Stripmap Synthetic Aperture Radar Images Research Articles

Improved phase curvature autofocus for stripmap synthetic aperture radar imaging

Based on the theory of phase curvature autofocus (PCA) on stripmap synthetic aperture radar (SAR), an improved algorithm for increasing the accuracy of phase error compensation is presented in this study. PCA method was proposed to extend the phase gradient autofocus method for SAR systems in stripmap mode. The main problems concerned with the traditional PCA algorithm are related to selecting candidates in the image for phase error estimation, windowing, estimation procedure, and range shift due to the phase error. In this study, the modification of traditional PCA algorithm has been performed in different steps including the following: improving range-compressed data, prominent points extraction, adaptive windowing, weighted maximum likelihood for phase error estimation, improving phase error result, range shift compensation, and determining the condition to end the iterations. Real data experiments demonstrate the success of the proposed autofocus method, which is applied to the stretched-based pulsed mode SAR data set in the absence of highly accurate inertial navigation units.

Segmentation of Marine SAR Images by Sublook Analysis and Application to Sea Traffic Monitoring

This paper presents a segmentation algorithm for marine synthetic aperture radar (SAR) images. The proposed approach is based on the analysis of image sublooks along azimuth direction and exploits a novel indicator, called incoherent entropy, to divide the input targets into three classes, namely, ship, sea, and ambiguity. A global threshold detector is then implemented to discriminate between stable targets (ships), providing low incoherent entropy amplitude, and ambiguity or sea, implying very high and high values of the indicator, respectively. An integration of the segmentation algorithm into maritime surveillance systems is investigated, proposing its use as a discrimination tool to limit the false alarm rate of traditional prescreening algorithms. The main steps of a standard SAR-based ship detection system are thus implemented to provide a first screening of the candidate targets, which are, then, processed by sublook analysis using incoherent entropy to identify false detections. The proposed technique is tested on stripmap SAR images collected by the TerraSAR-X mission, over the Gulf of Naples, Italy. Algorithm detections are validated using ground-truth data, provided by automatic identification system. The results confirm the capability of the proposed discrimination approach to reject the vast majority of the false detections resulting from the prescreening algorithm.

On the analysis of a time series of X–band TerraSAR–X SAR imagery over oil seepages

ABSTRACTA large time series of 42 dual–polarimetric co–polarized TerraSAR-X (TSX) StripMap Synthetic Aperture Radar (SAR) measurements are exploited to monitor a well-known oil seep area, i.e., the Taylor Energy site in the Gulf of Mexico. A comprehensive scattering analysis is undertaken to assess the impact of SAR imaging parameters (polarization, angle of incidence – AOI, noise floor) and environmental conditions (wind speed – WS, oil properties) on single-polarization SAR–based sea oil seep observation. The main goal of this study is to evaluate the reliability of the scattering–based information derived from the time series of TSX SAR imagery. A two-scale backscattering model is considered to give a physical framework that supports a better understanding of the effects of the above–mentioned factors.Experimental results showed that the high TSX noise floor significantly limits a reliable interpretation of the slick–free sea surface and oil seep backscattering at AOIs larger than 34 and 26, respectively, since they are contaminated by noise. Hence, it is shown that, at larger AOIs, the joint contribution of noisy SAR measurements and low oil backscattering does not result in a larger oil/sea separability. The latter is not remarkably influenced by polarization and WS, under low–to–moderate conditions. Experiments also demonstrate that, when reliable SAR measurements are available, sea oil seep backscattering is affected by the oil’s damping properties more than its concentration in the water column. The time variability of the polluted area is also estimated using the time series of TSX imagery and the obtained results agree with independent analysis undertaken on the same test site.

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.

