimation in terms of accuracy and computational cost. Precisely, this article proposes the interferometric coherence magnitude estimation by Machine Learning (ML). It results in a non-parametric and automated statistical inference. However, applying ML in this estimation context is not straightforward. The number and the domain of possible input processes is infinite and it is not possible to train all possible input signals. It is shown that the expected channel amplitudes and the expected interferometric phase cause redundancies in the input signals allowing to solve this issue. Similar to the empirical Bayesian methods, a single parameter for the maximum underlaying coherence is used to model the prior. However, no prior or any shape of prior probability is easy to implement within the ML framework. The article reports on the bias, the standard deviation and the root mean square error (RMSE) of the developed estimators. It was found that ML estimators improve the coherence estimation RMSE from small samples ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$2 N &lt; 30$</tex-math></inline-formula> ) and for small underlaying coherence compared to the conventional and empirical Bayes estimators. For three interferometric samples ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$N = 3$</tex-math></inline-formula> ) and a zero coherence magnitude, the bias related to the sample estimator improves from 0.53 to 0.39 by 27.8%. Assuming the maximum underlaying coherence is 0.6, the bias is reduced by 33.0% to 0.36 for the less strict and by 45.5% to 0.29 for the strict prior. The developed ML coherence magnitude estimators are suitable and recommended for operational InSAR systems. For the estimation, the ML model is extremely fast evaluated because no iteration, numeric integration or Bootstrapping is needed.

A Novel Multiangle Images Association Algorithm Based on Supervised Areas for GNSS-Based InSAR

Global navigation satellite system-based synthetic aperture radar interferometry (GNSS-based InSAR) systems can achieve 3-D deformation retrieval by associating multiangle images of different satellites. However, the difference in the scene radar cross section (RCS) and resolution cells makes multiangle images vary considerably. In addition, low resolution will further aggravate the difference in multiangle images. In this letter, a multiangle images association algorithm is proposed for GNSS-based InSAR systems. First, the supervised area is introduced to describe the areas of the same deformation based on the persistent scatter (PS) point. Then, the initial multiangle images association results are obtained by overlapping all PS points supervised areas of all satellites. Finally, the associated areas are normalized to obtain valid associated results. The raw data from eight Beidou satellites are used to prove the effectiveness of the proposed algorithm.

Airborne Single-Pass Multi-Baseline InSAR Layover Separation Method Based on Multi-Look Compressive Sensing

Due to the small number of baselines (2–3), the traditional L1 norm compressive sensing method for layover solution in InSAR has poor separation ability and height estimation stability and a long operation time. This paper, based on the idea of multi-look, adopts a multi-look compressive sensing method and a multi-look compressive sensing method based on separable approximate sparse reconstruction. The layover separation method based on multi-look compressive sensing adopts the surrounding pixels around the current point as independent observations together with this point to increase the observation vector in compressive sensing, and uses the singular value decomposition method to obtain the noise value, which is used to improve the dimensions of measured data in compressive sensing, reduces the noise level, and improves the stability of noise estimation. Meanwhile, the results of the multi-look L1 norm solution method are closer to those of the L0 norm solution, and the sparse reconstruction ability of compressive sensing is improved. Thus, the separation ability of the scatterers in the layover areas and the stability of height estimation are stronger. In addition, the multi-look compressive sensing method based on separable approximate sparse reconstruction constructs differential operation and soft functions, transforms the L1–L2 norm optimization into an iterative soft threshold shrinkage processing mode, and improves the processing speed by means of the threshold iteration method, which can effectively reduce the operation time while maintaining the resolution ability of scatterers in layover areas and the height direction estimation accuracy and provides the possibility for large-scale data processing. These two methods are effectively verified by means of simulation and measured data. The simulation experiments of the two methods are based on the airborne MEMPHIS system with four antennas, and the height values of the layover scatterers solved by the two methods are more reliable, stable, and closer to the real value than those solved by the traditional compressive sensing method. The operation time of the separable approximate sparse reconstruction method is comparable to the processing time of the traditional compressive sensing method and nearly one-quarter that of the multi-look compressive sensing method. The real data experiments of the two methods are based on the airborne Millimeter-wave InSAR system with three antennas. The two methods both have certain height resolutions in the height direction estimation of layover areas and fine elevation continuity, while traditional compressive sensing method cannot satisfy the condition of sparsity and has poor scatterer separation and elevation continuity. Nevertheless, the multi-look compressive sensing method is a little more stable than the separable approximate sparse reconstruction method, and the operation time of the separable approximate sparse reconstruction method is comparable to the traditional compressive sensing method and nearly one-fifth that of the multi-look compressive sensing method.

