Synthetic Aperture Radar Applications Research Articles

High-isolation and Side Lobe Level Reduction for Dual-band Series-fed Centre-fed X/Ku Shared Aperture Binomial Array Antenna for Airborne Synthetic Aperture Radar Applications

High-isolation and Side Lobe Level Reduction for Dual-band Series-fed Centre-fed X/Ku Shared Aperture Binomial Array Antenna for Airborne Synthetic Aperture Radar Applications

Interferometric Synthetic Aperture Radar (InSAR) applications for mapping of terrain displacement in mineral deposits

The Interferometric Synthetic Aperture Radar (InSAR) applications for mapping of terrain displacement have been tested on the Vlaykov Vruh and Tsar Assen porphyry-copper deposits to test terrain displacements and possible fault movements. Time series for each area have been prepared to display the evolution of displacement over time, for a given point for both Cu-porphyry outcrops.

Phase Estimation for Distributed Scatterers by Alternating Projection

Decorrelation is a major obstacle to the application of multitemporal interferometric synthetic aperture radar (InSAR) in areas with low coherence. Distributed scatterers (DSs) with similar backscattering in the spatial neighborhood are the key to improving the observational density and accuracy of deformation estimation in fast decorrelation regions. Phase series estimation from all possible interferograms is expected to improve the signal-to-noise ratio (SNR) and further enhance the sensitivity of deformation measurement. The coherence bias and the efficiency of the phase estimation raise concerns. In this article, we propose a computationally attractive algorithm for the interferometric phase estimation, namely alternating projection (AP), which is a combination of the alternating maximization and the projection matrix decomposition methods. The homogenous pixel selection and coherence estimation bias correction are conducted by the FaSHPS algorithm and DSIpro software toolbox. Results of simulations and real SAR data show that the proposed AP method could reconstruct credible phase series comparable to the quasi-Newton optimization algorithm [Broyden–Fletcher–Goldfarb–Shanno (BFGS)] while having three times the efficiency gain.

Distance Measures of Polarimetric SAR Image Data: A Survey

Distance measure plays a critical role in various applications of polarimetric synthetic aperture radar (PolSAR) image data. In recent decades, plenty of distance measures have been developed for PolSAR image data from different perspectives, which, however, have not been well analyzed and summarized. In order to make better use of these distance measures in algorithm design, this paper provides a systematic survey of them and analyzes their relations in detail. We divide these distance measures into five main categories (i.e., the norm distances, geodesic distances, maximum likelihood (ML) distances, generalized likelihood ratio test (GLRT) distances, stochastics distances) and two other categories (i.e., the inter-patch distances and those based on metric learning). Furthermore, we analyze the relations between different distance measures and visualize them with graphs to make them clearer. Moreover, some properties of the main distance measures are discussed, and some advice for choosing distances in algorithm design is also provided. This survey can serve as a reference for researchers in PolSAR image processing, analysis, and related fields.

A low-thrust finite state machine based controller for N-satellites formations in distributed synthetic aperture radar applications

Spacecraft formation flying has attracted notable interest in recent years, thanks to the properties of flexibility to different mission needs and enhanced robustness and capabilities compared to monolithic space systems. A key element for the full exploitation of this technology consists in the automation of formation management and control, allowing higher independence from ground stations as well as prompter reactions and higher autonomy in task-assignment and decision making. In this context, this work proposes a distributed architecture to autonomously coordinate and control formations containing any number of members applying low-thrust propulsion and employing finite state machines to make decisions and assign tasks to the elements of the formation based on their current state. The nominal relative trajectories (called slots) are represented within the architecture through a set of geometric parameters characterizing their stability, size, and shape. The architecture can autonomously maintain the spacecraft on a set of nominal slots, as well as reconfigure the formation to a newly assigned geometry and deal with contingency situations, performing collision avoidance manoeuvres and keeping track of the slots of the formation that remain empty to autonomously define a course of action allowing the evading spacecraft to re-join the formation safely. At the same time, a strategy for the identification of the geometrical conditions to be violated to efficiently perform formation maintenance is proposed. The architecture is tested by means of numerical simulations within a GMAT-MATLAB integrated environment considering a quasi-linear safe ellipse formation aimed at distributed synthetic aperture radar applications as reference test case. Simulation results demonstrate that the proposed architecture allows effective autonomous coordination within tight formations, with cm-level ΔV expenses, while being fully scalable with the number of satellites.

