Synthetic Aperture Radar Focusing Research Articles

Very High Resolution Automotive SAR Imaging from Burst Data

This paper proposes a method for efficient and accurate removal of grating lobes in automotive Synthetic Aperture Radar (SAR) images. Grating lobes can indeed be mistaken as real targets, inducing in this way false alarms in the target detection procedure. Grating lobes are present whenever SAR focusing is performed using data acquired on a non-continuous basis. This kind of acquisition is typical in the automotive scenario, where regulations do not allow for a continuous operation of the radar. Radar pulses are thus transmitted and received in bursts, leading to a spectrum of the signal containing gaps. We start by deriving a suitable reference frame in which SAR images are focused. It will be shown that working in this coordinate system is particularly convenient since it allows for a signal spectrum that is space-invariant and with spectral gaps described by a simple one-dimensional function. After an inter-burst calibration step, we exploit these spectral characteristics of the signal by implementing a compressive sensing algorithm aimed at removing grating lobes. The proposed approach is validated using real data acquired by an eight-channel automotive radar operating in burst mode at 77 GHz. Results demonstrate the practical possibility to process a synthetic aperture length as long as up to 2 m reaching in this way extremely fine angular resolutions.

Ultra-High-Resolution Spaceborne and Squint SAR Imaging for Height-Variant Geometry Using Polynomial Range Model

In this article, we propose an entire processing chain that addresses the geometrical defocusing problems caused by a large orbital arc, a high squint, and topography variations in ultra-high-resolution (UHR) synthetic aperture radar (SAR) operations. Slant-range histories are formulated using fifth-order polynomials to accurately express radar signals with a UHR spaceborne and squint SAR geometry. SAR focusing is first conducted with a constant height assumption. Thereafter, residual topography errors are compensated. Several beneficial contributions are included in the proposed processing chain. First, to achieve constant-height SAR focusing, we improve the typical least-square decomposition-based Stolt interpolations in terms of the image quality and computation time. Second, we clarify how illuminated areas are mapped in a two-dimensional imaging domain after polynomial-based focusing, which is completely different from the well-known relationship between the closest range and zero-Doppler time. Third, a generalized blockwise postfocusing method is devised to correct the range and azimuth defocusing effects induced by height variations. These contributions are verified using numerical simulations. Thus, we can conclude that the proposed method can provide focused SAR images for a height-variant geometry in UHR spaceborne and squint operations.

Detection and Localization of Closely Spaced Pipelines Using a 3-D Multistatic Subsurface SAR

Detection and localization of buried pipelines is an important problem for oil and water distribution industries as well as for excavation and construction companies. A novel 3D forward scattering model and dynamic grid search-based inversion algorithm of multiple buried pipelines using multistatic synthetic aperture radar (SAR) configuration is demonstrated in this article. Traditional imaging algorithms that focus the SAR signals by compensating only for the phase work well when the targets are far away from each other. By considering both the phase and amplitude of the scattered field and casting the inversion problem as an optimization problem, the detection and localization resolutions are improved for extended targets. A forward scattering model for multiple adjacent pipes is developed to track the scattering phase centers of each pipeline as the receiver location is changed. The model is used to calculate the resulting propagation phase and amplitude attenuation due to propagation in lossy media. The misfit between the measured data and the forward model is used as the cost function. The cost function is minimized by the dynamic grid search algorithm that starts with an initial focusing and then performs a more careful search to detect closely spaced pipelines. The forward model and inversion algorithm are validated and compared to a basic focusing algorithm using full-wave simulations as well as experimental data for both metallic as well as dielectric pipes. The results show improvement in range and cross range detection and localization resolutions over the basic SAR focusing algorithm.