Key issues of InSAR system designment based on satellite formation

Key issues of InSAR system designment based on satellite formation

Error analysis and 3D reconstruction using airborne array InSAR images

Multi-temporal synthetic aperture radar interferometry (MT-InSAR) is able to detect surface deformation and reconstruct a 3D surface model with high precision but requires a long observation period to accumulate the multi-baseline SAR images. The airborne array InSAR system is able to acquire a stack of multi-baseline SAR images in a single acquisition, which significantly improves the 3D modeling capability. However, processing the images obtained by the low-altitude platform using the conventional model will lead to geometric approximation (GA) errors, such as flattened phase error and reference error, which degrade the precision of the 3D reconstruction. In this paper, we quantitatively analyze the error sources of the array-InSAR interferograms and design a hybrid 3D phase unwrapping approach for 3D reconstruction. A hypothesis test is developed to identify the phase ambiguity by comparing the initial solution of the least-square with that of the beam-forming. Three indicators are proposed to identify the reliable arcs, achieving a reliable phase unwrapping. The L1 norm approach is adopted to detect the unwrapping errors during the spatial unwrapping and a two-tie network strategy is used to process the data in the individual blocks from the perspective of global optimization. Furthermore, an iterative scheme is recommended to compensate the geometric approximation errors. The main advantage of the proposed algorithm is the compensation of the GA error and reliable phase unwrapping. The experimental results by both simulated and real SAR data show that the proposed algorithm can eliminate the GA error and provide a viable solution to rapid 3D SAR imaging with an airborne platform.

Analysis and correction of ionospheric dispersion effect in spaceborne bistatic InSAR system

Analysis and correction of ionospheric dispersion effect in spaceborne bistatic InSAR system

Velocity Estimation of Ocean Surface Currents in along-Track InSAR System Based on Conditional Generative Adversarial Networks

Velocity estimation of ocean surface currents is of great significance in the fields of the fishery, shipping, sewage discharge, and military affairs. Over the last decade, along-track interferometric synthetic aperture radar (along-track InSAR) has been demonstrated to be one of the important instruments for large-area and high-resolution ocean surface current velocity estimation. The calculation method of the traditional ocean surface current velocity, as influenced by the large-scale wave orbital velocity and the Bragg wave phase velocity, cannot easily separate the current velocity, characterized by large error and low efficiency. In this paper, a novel velocity estimation method of ocean surface currents is proposed based on Conditional Generative Adversarial Networks (CGANs). The main processing steps are as follows: firstly, the known ocean surface current field diagrams and their corresponding interferometric phase diagrams are constructed as the training dataset; secondly, the estimation model of the ocean surface current field is constructed based on the pix2pix algorithm and trained by the training dataset; finally, the interferometric phase diagrams in the test dataset are input into the trained model. In the simulation experiment, processing results of the proposed method are compared with those of traditional ocean surface current velocity estimation methods, which demonstrate the efficiency and effectiveness of the novel method.