Bibliometric Analysis of Interferometric Synthetic Aperture Radar (InSAR) Application in Land Subsidence from 2000 to 2021

Land subsidence is one of the serious natural disasters which can cause heavy casualties and economic losses. As a vital method, Interferometric Synthetic Aperture Radar (InSAR) can provide quick and efficient solutions for analysis. Currently, most reviews on InSAR application in land subsidence only focused on single types of land areas, such as the land around groundwater and land of the mining area. There is a lack of discussion on all types of land areas. This study thus aims at conducting a bibliometric literature analysis of the existing literature from 2000 to 2021 to fill this gap. The authors used scientific mapping methods to analyze the InSAR applications in land subsidence so that researchers and practitioners can comprehend the procedure. Then, the authors identified the major research areas, development milestones, evolutionary stages, and the transaction dynamics of evolutionary stages. Knowledge maps of five aspects were applied and analyzed in this research, including temporal development analysis, countries and institutions, major research disciplines, high-frequency terms, and cocitation of high-citation papers. The results reveal that the research of land subsidence monitoring with InSAR is in the stage of diffusion from developing many tools and techniques to integrating with other research areas. Overall, the bibliometric results combined with evolutionary stages provide a holistic picture of the status quo and future trends in InSAR application in land subsidence.

Multi-Stream Fast Fourier Convolutional Neural Network for Automatic Target Recognition of Ground Military Vehicle

The synthetic aperture radar (SAR) is very useful in both military and civilian applications due to its 24/7, all-weather, and high resolution capabilities, as well as its ability to recognize camouflage and penetrating cover. In the field of SAR image interpretation, target recognition is an important research challenge for researchers all over the world. With the application of high-resolution SAR, the imaging area has been expanding, and different imaging modes have appeared one after another. There are many difficulties with the conventional understanding of human interpretation. There are issues like slow movement, a lot of labor, and poor judgment. Technology for intelligent interpretation needs to be developed immediately. Although deep convolutional neural networks (CNNs) have proven extremely efficient in image recognition, one of the major drawbacks is that they require more parameters as their layers increase. The cost of convolution operation for all convolutional layers is therefore high, and learning lag results from the inevitable rise in computation as the size of the image kernel grows. This study proposes a three ways input of SAR images into multi-stream fast Fourier convolutional neural network (MS-FFCNN). The technique elaborates on the transformation of rudimentary multi-stream CNN into MS-FFCNN. By utilizing the fast Fourier transformation instead of the standard convolution, it lowers the cost of image convolution in CNNs, which lowers the overall computational cost. The multiple streams of FFCNN overcome the problem of insufficient sample size and further improve the long training time while also improving the recognition accuracy. The proposed method yielded good recognition accuracy of 99.92%.

Wideband L/X-Band Shared-Aperture Phased Array Antenna for SAR Applications

In this article, a wideband shared-aperture phased array antenna is proposed for synthetic aperture radar (SAR) applications. A metal cavity-backed slot antenna and a slot antenna are used as the L- and X-band antenna elements, respectively. Notably, the X-band antenna elements are mounted on top of the L-band ones, and their interactions are successfully isolated by loading a layer of frequency selective surface (FSS). The FSS layer reflects the electromagnetic waves in X-band and allows transmission of the L-band electromagnetic waves, making the shared-aperture antenna work properly in L- and X-bands. Furthermore, a circular patch is designed to improve the bandwidth of the X-band antenna. Simulations indicate that the proposed antenna has impedance bandwidths of 46% in X-band (7.5–12 GHz) and 21% in L-band (1.7–2.1 GHz). Moreover, the X-band antenna can scan up to ±60° in the E-plane and ±30° in the H-plane with voltage standing wave ratio (VSWR) below 3. To verify the design method, a shared-aperture antenna prototype, which consists of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$6\times6$ </tex-math></inline-formula> X-band elements and one L-band element, has been fabricated and measured. Finally, the measured results agree well with the simulated ones.