Motion Estimation and Compensation in Automotive MIMO SAR

With the advent of self-driving vehicles, autonomous driving systems will have to rely on a vast number of heterogeneous sensors to perform dynamic perception of the surrounding environment. Synthetic Aperture Radar (SAR) systems increase the resolution of conventional mass-market radars by exploiting the vehicle’s ego-motion, requiring very accurate knowledge of the trajectory, usually not compatible with automotive-grade navigation systems. In this setting, radar data are typically used to refine the navigation-based trajectory estimation with so-called <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">autofocus</i> algorithms. Although widely used in remote sensing applications, where the timeliness of the imaging is not an issue, autofocus in automotive scenarios calls for simple yet effective processing options to enable real-time environment imaging. This paper aims at providing a comprehensive theoretical and experimental analysis of the autofocus <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">requirements</i> in typical automotive scenarios. We analytically derive the effects of navigation-induced trajectory estimation errors on SAR imaging, in terms of defocusing and wrong targets’ localization. Then, we propose a motion estimation and compensation workflow tailored to automotive applications, leveraging a set of stationary Ground Control Points (GCPs) in the low-resolution radar images (before SAR focusing). We theoretically discuss the impact of the GCPs position and focusing height on SAR imaging, highlighting common pitfalls and possible countermeasures. Finally, we show the effectiveness of the proposed technique employing experimental data gathered during open road campaign by a 77 GHz multiple-input multiple-output radar mounted in a forward-looking configuration.

A Fast Back-Projection SAR Imaging Algorithm Based on Wavenumber Spectrum Fusion for High Maneuvering Platforms

In this paper, a fast back-projection (BP) synthetic aperture radar (SAR) imaging algorithm based on wavenumber spectrum fusion is proposed for high maneuvering platforms with high squint angles and high dive angles. When the platforms have nonlinear trajectory errors, the trajectory errors will introduce significant spectrum displacement, which varies with the target position. If the influence of trajectory error is not considered, the trajectory’s deviation from the ideal SAR imaging geometry will degrade the focusing performance. The dive angle will further enlarge the influence on SAR focusing. In this paper, the center function of the spatially variable sub-aperture wavenumber spectrum is derived, firstly, which is the basis for reasonably setting the oversampling rate. Then, the accurate spectrum fusion method is proposed, which is efficiently implemented by fast Fourier transform (FFT) and circular shifting. The proposed algorithm is called high-squint and high-dive accelerated factorized back-projection (HSHD-AFBP). Compared to the commonly used spectrum fusion method, HSHD-AFBP not only improves the imaging quality, but also expands the image width. Finally, the effectiveness of the proposed algorithm is verified by simulation data.

Passive Synthetic Aperture Radar Imaging Using Radio-Astronomical Sources

Recent work has demonstrated a passive radio sounding approach that uses the Sun as a source for echo detection and ranging. As the Sun is a moving source with a position that is known <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">a priori</i> , we evaluate this technique’s capabilities to measure the echo’s phase history, map topography, and perform synthetic aperture radar (SAR) focusing. Here, we present our approach to implementing passive SAR using a compact, temporally incoherent radio-astronomical source as a signal of opportunity. We first evaluate the passive system’s capabilities to obtain an echo from a rough surface by determining the critical signal-to-noise ratio (SNR) for reliably observing the Sun’s echo reflection with our passive instrument. We then demonstrate that our technique can detect the necessary changes in range, phase, and reflectivity of an echo from the Sun. We next present the experimental results of our passive radar testing using the Sun at Dante’s View, Death Valley, to highlight this technique’s ability to perform 2-D imaging. Finally, with synthetic data, we demonstrate that we can use time-domain backprojection to focus a planar white noise signal, perform passive SAR imaging, and improve the measurement’s SNR and azimuth resolution. The results of passive SAR focusing on white noise highlight the potential for the Sun and Jupiter’s radio emissions to perform surface and subsurface imaging for planetary and terrestrial observations.

