Spotlight Synthetic Aperture Radar Imaging Research Articles

Highly squinted SAR imaging simulation of ship‐ocean scene based on EM scattering mechanism

To investigate highly squinted spotlight synthetic aperture radar (SAR) images of an electrically large ship target over a rough sea surface, this work focuses on the simulation analysis of SAR images from such a composite scene. For this problem, there are two key issues need to be considered, namely the simulation and the processing of SAR echoes. Considering the first issue, an efficient facet scattering model based on capillary wave modification facet scattering model and geometrical optics and physical optics hybrid method is applied to calculate the electromagnetic (EM) scattering characteristics from a real ship-ocean scene, based on which SAR echoes can be obtained. For the second issue, a non-linear frequency scaling algorithm (NFSA) is employed to efficiently process the highly squinted SAR echoes. Compared with the traditional frequency scaling algorithm, the NFSA extends the frequency scaling operation to the cubic order and makes a more accurate secondary range compression. With the solutions to the two issues, SAR images of a complicated ship-ocean scene under different incident and squint angles are presented and analysed. The reasonable results demonstrate the validity of the simulation approach and the practicability of the model for highly squinted spotlight SAR images.

Numerical simulation of highly squinted spotlight SAR images from complex targets using an amendatory frequency scaling algorithm

ABSTRACTIn the highly squinted spotlight synthetic aperture radar (SAR) image simulation of complex electrically large targets, the principal difficulties consist of the generation and the processing of SAR echo. Concerning the above two issues, this paper proposed a complete procedure for highly squinted SAR image simulation. Firstly, in order to generate the SAR echo efficiently and accurately, the geometrical optics and physical optics (GO-PO) hybrid method is employed to get the spatial distributed scattering fields, which is an essential step for the generation of SAR echo. Secondly, regarding to the processing of highly squinted SAR echo, the amendatory frequency scaling algorithm (AFSA) is adopted. Compared with the benchmark frequency scaling algorithm (FSA), AFSA eliminates the trouble caused by the range-dependent secondary range compression (SRC) error in high squint mode through the nonlinear frequency scaling (NFS) operation. Finally, according to the complete simulation procedure, SAR images of a complex ship target under different radar parameters are simulated and analysed. The simulation results indicate the performance of AFSA in the processing of highly squinted SAR echo. Meanwhile, the effectiveness and the reasonability of the complete simulation procedure are revealed as well.

Sliding Spotlight Mode Imaging with GF-3 Spaceborne SAR Sensor.

Synthetic aperture radar (SAR) sliding spotlight work mode can achieve high resolutions and wide swath (HRWS) simultaneously by steering the radar antenna beam. This paper aims to obtain well focused images using sliding spotlight mode with the Chinese Gaofen-3 SAR sensor. We proposed an integrated imaging scheme with sliding spotlight echoes. In the imaging scheme, the two-step approach is applied to the spaceborne sliding spotlight SAR imaging algorithm, followed by the Doppler parameter estimation algorithm. The azimuth spectral folding phenomenon is overcome by the two-step approach. The results demonstrate a high Doppler parameter estimation accuracy. The proposed imaging process is accurate and highly efficient for sliding spotlight SAR mode.

Synthetic aperture radar imaging simulator for pulse envelope evaluation

A simulator for spotlight synthetic aperture radar (SAR) image formation is presented. The simulator produces radar returns from a virtual radar positioned at an arbitrary distance and altitude. The radar returns are produced from a source image, where the return is a weighted summation of linear frequency-modulated (LFM) pulse signals delayed by the distance of each pixel in the image to the radar. The imagery is resampled into polar format to ensure consistent range profiles to the position of the radar. The SAR simulator provides a capability enabling the objective analysis of formed SAR imagery, comparing it to an original source image. This capability allows for analysis of various SAR signal processing techniques previously determined by impulse response function (IPF) analysis. The results suggest that IPF analysis provides results that may not be directly related to formed SAR image quality. Instead, the SAR simulator uses image quality metrics, such as peak signal-to-noise ratio (PSNR) and structured similarity index (SSIM), for formed SAR image quality analysis. To showcase the capability of the SAR simulator, it is used to investigate the performance of various envelopes applied to LFM pulses. A power-raised cosine window with a power p=0.35 and roll-off factor of β=0.15 is shown to maximize the quality of the formed SAR images by improving PSNR by 0.84 dB and SSIM by 0.06 from images formed utilizing a rectangular pulse, on average.