Accuracy analysis of multi-baseline InSAR height inversion

Digital elevation model (DEM) is of great significance in commercial and scientific applications, and the accuracy of elevation inversion represents the quality of DEM. With reference to the height measurement accuracy formula of single-baseline interferometric SAR, the mathematical relations between elevation accuracy and platform height, lower viewing angle, target oblique distance, baseline strip number, baseline length and baseline roll angle are established, and the variation of elevation accuracy with system parameters (especially the number of base lines and baseline length) is quantitatively analyzed, and the optimal range of multi-baseline InSAR system parameters is obtained. It provides a theoretical basis for the optimal design of system parameters.

Multisystem Interferometric Data Fusion Framework: A Three-Step Sensing Approach

The recent, sharp increase in the availability of interferometric data captured by different synthetic aperture radar (SAR) interferometry (InSAR) sensors poses a new scientific question that whether there is a processing framework that can combine these observations to obtain a more credible InSAR product (i.e., digital elevation model (DEM) and surface deformation estimation). In this article, we extend our previous two-stage programming-based multibaseline processing framework for combining the interferograms generated from disparate InSAR systems with different system parameters to enhance the InSAR performance at the signal processing stage. The proposed multisystem interferometric data fusion framework, abbreviated as TSDFF, includes three processing steps: multisystem interferogram registration, multisystem phase unwrapping, and absolute phase fusing. The advantage of TSDFF is that it can allow the data sets from different InSAR sensors to help each other to get rid of the limitation of the Itoh condition so that the application scope of each InSAR sensor will be effectively enlarged (e.g., measuring violent surface change or mountainous DEM). In addition, to quantitatively analyze the measurement bias robustness bound of TSDFF, the TSDFF-Fusion theorem is proposed, which offers significant application guidance for TSDFF at different noise levels. The real and simulated experimental results reveal the effectiveness of TSDFF for fusing the data sets from disparate InSAR systems.

AN APPROACH TO POSITIONAL QUALITY CONTROL METHODS FOR AIRBORNE INSAR HIGH-RESOLUTION X-BAND ORTHOIMAGES AND P-BAND DIGITAL TERRAIN MODEL

Abstract: The positional validation of datasets is an important step for cartography studies since it allows learning about its accuracy, and also indicates the data process quality. However, the positional validation of Synthetic Aperture Radar (SAR) datasets have some additional challenges when compared to optical images due to the geometric distortions. We employ existing targets such as traffic signs and lampposts in the scene and identify them on the image as control points. We performed the validation of the geographic coordinates used as planialtimetric positional control points, using both the amplitude backscattering orthoimage and the Digital Terrain Model (DTM) generated from the InSAR system. We employed the NMAS, ASPRS and NSSDA tests along with information by the Brazilian Standards. This validation showed these control points presented the following results for 1:10,000 scale: NMAS test - class “A” in PEC and PEC-PCD; ASPRS test - RMSE x = 1.317m, RMSE y = 1.231m and RMSE z = 1.145m; and NSSDA test - RMSE r = 1,802m, Precision r = 3.118m and Precision z = 2.244m. These results prove we can use the proposed targets as control points and the used InSAR datasets meet the expected quality for generation of geotechnic products for 1:10,000 scale.

Deformation Monitoring of Slopes With a Shipborne InSAR System: A Case Study of the Lancang River Gorge

Differential synthetic aperture radar interferometry (DInSAR) is a remote sensing technique to monitor ground deformation using repeat-pass data and suitable processing methods. Different platforms have been used to acquire DInSAR data such as space-borne, air-borne, car-mounted, and ground-based SAR systems. Space-borne SAR systems are relatively mature, but air-borne and other systems have attracted increasing interest of the remote sensing community due to their operational flexibility and observation capabilities. In this paper, a new InSAR platform is proposed for the deformation monitoring of reservoir slopes. The shipborne InSAR system uses frequency modulated continuous wave (FMCW) technology with one-transmit-dual-receive configuration. First, we describe the data acquisition process at the Lancang River Bank in October 2019. Subsequently, we present the imaging and interferometric capabilities of the new shipborne InSAR system. Moreover, we analyze the acquired radar data and present an assessment of the quality of the single look complex (SLC) SAR imagery and interferometric products. We focus on the influence of platform stability and baseline bias. Finally, we compare the calculated deformation with the measured deformation obtained from corner reflectors deployed in the monitored area. A line-of-sight error within 2cm is obtained. This paper proposes a novel solution for deformation monitoring of reservoir slopes and a new approach for InSAR applications.

