Circular Synthetic Aperture Radar Research Articles

A Backprojection-Based Imaging for Circular Synthetic Aperture Radar

Circular synthetic aperture radar (CSAR) has attracted much attention in the field of high-resolution SAR imaging. However, the CSAR image focusing is affected by the motion deviations of platform. In the processing of experimental CSAR data to deal with motion errors, the main way is using setup calibrators, which restricts its widespread applications. In this paper, based on the estimation of motion errors, an autofocus CSAR imaging strategy is proposed without using any setup calibrator. The first step is to split the entire aperture into several subapertures, the second step is to process the data in subapertures with an autofocus backprojection method, and the last step is to obtain the final CSAR image by merging the subimages obtained from the subaperture processing. The CSAR data processing results prove that the proposed strategy can remove the motion errors accurately and acquire well-focused CSAR images.

Holographic SAR Tomography Image Reconstruction by Combination of Adaptive Imaging and Sparse Bayesian Inference

In this letter, we propose an imaging algorithm for the holographic synthetic aperture radar tomography in the circumstance of sparse and nonuniform elevation circular passes. Considering the anisotropic behavior of scatterers and the off-grid effect of sparse signal recovery, the algorithm combines the 2-D adaptive imaging method for circular SAR and the sparse Bayesian inference-based method for elevation reconstruction. For each circular pass, the azimuth-range 2-D image can be formed by the adaptive imaging method, which depends on the preretrieved maximum azimuth response angle and the azimuth persistence width. To deal with the off-grid effect in elevation reconstruction, which is caused by the deviation between the true scatterers and the discretized imaging grids, the off-grid sparse Bayesian inference method jointly estimates the scatterers and elevation off-grid error by applying their hierarchical priors. Compared with the conventional compressive sensing method that does not concern the off-grid effect, the proposed algorithm can provide more accurate 3-D reconstruction for pointlike targets, which is verified by the real-data experiments.

Fast Factorized Backprojection Algorithm for One-Stationary Bistatic Spotlight Circular SAR Image Formation

In this paper, a fast factorized backprojection (FFBP) algorithm is proposed for the one-stationary bistatic spotlight circular synthetic aperture radar (OS-BSCSAR) data processing. This method represents the subimages on polar grids in the slant-range plane instead of the ground plane, which can be accurately referenced to the tracks of both transmitter and receiver. It can not only accurately accommodate the complicated circular track including the motion error, scene topographic information, large spatial variances and significant range-azimuth coupling of the echo data, but also improve the imaging efficiency compared with the backprojection (BP) algorithm. First, OS-BSCSAR imaging geometry is provided, and then the bistatic BP algorithm for the OS-BSCSAR imaging is derived to provide a basis for the proposed FFBP algorithm. Second, based on the subaperture imaging model, the polar grids for calculating the subimages are defined, and the sampling requirements for the polar grids are derived from the viewpoint of the bandwidth, which can offer the near-optimum tradeoff between the imaging quality and the imaging efficiency. Finally, implementation and computational burden of the proposed FFBP algorithm is discussed, and then the speed-up factor of the proposed FFBP algorithm with respect to the bistatic BP algorithm is derived. Experiment results are given to prove the correctness of the theory analysis and validity of the proposed FFBP algorithm.

A 3D Reconstruction Strategy of Vehicle Outline Based on Single-Pass Single-Polarization CSAR Data.

In the last few years, interest in circular synthetic aperture radar (CSAR) acquisitions has arisen as a consequence of the potential achievement of 3D reconstructions over 360° azimuth angle variation. In real-world scenarios, full 3D reconstructions of arbitrary targets need multi-pass data, which makes the processing complex, money-consuming, and time expending. In this paper, we propose a processing strategy for the 3D reconstruction of vehicle, which can avoid using multi-pass data by introducing a priori information of vehicle's shape. Besides, the proposed strategy just needs the single-pass single-polarization CSAR data to perform vehicle's 3D reconstruction, which makes the processing much more economic and efficient. First, an analysis of the distribution of attributed scattering centers from vehicle facet model is presented. And the analysis results show that a smooth and continuous basic outline of vehicle could be extracted from the peak curve of a noncoherent processing image. Second, the 3D location of vehicle roofline is inferred from layover with empirical insets of the basic outline. At last, the basic line and roofline of the vehicle are used to estimate the vehicle's 3D information and constitute the vehicle's 3D outline. The simulated and measured data processing results prove the correctness and effectiveness of our proposed strategy.