Autofocused Spotlight SAR Image Reconstruction of Off-Grid Sparse Scenes

Synthetic aperture radar (SAR) has significant role in remote sensing. Phase errors due to uncompensated platform motion, measurement model mismatch, and measurement noise can cause degradations in SAR image reconstruction. For efficient processing of the measurements, image plane is discretized and autofocusing algorithms on this discrete grid are employed. However, in addition to the platform motion errors, the reflectors, which are not exactly on the reconstruction grid, also degrade the image quality. This is called the off-grid target problem. In this paper, a sparsity-based technique is developed for autofocused spotlight SAR image reconstruction that can correct phase errors due to uncompensated platform motion and provide robust images in the presence of off-grid targets. The proposed orthogonal matching pursuit-based reconstruction technique uses gradient descent parameter updates with built in autofocus. The technique can reconstruct high-quality images by using sub Nyquist rate of sampling on the reflected signals at the receiver. The results obtained using both simulated and real SAR system data show that the proposed technique provides higher quality reconstructions over alternative techniques in terms of commonly used performance metrics.

Multi-linear sparse reconstruction for SAR imaging based on higher-order SVD

This paper focuses on the spotlight synthetic aperture radar (SAR) imaging for point scattering targets based on tensor modeling. In a real-world scenario, scatterers usually distribute in the block sparse pattern. Such a distribution feature has been scarcely utilized by the previous studies of SAR imaging. Our work takes advantage of this structure property of the target scene, constructing a multi-linear sparse reconstruction algorithm for SAR imaging. The multi-linear block sparsity is introduced into higher-order singular value decomposition (SVD) with a dictionary constructing procedure by this research. The simulation experiments for ideal point targets show the robustness of the proposed algorithm to the noise and sidelobe disturbance which always influence the imaging quality of the conventional methods. The computational resources requirement is further investigated in this paper. As a consequence of the algorithm complexity analysis, the present method possesses the superiority on resource consumption compared with the classic matching pursuit method. The imaging implementations for practical measured data also demonstrate the effectiveness of the algorithm developed in this paper.

Generalized Chirp Scaling Combined with Baseband Azimuth Scaling Algorithm for Large Bandwidth Sliding Spotlight SAR Imaging.

This paper presents an efficient and precise imaging algorithm for the large bandwidth sliding spotlight synthetic aperture radar (SAR). The existing sub-aperture processing method based on the baseband azimuth scaling (BAS) algorithm cannot cope with the high order phase coupling along the range and azimuth dimensions. This coupling problem causes defocusing along the range and azimuth dimensions. This paper proposes a generalized chirp scaling (GCS)-BAS processing algorithm, which is based on the GCS algorithm. It successfully mitigates the deep focus along the range dimension of a sub-aperture of the large bandwidth sliding spotlight SAR, as well as high order phase coupling along the range and azimuth dimensions. Additionally, the azimuth focusing can be achieved by this azimuth scaling method. Simulation results demonstrate the ability of the GCS-BAS algorithm to process the large bandwidth sliding spotlight SAR data. It is proven that great improvements of the focus depth and imaging accuracy are obtained via the GCS-BAS algorithm.

Synthetic aperture radar with dynamic metasurface antennas: a conceptual development.