Accurate Reconstruction and Suppression for Azimuth Ambiguities in Spaceborne Stripmap SAR Images

In this letter, an accurate mathematical model for azimuth ambiguity in stripmap synthetic aperture radar (SAR) images is first constructed, with an azimuth ambiguity factor (AAF) defined as the residual amplitude and phase terms of ambiguities. Next, a novel framework for reconstructing and suppressing azimuth ambiguity is proposed based on the analysis of the AAF. In this framework, azimuth ambiguities are accurately reconstructed by applying reconstruction filters in the range Doppler and 2-D frequency domain, and then, the reconstructed signal is used for suppressing azimuth ambiguities. Moreover, the proposed framework does not depend on the statistical characteristics of a SAR image and is capable of reducing the space-variant ambiguities. As verified by both simulated data and real TerraSAR-X data, the proposed method is capable of suppressing azimuth ambiguities in SAR images.

Quantitative Assessment of CFRP-concrete Cylinders Using Synthetic Aperture Radar Images

ABSTRACTA feature extraction algorithm is proposed to quantitatively assess the condition of intact and damaged carbon fiber reinforced polymer (CFRP)-wrapped concrete cylinders using synthetic aperture radar (SAR) images. The proposed algorithm converts SAR images into a simplified representation, based on the shape, size, and amplitude of SAR images. In this approach, the shape of scatterers in a SAR image is characterized by average Gaussian curvature (K), area ratio (R), and SAR amplitude (I), and is represented by a K-R-I curve. SAR images of intact and damaged CFRP-wrapped concrete cylinders were generated by a stripmap SAR imaging radar system (10.5 GHz) at various inspection angles (0°, 15°, 25°, 30°, 45°, and 60°). From our experimental result, it is found that the K-R-I representation of SAR images is capable of distinguishing damaged SAR images from intact ones at different inspection angles. Quantitative dissimilarity between the K-R-I curves of intact and damaged specimens is assessed by coefficient of correlation and compared with the signal-to-noise ratio (SNR) of SAR images. It is found that the dissimilarity of K-R-I curves is closely related to the SNR of SAR images, demonstrating the feasibility and potential of the proposed K-R-I representation.

Practical implementation of stripmap Doppler imaging

Doppler imaging is a technique that can generate fine two-dimensional (2D) imagery in the absence of large bandwidths. Radar imaging has traditionally consisted of combining wide bandwidth waveforms with aperture synthesis. Wide bandwidth waveforms provide high resolution in down-range (line-of-sight), whereas aperture synthesis enables high resolution in the orthogonal direction. However, in today’s increasingly congested spectral environment, using wide bandwidths waveforms is becoming less and less attractive. Consequently, imaging techniques that require only narrow bandwidth waveforms offer very attractive and practical advantages. An approach, examined here, is to use phase in conjunction with aperture synthesis to achieve high resolution in down-range while using narrowband waveforms. This method has the added benefit of using the same collection geometry as traditional stripmap synthetic aperture radar imaging. Therefore Doppler imaging is compatible with use in spectrally congested environments where wide bandwidth waveforms might be prohibited. In this study, the basic Doppler imaging concept is explained, a simple framework for its operation is introduced and resolution limits are examined. Results are presented from both simulations and full-scale experiments, which demonstrate range resolutions as fine as 23 cm using an 8.9 GHz CW waveform and 2 m long synthetic aperture.

GPU Processing for UAS-Based LFM-CW Stripmap SAR

Unmanned air systems (UAS) provide an excellent platform for synthetic aperture radar (SAR), enabling surveillance and research over areas too difficult, dangerous, or costly to reach using manned aircraft. However, the nimble nature of the small UAS makes them more susceptible to external forces, thus requiring significant motion compensation in order for SAR images to focus properly. SAR backprojection has been found to improve the focusing of low-altitude stripmap SAR images compared to frequency domain algorithms. In this paper the authors describe the development and implementation of SAR backprojection appropriate for UAS based stripmap SAR that utilizes the unique architecture of a graphics processing unit (GPU) in order to produce high-quality imagery in real-time.