Estimation of current velocity using circular SAR data

A method of current velocity estimation using airborne sea data is proposed. The sea data are collected by circular synthetic aperture radar. The range Doppler image can be acquired after range and azimuth compression for each beam scan angle. The corresponding average Doppler spectrum can be obtained and fitted to Gaussian shape well. Hence, the Doppler centre shift can be represented by the mean of Doppler spectrum. It is observed that the Doppler centre varies with the beam scan angle and the variation is approximately a sinusoid-shape function. The velocity and direction of current in a local area are fixed so the radial velocity caused by the current is a harmonic function of the scan angle. Therefore, the current velocity can be obtained by the amplitude of the harmonic. Actually, the radial velocity does not only include the current, but also includes the surface wave motion. However, the method presented can obtain the real current velocity directly, avoiding adopting the radial velocity of the scatterer, so the estimation of the current velocity is accurate.

Adaptive imaging of anisotropic target based on circular‐SAR

The isotropic reflectivity assumption is a valid approximation in traditional narrow-angle synthetic aperture radar (SAR). However, for large angular ranges most targets exhibit only limited scattering persistence. Therefore, this assumption is violated in circular-SAR (CSAR). Thus, the performance of traditional fully coherent image formation is poor in CSAR, because coherent integration over the entire aperture will obscure aspect-independent reflectivity characteristics. To address this problem, an adaptive imaging algorithm which accommodates anisotropic targets to improve image quality is proposed. The efficient use of valid azimuth angles can reduce noise and errors and highlight anisotropic targets in CSAR image. Another advantage of this algorithm is that the anisotropy target scattering behaviour can be extracted by data inversion in the imaging process. Compared with the sub-aperture approach, which can also extract the anisotropic scattering properties of target, the data inversion approach in the algorithm can provide more accurate results and a finer curve. The adaptive imaging method is validated in this Letter by simulation and an airborne dataset.

The Analysis and Realization of Motion Compensation for Circular Synthetic Aperture Radar Data

Regarding the two-dimensional (2-D) imaging processing of circular synthetic aperture radar (CSAR), the motion compensation (MOCO) in the frequency domain is not fully developed. To perform the MOCO for CSAR data in the frequency domain, a novel three-step strategy is presented in this paper. The motion error model is established first, and it is found that a difficulty of MOCO for CSAR lies in the space variance of the motion errors. Specifically, according to the proposed MOCO strategy, this first step is space-invariant MOCO, the second step is space-variant MOCO in the range-compressed angular-wavenumber domain with respect to subaperture data, and the last step is the autofocus operation in the 2-D wavenumber domain after the polar format resampling. Eventually, the complete MOCO flowchart is obtained. Simulation and experimental tests verify that the proposed motion error model is valid and the three-step MOCO strategy can remove motion errors accurately and figure out well-focused CSAR images.

Detection of Moving Targets by Refocusing for Airborne CSSAR

Due to the advantage of short revisit time, airborne circular stripmap synthetic aperture radar (CSSAR) is an attractive tool for air-to-ground surveillance and reconnaissance. This paper deals with the issue of ground moving-target detection with an airborne CSSAR and proposes a new autofocus-based detection algorithm. The prominent features of the proposed algorithm are the incorporation of the Doppler ambiguity information into the autofocus-based moving-target detection and the ability to solve the problem of large range cell migration, which affects most of autofocus algorithms. The proposed algorithm can detect not only the targets whose azimuth chirp rates are different from that of the static clutter background but also the targets whose Doppler ambiguities are different from that of the static clutter background. Numerical results show that the proposed algorithm works well in both homogeneous and heterogeneous clutter backgrounds.

Two-Dimensional Spectrum for Circular Trace Scanning SAR Based on an Implicit Function

For circular trace scanning synthetic aperture radar (CTSSAR), the conventional approximated quadratic range equation assumption does not hold due to the impact of the curved flight path. Thus, existing SAR methods cannot focus the target accurately and efficiently in CTSSAR. To address this problem, the stationary phase can be regarded as an implicit function of the Doppler frequency. Therefore, the 2-D spectrum can be consequently achieved by employing the principle of stationary phase. In this letter, an imaging algorithm based on the derived spectrum is developed for CTSSAR. Promising results from simulation demonstrate the validity and effectiveness of the approach.