We investigate the application of dynamic metasurface antennas (DMAs) to synthetic aperture radar (SAR) systems. Metasurface antennas can generate a multitude of tailored electromagnetic waveforms from a physical platform that is low-cost, lightweight, and planar; these characteristics are not readily available with traditional SAR technologies, such as phased arrays and mechanically steered systems. We show that electronically tuned DMAs can generate steerable, directive beams for traditional stripmap and spotlight SAR imaging modes. This capability eliminates the need for mechanical gimbals and phase shifters, simplifying the hardware architecture of a SAR system. Additionally, we discuss alternative imaging modalities, including enhanced resolution stripmap and diverse pattern stripmap, which can achieve resolution on par with spotlight, while maintaining a large region-of-interest, as possible with stripmap. Further consideration is given to strategies for integrating metasurfaces with chirped pulse RF sources. DMAs are poised to propel SAR systems forward by offering a vast range of capabilities from a significantly improved physical platform.

Theoretical Application of Overlapped Subaperture Algorithm for Quasi-Forward-Looking Parameter-Adjusting Spotlight SAR Imaging

This letter theoretically extends and applies the overlapped subaperture algorithm (OSA) for the challenging spotlight synthetic aperture radar (SAR) imaging in a quasi-forward-looking (QFL) geometry. A parameter-adjusting framework, in which the radar parameters relate closely to the geometry, is employed to mitigate the spatial signal coupling. By innovatively fitting the phase error induced by the planar wavefront assumption directly to the wavenumbers, both the linear and quadratic phase errors, which determine the geometrical distortion and the defocusing effects, respectively, can be accurately expressed and then corrected. When compared with the parameter-adjusting polar format algorithm proposed by the authors in previous work, the OSA is superior in contributing to an expanded imaging swath. The validity of the OSA methodology is demonstrated by the simulation of a Ka-band SAR working in the QFL diving mode with an extreme 85° squint angle.

SAR ATR by a combination of convolutional neural network and support vector machines

A combination of a convolutional neural network, which belongs to the deep learning research field, and support vector machines is presented as an efficient automatic target recognition system. Additional training methods that incorporate prior knowledge to the classifier and further improve its robustness against imaging errors and target variations are also presented. These methods generate artificial training data by elastic distortion and affine transformations that represent typical examples of image errors, like a changing range scale dependent on the depression angle or an incorrectly estimated aspect angle. With these examples presented to the classifier during the training, the system should become invariant against these variations and thus more robust. For the classification, the spotlight synthetic aperture radar images of the moving and stationary target acquisition and recognition database are used. Results are shown for the ten class database with a forced decision classification as well as with rejection class.

A coordinate-transform based FFBP algorithm for high-resolution spotlight SAR imaging

This paper proposes a coordinate-transform (CT) implementation for the fast factorized backprojection (FFBP) algorithm (CT-FFBP) to process high-resolution spotlight synthetic aperture radar (SAR) data. Unlike the FFBP utilizing two-dimensional image-domain interpolation for sub-aperture fusion, CT-FFBP finishes the image-projection using CT with the accommodation of chirp-z transform and circular shifting. Without interpolation, CT-FFBP yields enhanced efficiency over the interpolation based FFBP, besides maintaining high precision simultaneously. Both simulation and real-data experiments verifies the efficiency and precision superiorities of the CT-FFBP.

An Improved PFA With Aperture Accommodation for Widefield Spotlight SAR Imaging

This letter presents an improved polar format algorithm for nonlinear aperture and widefield spotlight synthetic aperture radar imaging. In the proposed algorithm, the chirp $z$ transform is used for uniform range resampling, while the fast Gaussian grid nonuniform fast Fourier transform is employed to focus the nonuniform samples in azimuth. Additionally, the space-variant postfiltering is incorporated for eliminating the geometric distortion and marginal defocusing effects induced by wavefront curvature. The effectiveness of the proposed algorithm is validated by simulation and real large scene Gotcha data set.