Delay Doppler SAR Focusing and Quantitative Quality Control of the Radar for Europa Assessment and Sounding: Ocean to Near-Surface (REASON) Sounding Data Product

Synthetic aperture radar (SAR) focusing will be a fundamental step in the analysis of the radar sounding datasets collected by the Radar for Europa Assessment and Sounding: Ocean to Near-surface (REASON) instrument as part of NASA's upcoming Europa Clipper mission. Due to the flyby trajectory of the mission, REASON data acquisition will be distinct compared to other space-borne radar sounders, and therefore, require a tailored SAR focusing strategy. Here, we present a SAR focusing architecture based on the delay Doppler approach employed in US SHAllow RADar (SHARAD) data analysis with the following modifications for REASON data idiosyncrasies; an interpolation to a constant ground track interval to account for REASON's variable PRF; and an adaptive Doppler centroid estimation to account for the flyby geometry. The ability of our modified delay Doppler SAR focusing approach to focus space-borne datasets as well as its specific feasibility for REASON are demonstrated using both SHARAD and MARSIS datasets. In addition, we present a quantitative quality control framework based on pixel power probabilities and demonstrate how it can be leveraged to quantify the effects of SAR focusing and differentiate focused results generated with different processing parameters. Finally, we revisit and discuss the assumption of depth-independent SAR focusing implicit in the choice to construct a REASON SAR focusing approach based on the delay Doppler method and provide a comparison with depth-dependent SAR focusing for a simplified acquisition geometry.

A 3D Image Reconstruction Model for Long Tunnel Geological Estimation

Long tunnels often collapse during the construction period. To ensure personnel safety, the geological characteristics must be predicted before tunnel face excavation. In this study, the ground-penetrating radar (GPR) technique is introduced to obtain information regarding the tunnel excavation face at a certain interval. The amplitude of the radar echo signal is expressed as a function of the position and travel time. A B-scan strategy is selected for the GPR to obtain tunnel information. A frequency-domain ( w -k) focusing algorithm, namely, a synthetic aperture radar focusing algorithm, is applied to focus scattered radar signals to obtain focused images. A low-pass filter is designed to remove noises from the original signals. The contours of target objects are extracted from the background information using the edge detection technique. Space coordinate values of the objects are converted to polar coordinates using the Hough transform algorithm for 3D modeling. Visual C++ and AutoCAD are combined to develop a 3D CAD model to help managers in controlling the construction process. The system creates 3D visualization model images and evaluates the geological characteristics of the tunnel excavation faces. The Taigu Tunnel located in the Shanxi Province of China is taken as a case study. A procedure for the geological analysis of this tunnel is introduced in detail, and a 3D image model is built. The results show that the 3D model can help predict rock compositions and locate potential hazards. Moreover, it has better accuracy than conventional models and can be applied to similar transportation construction projects.

SodSAR: A Tower-Based 1-10 GHz SAR System for Snow, Soil and Vegetation Studies.

We introduce SodSAR, a fully polarimetric tower-based wide frequency (1–10 GHz) range Synthetic Aperture Radar (SAR) aimed at snow, soil and vegetation studies. The instrument is located in the Arctic Space Centre of the Finnish Meteorological Institute in Sodankylä, Finland. The system is based on a Vector Network Analyzer (VNA)-operated scatterometer mounted on a rail allowing the formation of SAR images, including interferometric pairs separated by a temporal baseline. We present the description of the radar, the applied SAR focusing technique, the radar calibration and measurement stability analysis. Measured stability of the backscattering intensity over a three-month period was observed to be better than 0.5 dB, when measuring a target with a known radar cross section. Deviations of the estimated target range were in the order of a few cm over the same period, indicating also good stability of the measured phase. Interforometric SAR (InSAR) capabilities are also discussed, and as a example, the coherence of subsequent SAR acquisitions over the observed boreal forest stand are analyzed over increasing temporal baselines. The analysis shows good conservation of coherence in particular at L-band, while higher frequencies are susceptible to loss of coherence in particular for dense vegetation. The potential of the instrument for satellite calibration and validation activities is also discussed.