Filtering of Azimuth Ambiguity in Stripmap Synthetic Aperture Radar Images

Due to the specific characteristics of the SAR system, peculiar artifacts can appear on SAR images. In particular, finite pulse repetition frequency (PRF) and nonideal antenna pattern give rise to azimuth ambiguity, with the possible presence of “ghosts” on the image. They are due to the replica of strong targets located outside of the antenna main beam, superposed onto low intensity areas of the imaged scene. In this paper, we propose a method for the filtering of azimuth ambiguities on stripmap SAR images, that we name “asymmetric mapping and selective filtering” (AM&SF) method. Our framework is based on the theory of selective filtering and on a two-step procedure. In the first step, two asymmetric filters are used to suppress ambiguities due to each sidelobe of the antenna pattern, and the ratios between the original and filtered images are used to produce two maps of the ambiguity-affected areas (one for each sidelobe). In the second step, these maps are used to produce a final image in which only the areas affected by the ambiguities are replaced by their filtered (via the proper of the two filters) versions. The proposed method can be employed in situations in which similar approaches fail, and it has a smaller computational burden. The framework is positively tested on TerraSAR-X and COSMO/SkyMed SAR images of different marine scenes.

Mitigation of Azimuth Ambiguities in Spaceborne Stripmap SAR Images Using Selective Restoration

A novel framework is proposed for mitigating azimuth ambiguities in spaceborne stripmap synthetic aperture radar (SAR) images. The azimuth ambiguities in SAR images are localized by using a local mean SAR image, SAR system parameters, and a defined metric derived from azimuth antenna pattern. The defined metric helps isolate targets lying at locations of ambiguities. The mechanism for restoration of ambiguity regions is selected on the basis of size of ambiguity regions. A compressive imaging technique is employed to restore isolated ambiguity regions (smaller regions of interconnected pixels), whereas clustered regions (relatively bigger regions of interconnected pixels) are filled by using exemplar-based inpainting. The simulation results on a real TerraSAR-X data set demonstrated that the proposed scheme can effectively remove azimuth ambiguities and enhance SAR image quality.

Suppressing Moving Target Artifacts in Multi-Channel Stripmap SAR Images by Space–Doppler Filtering

Synthetic aperture radar (SAR) as a method for ground imaging by using a single antenna or a sensor array has widely found attraction for remote sensing applications and reconnaissance tasks. Independent of the particular sensor but inherent to the SAR processing, moving objects in the observed scene are imaged at incorrect positions and can appear in a smeared fashion. For countering these disturbing artifacts a joint spatial-spectral processing is proposed and analyzed in this paper that allows to suppress echoes from moving targets in multi-channel stripmap SAR data while preserving the echoes of the fixed scene. Results obtained with experimental data from an airborne system show the potential and limitations for a practical application of the presented method.

A New Improved Step Transform Algorithm for Highly Squint SAR Imaging

In this letter, a new improved step transform (IST) algorithm is developed for highly squint stripmap synthetic aperture radar (SAR) imaging. Different from the previous step transform algorithms, such as the time-varying step transform algorithm, the new algorithm compensates the cubic phase term and the phase term caused by the varying chirp rate using estimation of the target position focused in the coarse-resolution fast Fourier transform, and these undesirable phase terms can be compensated more appropriately. The algorithm can process SAR imaging under a squint angle of up to 75° in X-band. Simulation results show that the IST algorithm is effective.

Ultrawideband (UWB) Radar Imaging of Building Interior: Measurements and Predictions

In this paper, we explore using the ultrawideband radar technology for sensing through-the-wall imaging. We conducted a field experiment with our in-house designed impulse-based radar, in which a stripmap synthetic aperture radar (SAR) geometry was employed in mapping an abandoned army barrack building with a large footprint area. The images obtained from two sides of the building were combined in order to obtain the full building layout, including the interior structure. Computer simulations performed with Xpatch, a physical optics-based ray tracing code, are used to explain some phenomena observed in the measured SAR images.