Motion and Doppler Characteristics Analysis Based on Circular Motion Model in Geosynchronous SAR

The Doppler characteristics of geosynchronous synthetic aperture radar (GEO SAR) cannot be explained by the conventional linear motion model (LMM), and the work modes of GEO SAR have not been clearly illustrated. To solve these problems, a circular motion model (CMM) is proposed based on the mathematical concept of curvature circle. GEO SAR is considered to run along the curvature circle whose center is not the earth center at most orbital positions. Then, the velocity of the zero-Doppler plane is derived based on the CMM to correctly express the Doppler parameters and analyze the Doppler characteristics of GEO SAR. Analyses results indicate that the circular motion of GEO SAR causes the sign-variant velocity of the zero-Doppler plane, which then induces the complex Doppler characteristics. Furthermore, GEO SAR is considered to work in two different modes according to the motion and Doppler characteristics. When the Doppler rate is zero or near zero, GEO SAR is similar to a partial aperture circular SAR (CSAR) and has a nonlinear time–frequency relationship, which causes the invalidity of the conventional frequency-domain imaging algorithms. When the Doppler rate is nonzero, GEO SAR is similar to the low-earth-orbit (LEO) SAR. Finally, the validity of this study is verified by computer simulations. The proposed CMM can explain the complex Doppler characteristics of GEO SAR. The derived expressions and the work mode analyses can provide further directions for the system design and imaging.

Height Profile Estimation of Power Lines Based on Two-Dimensional CSAR Imagery

In circular synthetic aperture radar (CSAR) mode, a 2-D image contains 3-D spatial information about the imaged targets. This letter describes an attempt to estimate the height profiles of power lines with slightly varying heights based on 2-D CSAR imagery. First, according to the characteristics of a 2-D CSAR image of a power line with constant height, an approximate formula is deduced to calculate the height of the power line. This formula can also be used to calculate the height of several power lines with the same constant height. Second, a three-step processing method is proposed for height profile estimation of power lines with slightly varying heights. The first step is to extract regions of power lines automatically. The second step is to obtain the initial heights of the power lines according to the deduced approximate formula. The third step is to estimate the final height profiles of the power lines. Finally, experimental results have shown that 2-D imaging results of power lines with slightly varying heights are well focused when the height profiles estimated by the proposed three-step method are used.

Fourier-Based 2-D Imaging Algorithm for Circular Synthetic Aperture Radar: Analysis and Application

Circular synthetic aperture radar (CSAR) has become a research hotspot in the SAR community. Since the Fourier-based imaging methods of CSAR are underdeveloped, further developments have to be investigated. In this paper, the exact expression and property analysis of the spectrum of CSAR are presented first. It turns out that the challenges of the Fourier-based 2-D imaging processing of CSAR lie in the projection of spectrum from the slant plane into the ground plane. Correspondingly, a spectrum-projection method by matched filtering as well as the practical subaperture-based imaging flow of CSAR are proposed, during which the trajectory deviation has been taken into account. Simulation and experimental tests are carried out to measure the efficiency and accuracy of the proposed method. The corresponding results verify that the proposed signal model is correct and the presented imaging flow is a good candidate to produce well-focused CSAR imagery with much less time consumption.

Airborne DLSLA 3-D SAR Image Reconstruction by Combination of Polar Formatting and <inline-formula> <tex-math notation="LaTeX">$L_1$</tex-math></inline-formula> Regularization

Airborne downward-looking sparse linear array 3-D synthetic aperture radar (DLSLA 3-D SAR) operates downward-looking observation and obtains the 3-D microwave scattering information of the observed scene. The cross-track physical sparse linear array is often configured to obtain uniform virtual phase centers in order to adopt the frequency-domain algorithm. However, the virtual phase centers usually have to be nonuniformly and sparsely distributed due to the array elements' installation locations restricted by the airborne platform and the airborne wing tremor effect. In this state, the frequency-domain algorithm cannot be directly used. In this paper, a DLSLA 3-D SAR image reconstruction algorithm that combines polar formatting and $L_1$ regularization is presented. Wave propagation and along-track dimensional imaging are first finished after polar formatting and wavefront curvature phase error compensation; then, cross-track dimensional imaging is completed with the $L_1$ regularization technique. The proposed algorithm is applicable to airborne DLSLA 3-D SAR imaging under nonuniformly and sparsely distributed virtual phase centers condition. The proposed algorithm was verified by 3-D distributed scene simulation experiment (P-band circular SAR image was selected as radar cross-section input, and X-band digital elevation model of the same area was selected as the coordinate positions of the scene) and the field experiment. Image reconstruction results and image reconstruction performances, such as normalized radar cross section, height errors, and orthographic projection image grayscale distribution, are demonstrated and analyzed with different signal-to-noise ratios, different array sparsity, and the incomplete compensated residual oscillation error 3-D distributed scene simulation experiments. Simulation and field experimental results show the good performance in focusing and the robustness of the proposed algorithm.