A New Fast Factorized Back-Projection Algorithm with Reduced Topography Sensibility for Missile-Borne SAR Focusing with Diving Movement

Time-domain algorithms have significant performance advantages for missile-borne synthetic aperture radar (SAR) focusing with diving movement. However, due to the diving curve trajectory of the missile platform, the range and angular histories of the target become very sensitive to unknown tomography, which provides difficulties for SAR algorithm development. To address this problem, we have proposed a new fast factorized back-projection (FFBP) algorithm with reduced topography sensibility for missile-borne SAR focusing. The new algorithm was designed based on an orthogonal cylindrical coordinate (OCC) system, in which the cross section of a cylinder in the coordinate system is approximately orthogonal to the diving curve trajectory. Owing to the acquisition symmetry of the OCC system, the range and the angular histories of the grid in the OCC geometry become less dependent of the topography in every recursion of FFBP implementation, which can dramatically reduce the adverse effects of unknown topography and achieve high focusing performance. In the simulation, echo signal based on a set of typical parameters from a missile-borne SAR system is generated with unknown tomography. Promising results with 1 m resolution are finally achieved, which demonstrates the performance of the proposed algorithm. The limitation of the algorithm is also discussed in the final part, which will facilitate the development of raw data processes in practical application.

Vegetated Target Decorrelation in SAR and Interferometry: Models, Simulation, and Performance Evaluation

The paper addresses the temporal stability of distributed targets, particularly referring to vegetation, to evaluate the degradation affecting synthetic aperture radar (SAR) imaging and repeat-pass interferometry, and provide efficient SAR simulation schemes for generating big dataset from wide areas. The models that are mostly adopted in literature are critically reviewed, and aim to study decorrelation in a range of time (from hours to days), of interest for long-term SAR, such as ground-based or geosynchronous, or repeat-pass SAR interferometry. It is shown that none of them explicitly account for a decorrelation occurring in the short-term. An explanation is provided, and a novel temporal decorrelation model is proposed to account for that fast decorrelation. A formal method is developed to evaluate the performance of SAR focusing, and interferometry on a homogenous, stationary scene, in terms of Signal-to-Clutter Ratio (SCR), and interferometric coherence. Finally, an efficient implementation of an SAR simulator capable of handling the realistic case of heterogeneous decorrelation over a wide area is discussed. Examples are given by assuming two geostationary SAR missions in C and X band.

Highly Squinted MEO SAR Focusing Based on Extended Omega-K Algorithm and Modified Joint Time and Doppler Resampling

A squinted observation geometry along with long integration time significantly aggravates the range walk and spatial variation of a medium-earth-orbit (MEO) synthetic aperture radar (SAR) signal. Variable pulse repeating frequency (PRF) is recommended to avoid the blockage in echo recording and save storage space. The existing wavenumber algorithms cannot handle the nonlinear and range–azimuth-coupled spatial variation (RACSP) over a large scene. In this paper, we propose a modified Stolt mapping method along with a modified joint time and Doppler resampling (JTDR) for highly squinted MEO SAR data processing. An azimuth timescale transformation is used to deal with the nonlinear spatial variation of the azimuth frequency-modulation (FM) rate. An extended Omega-K is used to linearize the range frequency and achieve range cell migration correction (RCMC). To address the RACSP, the Doppler is linearized in the range-Doppler domain using a range-dependent Doppler scale transformation. The computational complexity and geometry distortion correction (GDC) are also discussed. Simulation results are shown to verify the effectiveness of the developed focusing approaches.

A Phase-Preserving Focusing Technique for TOPS Mode SAR Raw Data Based on Conventional Processing Methods

We present a new solution for the phase-preserving focusing of synthetic aperture radar (SAR) raw data acquired through the Terrain Observation with Progressive Scan (TOPS) mode. The proposed algorithm consists of a first interpolation stage of the TOPS raw data, which takes into account the Doppler Centroid frequency variations due to the azimuth antenna steering function, and allows us to unfold the azimuth spectra of the TOPS raw data. Subsequently, the interpolated signals are processed by using conventional phase-preserving SAR focusing methods that exploit frequency domain and spectral analyses algorithms, which are extensively used to efficiently process Stripmap and ScanSAR data. Accordingly, the developed focusing approach is easy to implement. In particular, the presented focusing approach exploits one of the available frequency domain Stripmap processing techniques. The only modification is represented by the inclusion, within the 2D frequency domain focusing step, of a spurious azimuth chirp signal with a properly selected azimuthal rate. This allows us to efficiently carry out the TOPS azimuth focusing through the SPECAN method. Furthermore, an important aspect of this algorithm is the possibility to easily achieve a constant and tunable output azimuth pixel size without any additional computing time; this is a remarkable feature with respect to the full-aperture TOPS-mode algorithms available in the existing literature. Moreover, although tailored on Sentinel-1 (S1) raw data, the proposed algorithm can be easily extended to process data collected through the TOPS mode by different radar sensors. The presented experimental results have been obtained by processing real Sentinel-1 raw data and confirm the effectiveness of the proposed algorithm.