A new phase unwrapping method for cross-track interferometric synthetic aperture radar systems

One of the essential applications of interferometric synthetic aperture radar (InSAR) systems is to estimate the ground surface height. To this end, the altitude of each pixel in the region is estimated according to the phase difference of the two received signals by two sensors. However, the sensor has an ambiguity in the relative terrain altitude due to the 2π cyclic nature of the interferometric phase, which leads to a significant error in altitude estimation. In this paper, by focusing on the phase unwrapping issue in InSAR processing, an efficient iterative approach to minimize the phase difference error is presented. For this purpose, first, according to the InSAR imaging geometry, the interferometric phase relationships are described. Second, based on the least-squares approach, the phase unwrapping problem is expressed as an optimization issue with a specific cost function. Third, the cost function is converted to a submodular convex Markov random field (MRF) function. Finally, the resulting optimization problem is solved by using a fast and efficient approach to optimize submodular convex MRF functions. The proposed method's performance is examined using several numerical studies compared to its relevant competitors. The mean square error (MSE) of elevation estimation is considered the performance metric. Numerical simulations have confirmed the efficiency of the proposed algorithm in terms of MSE of elevation estimation. As seen, the outperformance of the proposed method with respect to its best competitor is at least 2 times (3 dB). The operation times of various methods are also compared as a measure of their convergence rate. Based on simulation results, the convergence rate of the proposed algorithm is more than 50 times better than that of its closest competitor.

An efficient technique to realize low‐profile dual‐band multi‐polarized shared‐aperture slot antenna array

An efficient technique to realize dual-band multi-polarized shared-aperture slot antenna array is proposed in this paper, featuring in all-metal, low-profile, light-weight and high radiation efficiency. The cavity-backed longitudinal slots are used at L-band for vertical polarization, while horizontal and vertical polarizations are both achieved at C-band, by utilizing interleaved ridged waveguides with two different kinds of slots. A coaxial-feed end-grounded metallic bridge is developed to excite the L-band cavity-backed slots, so the volume and weight of the L-band cavity can be obviously reduced. To further make the whole antenna structure compact and tight, the reduced L-band cavity is embedded into the serration, surrounding by two adjacent C-band ridged waveguides for vertical polarization and one for horizontal polarization. An array prototype, which consists of two L-band single-polarized antennas and four pairs of C-band dual-polarized antennas, is fabricated and measured. Experimental results are well consistent with the simulated ones, showing a satisfying impedance bandwidth of 12% in L-band and 5.5% in C-band, and besides high radiation efficiency above 85% for both bands. The all-metallic structure of this proposed array provides the thermal and mechanical advantages for space-borne synthetic aperture radar (SAR) application.

An Improved Technique for Single-Channel Video-SAR Based on Fractional Fourier Transform

In the field of synthetic aperture radar (SAR), a lot of researchers have tried to study an improved application beyond the conventional two-dimensional image. Video-SAR (ViSAR) is one of the hot issue in the SAR application. The main purpose of ViSAR is to monitor various targets in the area of interest in time order. It can offer video images to detect not only the fixed target but also the moving target. For the signal processing of ViSAR, this article introduces the improved performance by the Doppler shifting technique with fractional Fourier transform. And also, it shows that the proposed method can separate the unexpected signal of the moving target within each frame of single-channel ViSAR. Furthermore, the overall algorithm can increase efficiency and reliability in ViSAR processing. To verify the improvement of our method, we carry out the practical experiments by an X-band chirp pulse SAR system, mounted on an airplane.

위성 SAR용 이중 반사판 검증을 위한 위상 배열 급전기 설계 및 제작

In this study, when developing a phased array feeder for the verification of dual reflector antennas for satellite synthetic aperture radar (SAR) applications, the main component test and performance verification of the feeder were considered. The performance was verified at the level of the component radiator, radiofrequency/control board, and integrated phased array feeder with specifications, including the bandwidth, polarization, directivity, beam width, and side lobe, required for the feeder. Accordingly, it was confirmed that the bandwidth was 19.18 % (H) and 16.07 % (V), directivity was 38.42 dBi (H), 38.32 dBi (V), HPBW Az/El 2.064° (H)/2.187° (H), 2.083° (V)/2.202° (V), and the side lobe was under −12.84 dB (H), −13.05 dB (V). Therefore, we verified that it can be adopted as a phased array feeder for the verification of dual reflector antennas for satellite SAR applications.

Research on Configuration Constraints of Airborne Bistatic SARs.

Based on the analysis of the airborne bistatic synthetic aperture radar (SAR) imaging geometric mode, an extended nonlinear chirp scaling algorithm is employed to simulate and verify the imaging effect of the bistatic SARs. A gradient theory-based two-dimensional resolution bistatic SAR model is proposed, and the constraints of the multi-platform flight trajectory parameters meeting the imaging accuracy of the bistatic SAR are analyzed. Finally, through the bistatic SAR imaging simulation of cooperative flight trajectories under various situations, the spatial configuration constraint envelope between the flight vehicles to achieve the optimal resolution is revealed. The results of this paper will provide a theoretical reference for the SAR application in formation flight control.