A Focusing Algorithm for Circular SAR Based on Phase Error Estimation in Image Domain

Residual motion error is common in high-resolution circular Synthetic Aperture Radar (SAR) image defocusing. The Signal-to-Clutter Ratio (SCR) in echo data domain is relatively low; thus, the phase error spans several range bins. To solve this problem, we propose a focusing algorithm for circular SAR based on phase-error estimation in the image domain. The method estimates the point-target image window interception and then the phase error from echo regeneration in the defocused image. Subsequently, the range migration error is calculated, and finally, the phase error in the echo data is compensated for azimuth focusing and range cell migration correction. Simulation and real-data processing verified the proposed method.

Vehicle Layover Removal in Circular SAR Images via ROSL

Circular synthetic aperture radar (CSAR) has raised interest in both wide-aspect-angle 2-D imaging and 3-D feature reconstruction. As for CSAR 2-D imaging with a 360° aperture, vehicles spotlighted in the scene are depicted with multiview layover, which makes the imagery intuitively less comprehensible. In addition, the shape of the layover bulge depends on the elevation of the radar platform. Thus, otherwise identical vehicle targets appear differently in the image when the elevation deviates from a constant, which makes target discrimination more difficult. In this letter, subaperture images are vectorized and stacked to build a composite matrix. Decomposing the composite matrix via robust orthonormal subspace learning results in a low-rank matrix and a sparse matrix. The layover belongs to the sparse matrix and thus can be get rid of. The performance of the proposed method has been verified on synthesized and real CSAR data sets. Experimental results show that the multiview layover of vehicles is eliminated effectively. Moreover, the CSAR images become insensitive to elevation variation after layover removal, which benefits target discrimination.

Statistical Models of Speckle for Circular SAR Imaging

Statistical Models of Speckle for Circular SAR Imaging

Breast tumor detection using UWB circular-SAR tomographic microwave imaging.

This paper describes the possibility of detecting tumors in human breast using ultra-wideband (UWB) circular synthetic aperture radar (CSAR). CSAR is a subset of SAR which is a radar imaging technique using a circular data acquisition pattern. Tomographic image reconstruction is done using a time domain global back projection technique adapted to CSAR. Experiments are conducted on a breast phantoms made of pork fat emulating normal and cancerous conditions. Preliminary experimental results show that microwave imaging of a breast phantom using UWB-CSAR is a simple and low-cost method, efficiently capable of detecting the presence of tumors.

Expediting back‐projection algorithm for circular SAR imaging

The availability of an expediting back-projection (EBP) algorithm for circular synthetic aperture radar (CSAR) imaging is investigated. EBP works by dividing the full aperture into sub-apertures, and using a unified polar grid to generate sub-images. On the basis of the correspondence between the wavenumber domain and the phase history domain, EBP combines all sub-aperture spectrums into a full-aperture one and reconstructs the CSAR image followed by a two-dimensional (2D) fast Fourier transform. Without time-consuming 2D interpolation, EBP is capable of decreasing the loss of spectrum, while improving significantly the computational efficiency compared with direct BP.

Wide‐field circular SAR imaging: An empirical assessment of layover effects

ABSTRACTIn circular synthetic aperture radar (CSAR), targets are usually scanned over the complete azimuthal aperture of 360°. A major challenge inhibiting successful CSAR image production is encountered in two‐dimensional imaging of relatively large scenes (i.e. wide‐field scenarios). For such cases, the spatially variant radar signature gives rises to image degradations known as layover effects. In this paper, the imaging results for hypothetical and real complex targets using their CSAR data at C band are demonstrated to characterize these effects. In real experiments, a ground‐based, outdoor CSAR system is exploited thanks to the circular balcony of a building that provides 270° view of targets. A spherical back‐projection algorithm is used to focus near‐field data and the reconstructed images are also cleaned out from clutter to more easily visualize the layover artifacts. © 2015 Wiley Periodicals, Inc. Microwave Opt Technol Lett 57:489–497, 2015

A New Imaging Method for Circular Trace Scanning SAR with Wide Observation

Circular Trace Scanning SAR is a new strip map mode SAR imaging in recent years, its imaging speed is fast with larger scene. This paper first establishes the imaging geometry right, by the four order approximation of the oblique distance model, combined with the series inversion method, and the removal of the coupling terms in the spectrum in the range Doppler domain, finally complete the azimuth compression. The simulation results prove the validity and feasibility of the imaging.