Squinted SAR focusing for improving automatic radar sounder data analysis and enhancement

ABSTRACTRadar sounder (RS) instruments are providing a huge amount of subsurface data. In order to support the study of this data, several automatic methods have been recently proposed. So far, the development of such methods mostly focused on publicly available radargrams (standard products), which are generated from raw data in order to obtain high visual quality images. The possibility to exploit raw processing to derive additional information for automatic analyses has not yet been considered. In order to fill this gap, in this paper, we show that by properly tuning raw signal processing it is possible to automatically obtain additional a priori information on subsurface targets. Such information can be used to potentially improve the results of further automatic analyses and/or address problems that cannot be easily solved automatically using only standard products. In particular, we propose four measurements obtained using squinted synthetic aperture radar focusing that provide useful physical information about subsurface features. Moreover, in order to prove the effectiveness of the proposed approach, a novel preprocessing method for automatic layer detection techniques based on the concepts developed in this paper is presented and validated. All the examples reported in the paper use real planetary RS data acquired by the SHAllow RADar instrument on Mars.

Detection and Imaging of Moving Targets With LiMIT SAR Data

Detecting moving targets in synthetic aperture radar (SAR) imagery has recently gained a lot of interest as a way to augment optical moving target detection and classification in adverse (e.g., cloudy) weather conditions. In this paper, we primarily focus on the problem of detecting and imaging moving targets in single-channel (or summed multichannel) SAR data. Single-channel-based methods provide the ability to do detection well below the normal minimum detectable velocity (MDV) of multichannel-based GMTI. This can be particularly important for small radar antennas, which tend to have high conventional GMTI MDV. We also show results for multiple channel geolocation after single-channel detection and imaging. The algorithms consist of the following steps. We first suppress the stationary scene by comparing noncoherent time-subimages. We then detect the movers by applying a set of possible motion corrections to the image and use a novel matched filter to detect the movers in this space. We can then image the moving targets using standard SAR focusing techniques and geolocate the movers using multichannel (if available) along-track interferometry. We demonstrate and evaluate our algorithms using data collected from the Lincoln Multimission ISR Testbed airborne radar system.

Atmospheric Phase Screen in GEO-SAR: Estimation and Compensation

We study the impact of atmospheric turbulence, specifically the wet tropospheric delay, in that synthetic aperture radar (SAR) with very long integration time, from minutes to hours, and wide swaths, such as the geosynchronous or geostationary SAR. In such systems, the atmospheric phase screen (APS) cannot be assumed frozen in time as for Low Earth Orbit or airborne SARs nor constant in space as for the ground-based SAR. The impact of space–time turbulence on SAR focusing is quantitatively assessed, and a novel focusing method that integrates APS estimation and compensation is proposed. Performances are evaluated as a function of SAR parameters, mainly the wavelength, based on a parametric model of the APS variogram, and results achieved by a simulating realistic scenario are shown.