Fast InSAR Time-Series Analysis Method in a Full-Resolution SAR Coordinate System: A Case Study of the Yellow River Delta

Ground deformation is a major determinant of delta sustainability. Sentinel-1 Terrain Observation by Progressive Scans (TOPS) data are widely used in interferometric synthetic aperture radar (InSAR) applications to monitor ground subsidence. Due to the unparalleled mapping coverage and considerable data volume requirements, high-performance computing resources including graphics processing units (GPUs) are employed in state-of-the-art methodologies. This paper presents a fast InSAR time-series processing approach targeting Sentinel-1 TOPS images to process massive data with higher efficiency and resolution. We employed a GPU-assisted InSAR processing method to accelerate data processing. Statistically homogeneous pixel selection (SHPS) filtering was used to reduce noise and detect features in scenes with minimal image resolution loss. Compared to the commonly used InSAR processing software, the proposed method significantly improved the Sentinel-1 TOPS data processing efficiency. The feasibility of the method was investigated by mapping the surface deformation over the Yellow River Delta using SAR datasets acquired between January 2021 and February 2022. The findings indicate that several events of significant subsidence have occurred in the study area. Combined with the geological environment, underground brine and hydrocarbon extraction as well as sediment consolidation and compaction contribute to land subsidence in the Yellow River Delta.

Radar and multispectral remote sensing data accurately estimate vegetation vertical structure diversity as a fire resilience indicator

AbstractThe structural complexity of plant communities contributes to maintaining the ecosystem functioning in fire‐prone landscapes and plays a crucial role in driving ecological resilience to fire. The objective of this study was to evaluate the resilience to fire off several plant communities with reference to the temporal evolution of their vertical structural diversity (VSD) estimated from the data fusion of C‐band synthetic aperture radar (SAR) backscatter (Sentinel‐1) and multispectral remote sensing reflectance (Sentinel‐2) in a burned landscape of the western Mediterranean Basin. We estimated VSD in the field 1 and 2 years after fire using Shannon's index as a measure of vertical heterogeneity in vegetation structure from the vegetation cover in several strata, both in burned and unburned control plots. Random forest (RF) was used to model VSD in the control (analogous to prefire scenario) and burned plots (1 year after fire) using as predictors (i) Sentinel‐1 VV and VH backscatter coefficients and (ii) surface reflectance of Sentinel‐2 bands. The transferability of the RF model from 1 to 2 years after wildfire was also evaluated. We generated VSD prediction maps across the study site for the prefire scenario and 1 to 4 years postfire. RF models accurately explained VSD in unburned control plots (R2 = 87.68; RMSE = 0.16) and burned plots 1 year after fire (R2 = 80.48; RMSE = 0.13). RF model transferability only involved a reduction in the VSD predictive capacity from 0.13 to 0.20 in terms of RMSE. The VSD of each plant community 4 years after the fire disturbance was significantly lower than in the prefire scenario. Plant communities dominated by resprouter species featured significantly higher VSD recovery values than communities dominated by facultative or obligate seeders. Our results support the applicability of SAR and multispectral data fusion for monitoring VSD as a generalizable resilience indicator in fire‐prone landscapes.

Sensing the Urban Environment by Automotive SAR Imaging: Potentials and Challenges

In this paper, we discuss the possibility of generating high-resolution mapping of urban (or extra-urban) environments by the application of synthetic aperture radar (SAR) processing concepts to the data collected by mm-wave automotive radars installed on-board commercial vehicles. The study is motivated by the fact that radar sensors are becoming an indispensable component of the equipment of modern vehicles, being characterized by low cost, good performance, and affordable processing; therefore, in the future, nearly every single vehicle could be potentially equipped with radar devices capable of high-resolution imaging, enabled by application of SAR processing methodologies. Throughout this paper, we aim to discuss the role of SAR imaging in the automotive context under a theoretical and experimental perspective. First, we present the resulting benefits in terms of angular resolution and signal-to-noise ratio. Then, we discuss relevant technological aspects, such as suppression of angular ambiguities, fine estimation of platform motion, and SAR processing architectures, and we present a preliminary evaluation of the required computational costs. Finally, we will present a number of experimental results based on open road campaign data acquired using an 8-channel MIMO radar at 77 GHz, considering the cases of side-looking SAR, forward SAR, and SAR imaging of moving targets.