Evaluation and Analysis of Interferograms from an InSAR Radar Encrypted by an AES-Based Cryptosystem with The Five Encryption Modes

This paper falls within the framework of the security of satellite images, in particular interferograms from an Interferometric Synthetic Aperture Radar (inSAR) system. The innovation of this work consists in the application of a cryptosystem based on two algorithms Advanced Encryption Standard (AES) and the Rivest, Shamir and Adleman (RSA) encryption algorithm for securing interferograms of inSAR systems. AES employs five encryption modes Electronic Code Book (ECB), Cipher Bloc Chaining (CBC), Cipher FeedBack (CFB), Output FeedBack (OFB), and counter-mode encryption (CTR). The use of the AES algorithm alone can only ensure the confidentiality function. In the proposed cryptosystem confidentiality is ensured by the AES algorithm, authenticity is guaranteed by the RSA algorithm, and integrity is ensured by two parameters; the correlation function between the adjacent pixels and the SSIM parameters (structural similarity index SSIM). For evaluation and analysis of security performance for interferogram encryption, several test metrics are employed. These metrics are: Analysis of histograms of the encrypted interferograms, correlation between the adjacent pixels, between the original interferogram and the encrypted interferogram, SSIM between the original interferogram and the decrypted one. Moreover, we exploit the analysis of resistance to error propagation for the five modes. The obtained results show a superiority of the OFB and CTR modes for the encryption of inSAR interferograms compared to ECB, CFB, and CBC modes. It is noteworthy, that the main criteria that can be used to choose between OFB and CTR for encryption of satellite images are propagation of errors and the complexity material for their locations on the edges of the satellites propagation of errors and the complexity material for their locations on the edges of the satellites. OFB mode is employed in satellites to minimize the number of on-board circuits, which is decisive for satellites. CTR mode is recommended by the CCSDS (Consultative Committee for Space Data Systems) for telemetry (TM) and remote control (TC) encryption.

Number of Pixel Change Rate and Unified Average Changing Intensity for Sensitivity Analysis of Encrypted inSAR Interferogram

The transmission of images from satellites to earth is on the brink of many threats which can affect the confidentiality of the data as well as its quality. Several encryption algorithms are used to secure the transmitted images. The objective in this work is to analyze the sensitivity of a particular type of satellite image, which is an interferogram from interferometric imaging systems inSAR system. This image is encrypted by cryptosystem based on the Advanced Encryption Standard with key length of 256 bits (AES-256) standard and the asymmetric Rivest, Shamir &amp; Adelman (RSA) encryption algorithm using Counter-mode encryption (CTR) mode and Output FeedBack (OFB) mode. The analysis made in this paper is carried out on two types of sensitivity. The first analysis is the sensitivity to change of a pixel in the original interferogram and the second is the sensitivity to the key. Two parameters are used to assess sensitivity: The Number of Pixel Change Rate (NPCR) and the Unified Average Changing Intensity (UACI). The obtained results show that the two modes AES-256-OFB and AES-256-CTR are favorable but cannot be implemented on board a satellite without providing a mechanism capable of compensating for the low resistance to error propagation. Metrics on the clear and encrypted interferogram are exploited such as the Structural Similarity Index (SSIM), Gradient-based Structural Similarity (GSSIM), The use of these metrics, allowed us to see that a change of one pixel in the interferogram and the change of the encryption key will affect the quality of the interferogram, as well as a statistical histogram analysis.