Power Spectra of Very High Resolution SAR Amplitude Images of Urban Areas

With the launch of COSMO/SkyMed and TerraSARX missions, very high resolution (VHR) Synthetic Aperture Radar (SAR) images of urban areas have become routinely available. In particular, in the spotlight acquisition mode, COSMO/SkyMed SARs are able to obtain a resolution even better than one meter. Accordingly, in principle a huge amount of information on objects present in the urban scenario can be extracted from such images; however, due to the involved interaction between incident electromagnetic wave and imaged scene, direct interpretation of VHR SAR images is not straightforward, and different methods to analyze them are being developed by the scientific community. In this paper, we explore the potentiality of using the power spectral density (PSD) of VHR SAR amplitude images of urban areas for information extraction. First, we propose a theoretical model of the PSD of such images, and then we test the validity of the developed model on COSMO/SkyMed spotlight SAR images of urban areas. Finally, some suggestions are provided on how the parameters of the obtained PSD can be exploited to extract useful information from VHR SAR amplitude images of urban areas.

Polar format algorithm based on fast Gaussian grid non‐uniform fast Fourier transform for spotlight synthetic aperture radar imaging

Conventional polar format algorithm (PFA) and its variations normally assume an ideal imaging geometry of a linear flight path, which cannot counteract the non-uniformity of samples existing in the circumstance of a highly non-linear aperture. This scenario may occur because of various factors such as rugged topography, atmospheric turbulence and intended manoeuvres. To address this challenge, this study develops a novel PFA with aperture accommodation for spotlight synthetic aperture radar (SAR) imaging. The proposed algorithm provides a new adaption of the fast Gaussian grid (FGG) non-uniform fast Fourier transform (NUFFT) scheme to two-dimensional (2D) SAR imaging of 3D scene, whose main idea is to convolve the non-uniform samples onto a uniform grid with a Gaussian kernel and then exploit the efficient 2D FFT for image reconstruction. In virtue of the 2D FGG NUFFT, a favourable tradeoff between reconstruction precision and computational efficiency is gained. Simulations illustrate the superiority of the proposed algorithm over the conventional non-uniform Sinc interpolation method. Also, the public real Gotcha dataset validates the effectiveness of the authors method.

Smear signature morphology of surface targets with arbitrary motion in spotlight synthetic aperture radar imagery

This study develops a methodology for analytically predicting the detailed smear signature morphology of surface targets with arbitrary motion in spotlight synthetic aperture radar (SAR) imagery. The radar sensor is assumed to move with constant speed and heading on a level flight path with broadside imaging geometry. Cases of uniform target motion exhibit morphology of simply curved smear shapes, as has been reported previously. However, the present analysis shows that non-uniform target motion can cause complicated smear shapes in spotlight SAR imagery. Specifically, the method of stationary phase is applied to local subaperture SAR images to yield analytic non-parametric expressions for the morphology of smear signatures within spotlight SAR imagery for surface targets with arbitrary motion trajectories. This predictive capability offers the potential of extracting some characteristics of true target motion based upon the induced SAR smear signatures alone.

A Parameter-Adjusting Polar Format Algorithm for Extremely High Squint SAR Imaging

The polar format algorithm (PFA) is a wavenumber domain imaging method for spotlight synthetic aperture radar (SAR). The classic fixed-parameter PFA employs interpolation technique for data correction. However, such an operation will induce heavy computational load and cause degradation in computation precision. To optimize image formation processing performance, this study presents a novel parameter-adjusting PFA, which can implement SAR image formation at an extremely highly squint angle with obviously improved computation efficiency and imaging precision. In the parameter-adjusting PFA, radar parameters, such as center frequency, chirp rate, pulse duration, sampling rate, and pulse repeat frequency (PRF), vary for each azimuth sampling position. Due to the parameter adjusting strategy, the echoed signal can be acquired directly in keystone format with uniformly distributed azimuth intervals. In this case, range interpolation, which is necessary in the fixed-parameter PFA to convert data from polar format to keystone format, can be eliminated. Chirp z-transform (CZT) can be employed to focus SAR data along the azimuth direction. Compared with truncated sinc-interpolation, CZT was found to perform better in inducing less phase and amplitude errors in data processing. When residual video phase (RVP) compensation was accomplished for dechirped signal, the processing steps of the parameter-adjusting PFA were simplified as azimuth CZTs and range inverse fast Fourier transforms (IFFT). Lastly, computer simulation of multiple point targets validated the presented approach.