Three‐dimensional SAR imaging of sea targets with low PRF sampling

Three-dimensional (3D) synthetic aperture radar (SAR) image formation provides the scene reflectivity estimation along azimuth, range, and elevation coordinates. A common 3D SAR focusing approach is compressed sensing (CS)-based SAR tomography, but this technique brings image quality problems because of the undesired side-lobes in the focused two-dimensional (2D) images. Moreover, the amount of raw data, which is used for 3D imaging, is still very large. To reduce the amount of raw data and achieve satisfying 3D resolving ability, a novel 3D imaging method based on multidimensional CS (MCS) is proposed for multi-baseline SAR. In this study, the multi-baseline SAR 3D raw signals are presented in space-time domain; and the proposed 3D imaging algorithm based on MCS is used to reduce the amount of raw data. The range, azimuth and elevation profiles can be reconstructed with an extremely low Pulse Recurrence Frequency (PRF) with this algorithm. Comparisons with the existing CS-tomographic focusing method are also presented. Experimental results demonstrate that the proposed algorithm can efficiently solve the 3D imaging task with limited PRF sampling.

Airborne DInSAR Results Using Time-Domain Backprojection Algorithm: A Case Study Over the Slumgullion Landslide in Colorado With Validation Using Spaceborne SAR, Airborne LiDAR, and Ground-Based Observations

The major impediment to accurate airborne repeat-pass differential synthetic aperture radar (SAR) interferometry (DInSAR) is compensating for aircraft motion caused by air turbulence. Various motion compensation (MoCo) procedures have been used in the airborne DInSAR processing to acquire reliable deformation mapping. In this paper, we present the use of time-domain backprojection (BP) algorithm for SAR focusing in an airborne DInSAR survey: No MoCo procedure is needed because the BP algorithm is inherently able to compensate for platform motion. In this study, we present the results of a pilot study aimed at demonstrating the feasibility of deformation mapping with an airborne SAR system based on the monitoring of the Slumgullion landslide in Colorado, USA between July 3 and 10 of 2015. The employed airborne SAR system is an Artemis SlimSAR that is a compact, modular, and multi-frequency radar system. Airborne light detection and ranging and global navigation satellite system (GNSS) observations, as well as spaceborne DInSAR results using COSMO-SkyMed (CSK) images, were used to verify the performance of the airborne SAR system. The surface velocities of the landslide derived from the airborne DInSAR observations showed good agreement with the GNSS and spaceborne DInSAR estimates. A three-dimensional deformation map of the Slumgullion landslide was also generated, which displayed distinct correlation between the landslide motion and topographic variation. This study shows that an inexpensive airborne L -band DInSAR system has the potential to measure centimeter level deformation with flexible temporal and spatial baselines.

Fast and Efficient Correction of Ground Moving Targets in a Synthetic Aperture Radar, Single-Look Complex Image

Ground moving targets distort normally-focused synthetic aperture radar (SAR) images. Since most high-resolution SAR data providers only offer single-look complex (SLC) data rather than raw signals to general users, they need to apply a simple and efficient residual SAR focusing to SLC data containing moving targets. This paper presents an efficient and effective SAR residual focusing method that is practically applicable to SLC data. The residual Doppler spectrum of the moving target is derived from a general SAR configuration and normal SAR focusing. The processing steps are simple and straightforward, with a limited size of the processing window, e.g., 64 × 64. Application results using simulation data and actual TerraSAR-X SLC data with a speed-controlled vehicle demonstrate the effectiveness of the method, which particularly improves the −3 dB width, integrated sidelobe ratio, and symmetry of the reconstructed signals. In particular, the azimuthal symmetry becomes seriously distorted when the target speed is higher than 8 m/s (or 28.8 km/h), and the symmetry is well recovered by the proposed method.

Experimental operation of drone micro‐SAR with efficient time‐varying velocity compensation

Drone platform for synthetic aperture radar (SAR) operation has been little publicised due to the technical constraint of the payload implementation. Multi-rotor drone based SAR is distinguished from the conventional airborne system by the increased sensitivity to turbulences and poor motion stability. Extremely limited power and mass budgets may prevent the use of extra hardware for motion compensation and the difficulty of SAR focusing is aggravated. Feasibility of micro-SAR drone operation is investigated through field tests, where experimental SAR images are acquired over ground targets. Attempts have been made to implement near-real-time compensation for non-uniform motion disturbance. Finally, experimental drone SAR operation is validated through calibrated SAR images.