Baseline Design for Multibaseline InSAR System: A Review

Multibaseline (MB) synthetic aperture radar (SAR) interferometry (InSAR) is an exciting and growing remote sensing technique, which can improve the traditional InSAR from the ill-posed problem to the well-posed problem. Baseline lengths play an important role in the MB InSAR system design. It is fair to say that the baseline lengths of the MB InSAR system directly determine the quality of the MB InSAR products. In this article, we present an overview of the established MB baseline design criteria and requirements for the MB InSAR digital elevation model (DEM) generation, which includes the effect of the baseline lengths and their estimation errors on ambiguity height, DEM accuracy, decorrelation, and MB phase unwrapping robustness. In addition, we prospectively apply the geometric programming technique to combine those effects together for obtaining the global optimal baseline lengths of the MB InSAR system. It is our hope that this review will provide guidelines to future researchers to enhance further the new airborne and spaceborne MB InSAR system developments.

Accuracy detection of Satellite and InSAR Technology in the Deformation Monitoring in Civil Engineering

This paper focuses on the application of Satellite Navigation Positioning System (such as GPS and BeiDou Navigation Satellite System) and InSAR technology in healthy monitoring in civil engineering. Considering the high cost of Satellite Positioning measurement and blind spot of InSAR measurement, it is reasonable to combine both technologies for accomplishing regionally area and focused points monitoring. During the study, the control network points were positioned with GPS measurement technique and height differences were supported with precise levelling measurements. As the result of measurement campaigns, the height differences were determined from the GPS measurements and InSAR measurements respectively. Later on, deformation analysis using the height differences according to provided data from the GPS and the data from the InSAR system were carried out separately. The comparison between GPS and InSAR results will be shown in the paper.

A SINGLE-PASS AIRBORNE INTERFEROMETRIC CALIBRATION METHOD RESEARCH FOR DEM MAPPING

Abstract. This paper presents a novel single-pass airborne interferometric calibration method with a limited Number GCPs for InSAR digital elevation model (DEM) mapping. The proposed method is based on a rigorous three-dimensional model for a single-pass airborne InSAR system. The corrected InSAR parameters of baseline length, baseline inclination, near slant range, and Doppler centroid frequency, as well as phase offset, can be jointly solved via a unified optimization procedure in terms of the constructed three-dimensional geometric model using a limited number ground control points (GCPs). The proposed method is evaluated on real data of the CASMSAR system in X-band, the final DEMs generated by the calibration processing achieve a high accuracy level (1–3 m standard deviation), even in the presence of only 3–5 GCPs.

On the Capabilities of the Italian Airborne FMCW AXIS InSAR System

Airborne Synthetic Aperture Radar (SAR) systems are gaining increasing interest within the remote sensing community due to their operational flexibility and observation capabilities. Among these systems, those exploiting the Frequency-Modulated Continuous-Wave (FMCW) technology are compact, lightweight, and comparatively low cost. For these reasons, they are becoming very attractive, since they can be easily mounted onboard ever-smaller and highly flexible aerial platforms, like helicopters or unmanned aerial vehicles (UAVs). In this work, we present the imaging and topographic capabilities of a novel Italian airborne SAR system developed in the frame of cooperation between a public research institute (IREA-CNR) and a private company (Elettra Microwave S.r.l.). The system, which is named AXIS (standing for Airborne X-band Interferometric SAR), is based on FMCW technology and is equipped with a single-pass interferometric layout. In the work we first provide a description of the AXIS system. Then, we describe the acquisition campaign carried out in April 2018, just after the system completion. Finally, we perform an analysis of the radar data acquired during the campaign, by presenting a quantitative assessment of the quality of the SLC (Single Look Complex) SAR images and the interferometric products achievable through the system. The overall analysis aims at providing first reference values for future research and operational activities that will be conducted with this sensor.