Integrating Autofocus Techniques With Fast Factorized Back-Projection for High-Resolution Spotlight SAR Imaging

Back-projection (BP) is considered as an ideal methodology for the high-resolution synthetic aperture radar (SAR) imaging. However, applying conventional autofocus techniques to BP imagery requires a special consideration and is usually difficult to implement. In this letter, we present a scheme to compatibly blending a novel multiple aperture map drift (MAMD) algorithm with fast factorized back-projection (FFBP). Through an elaborate BP coordinate, we construct the Fourier transform relationship between FFBP sub-aperture (SA) images and the corresponding range-compressed phase history data. The phase error function is achieved by the MAMD within FFBP recursions, and well-focused imagery is obtained by phase correction on the range-compressed phase history data. The proposed scheme inherits the advantages of high precision and efficiency of the FFBP, and is suitable for high-resolution spotlight SAR imaging with raw data. Real data experiments guarantee the effectiveness of our proposed scheme.

Novel approach based on deramping technique for squinted sliding spotlight SAR imaging

This paper investigates a novel approach based on the deramping technique for squinted sliding spotlight Synthetic Aperture Radar (SAR) imaging to resolve the azimuth spectrum aliasing problem. First of all, the properties of the azimuth spectrum and the squint angle impacts on the azimuth spectrum aliasing problem are analyzed. Based on the analysis result, an operation of filtering is added to the azimuth preprocessing step of traditional Two-Step Focusing Approach (TSPA) to resolve the azimuth folding problem and remove the influence of the squint angle on the azimuth spectrum aliasing problem. Then, a modified Range Migration Algorithm (RMA) is performed to obtain the precise focused image. Furthermore, the focused SAR image folding problem of traditional TSPA is illuminated in this paper. An azimuth post-processing step is proposed to unfold the aliased SAR image. Simulation experiment results prove that the proposed approach can solve the spectrum aliasing problem and process squinted sliding spotlight data efficiently.

Compressive radar with off-grid targets: a perturbation approach

Compressed sensing (CS) schemes are proposed for monostatic as well as synthetic aperture radar (SAR) imaging with chirped signals and ultra-narrowband (UNB) continuous waveforms. In particular, a simple, perturbation method is developed to reduce the gridding error for off-grid targets. A coherence bound is obtained for the resulting measurement matrix. A greedy pursuit algorithm, support-constrained orthogonal matching pursuit, is proposed to take advantage of the support constraint in the perturbation formulation and proved to have the capacity of determining the off-grid targets to the grid accuracy under favorable conditions. Alternatively, the locally optimized thresholding is proposed to enhance the performance of the CS method, basis pursuit. For the advantages of higher signal-to-noise ratio and signal-to-interference ratio, it is proposed that Spotlight SAR imaging will be implemented with CS techniques and multi-frequency UNB waveforms. Numerical simulations show promising results of the proposed approach and algorithms.

A NEW CONICAL-TRAJECTORY POLAR FORMAT ALGORITHM FOR SPOTLIGHT BISTATIC SAR

The Polar Format Algorithm (PFA) is suitable for spotlight synthetic aperture radar (SAR) image focusing either in monostatic or bistatic cases. The classic linear-trajectory PFA complete data correction in wavenumber domain, converting data from the polar format to the rectangular format. However, the two- dimension processing (either using interpolation or chirp-z transform) introduces heavy computational load, which limits its real-time applications. This study presents a conical-trajectory PFA for bistatic SAR, in which the transmitter and receiver are designed to ∞y on conical surfaces, to simplify image formation procedures via eliminating the necessity of range processing. Moreover, the conical- trajectory PFA provides a space-invariant range resolution to simplify the SAR image comprehension. A spotlight forward-looking bistatic missile guidance application was simulated for the algorithm validation and performance analysis.