Superstructure scattering features and their application in high-resolution SAR ship classification

Ship classification in high-resolution (HR) synthetic aperture radar (SAR) images is an important and challenging task. The deep learning methods rely heavily on massive labeled data, which is not practical for SAR applications due to the lack of feature consistency under different sensors, angle of view, and scenarios, while the statistical methods are vulnerable to noise, image quality, and radiometric calibration and have poor robustness. To overcome these problems, a more robust superstructure scattering feature, named scattering bright line feature, is proposed to realize the convenient classification of ships in engineering applications. Based on this, a decision tree classifier for three types of merchant ships is developed. Four types of HR SAR slices are used to verify the validity of the new feature by both the decision tree and support vector machine classifiers, and the results show that the proposed feature has good classification performance in merchant ships with an overall accuracy higher than 80%.

Сучасні низькоорбітальні угруповання космічних апаратів дистанційного зондування землі з використанням радарів із синтезованою апертурою

The purpose of this work is to determine the current trends in the development of low-orbit constellations of spacecraft with synthetic aperture radar (SAR), which have a number of significant advantages in Earth remote sensing. It is shown that the demand for Earth remote sensing data and products and services based thereon continues to grow worldwide. The applicability of SAR to Earth remote sensing is considered. The main differences and advantages of image acquisition using SAR spacecraft in comparison with optical spacecraft are shown. The main directions of using low-orbit SAR spacecraft in Earth remote sensing are identified. Land and water surface observation using SAR spacecraft is shown to be one of the most effective remote sensing methods. In particular, it is shown that low-orbit spacecraft constellations can be used to advantage in solving many tasks in the socio-economic sector and tasks aimed at continuous real-time monitoring of various objects. The characteristics of the various Earth remote sensing spacecraft constellations, in particular low-orbit commercial ones, launched into orbit during the past decade are considered. Problems in and prospects for the development of low-orbit SAR spacecraft constellations are elucidated. Existing and planned SAR spacecraft constellations with traditional and mini-satellite platform technologies are overviewed. It is shown that the performance characteristics continue to improve, thus allowing one to get data from any area of the Earth at any time. It is shown that small spacecraft in low and ultralow orbits have significant benefits over traditional spacecraft in power characteristics, but are outperformed by them in the duration of communication sessions and active life. The results obtained make it possible to work out recommendations on the designing of low-orbit constellations of domestic Earth remote sensing spacecraft, in particular on the development of orbit determination models and algorithms and spacecraft dynamics models.

SAR Signal Formation and Image Reconstruction of a Moving Sea Target

Maritime application of synthetic aperture radar (SAR) technology for sea-target surveillance and imaging is considered in this study. A SAR scenario, including the kinematics of a SAR satellite and a ship moving on the sea, along with the geometry of the target, are analytically described. A linear frequency modulation (LFM) waveform is applied for the target’s illumination. Based on the target’s geometry, SAR and target kinematics and the LFM waveform, a SAR signal model is synthesized. It is proven that the process of signal formation is a transformation of the three-dimensional (3D) image into a two-dimensional (2D) signal, whereas the target’s 2D imaging is an inverse transformation of the 2D signal into the target’s 2D image. SAR signal components, linear Fourier terms and higher-order phase terms are analytically derived and discussed in detail. Moreover, it is proven that SAR image reconstruction is a motion-compensation procedure, i.e., it removes all phases induced by first- and higher-order motion. Based on the SAR signal analysis, an illustrative iterative image-reconstruction algorithm is derived. The quality of the imaging is evaluated by an entropy cost function. Simulation experiments are carried out to verify the correctness of the theoretical statements in respect of SAR signal formation and image reconstruction.

Temporal Coherence Estimators for GBSAR

Many Ground-Based Synthetic Aperture Radar (GBSAR) applications demand preliminary analysis to select areas with high-quality signal. That is, areas in which the phase can be processed to extract the desired information. The interferometric coherence and the amplitude dispersion index are important tools widely used in the literature to assess the quality of GBSAR images. So far, no direct relation has been found between the two. Indeed, they are parameters of different natures: amplitude dispersion index is calculated with only amplitude values, while coherence provides information also on the signal phase. The purpose of this article is to find a relation between the two parameters. Indeed, the amplitude dispersion index provides some practical advantages if compared to coherence estimators, especially to perform fast preliminary analysis. In this article, a theoretical relation between amplitude dispersion index and coherence is retrieved. GBSAR measurements acquired in different scenarios, at different working frequencies are presented and used to validate such a relation.