Efficient imaging algorithm for spaceborne synthetic aperture radar/ground moving target indication systems

This paper proposes a new ground moving target imaging algorithm for high-resolution airborne circular stripmap synthetic aperture radar (CSSAR)-ground moving target indication (GMTI) systems. In the proposed algorithm, the range cell migration correction is performed in the 2D frequency domain via a phase multiplication. The azimuth compression is performed in the range Doppler domain. A key step of the proposed algorithm is to utilize an iterative strategy to achieve an accurate correction of the range cell migration. This step makes the proposed algorithm work well for high-resolution CSSAR-GMTI systems. Numerical simulations are conducted to validate the proposed algorithm.

An effective focusing approach for azimuth invariant bistatic SAR processing

With appropriate geometry configurations, bistatic Synthetic Aperture Radar (SAR) can break through the limitations of monostatic SAR for forward-looking imaging. Thanks to such a capability, bistatic forward-looking SAR (BFSAR) has extensive potential applications. This paper develops a frequency-domain imaging algorithm for translational invariant BFSAR. The algorithm uses the method of Lengendre polynomials expansion to compute the two dimensional point target reference spectrum, and this spectrum is used to perform the range cell migration correction (RCMC), secondary range compression and azimuth compression. In particular, the Doppler-centroid and bistatic-range dependent interpolation for residual RCMC is presented in detail. In addition, a method that combines the ambiguity and resolution theories to determine the forward-looking imaging swath is also presented in this paper.

This paper presents a study on signal modeling for airborne multichannel circular stripmap synthetic aperture radar (CSSAR)-ground moving target indication (GMTI) systems with relatively high resolution. High resolution is an important trend of synthetic aperture radar (SAR), which means higher accuracy requirement of range history and longer synthetic aperture time. It's known that targets are probably experience accelerations as the synthetic aperture time increases. Therefore, compared with the systems of lower resolution, the target signal modeling of high-resolution systems becomes more challenging. Besides, the coupling relationship among a target's motion and position parameters becomes more complicated due to the existence of accelerations. In this paper, a fourth-order range history model of a moving target is developed. Moreover, the target signal model is established, and the along-track interferometric (ATI) phase history is derived to reveal the coupling relationship among a target's motion and position parameters.

Spaceborne Synthetic Aperture Radar (SAR) instruments are effective tools for monitoring and mapping wetlands. With the availability of SAR instruments providing various polarization options, the scope of this study is to evaluate the new compact polarization for wetland multitemporal change detection using simulated RADARSAT Constellation Mission (RCM) SAR data. A series of fully polarimetric (FP) SAR images were collected over a test site located in Ontario, Canada, and used to simulate RCM compact polarimetric (CP) data. The simulated data were evaluated for multitemporal change detection and the results were compared to those from FP SAR data. WorldView imagery and water level data were used for analysis and validation of the change detection results. The study shows potential for using the CP SAR for multitemporal change detection over three major wetland classes: shallow water, marsh, and swamp. Although FP SAR was slightly more effective in multitemporal change detection compared to CP SAR, the percentage of agreement between the change detection results of FP and CP SAR was always greater than 90% for all wetland classes. The highest overall percentage of agreement (98.4%) between the results of FP and CP SAR was observed over the shallow water, while the lowest (92.5%) was observed over swamp.

The curved trajectory can lead to severely 2-D spatial-variance in spaceborne synthetic aperture radar (SAR). The azimuth-variance makes the traditional frequency domain imaging algorithms for the straight trajectory based on the assumption of azimuth translational invariance invalid. To correct the severely 2-D spatial-variance in curved trajectory spaceborne SAR, this paper studies a frequency imaging algorithm based on an optimal linear range walk correction (LRWC) preprocessing and 2-D singular value decomposition (SVD). Before the correction of the 2-D spatial-variance, an optimal LRWC preprocessing is introduced to minimize the azimuth-variance. Subsequently, a range block-SVD is proposed to correct the range-variance and, thus, achieves the accurate range cell migration correction. Finally, the azimuth tandem-SVD method is used to correct the azimuth-variance and, thus, accomplishes the azimuth compression for the whole azimuth scene. Processing of the simulated data validates the effectiveness of the proposed algorithm.

The F-SCAN principle is a better alternative to the scan-on-receive technique (SCORE) based on digital beamforming (DBF), which can avoid low gain caused by a conventional broad beam in the case of a wide swath. In F-SCAN SAR, a pencil beam scans the entire target area from far to near, providing high energy independent of the position and ensuring a low range ambiguity-to-signal ratio (RASR). Moreover, echo compression can be achieved via appropriate system parameter configuration, significantly shortening the receive window and reducing the amount of data. A wider range swath can, therefore, be achieved. However, for this novel F-SCAN SAR working mode, signal modeling and imaging processing are key issues that needed to be addressed. In this paper, the far-field synthetic antenna pattern of the space–time coding array (STCA) is first derived and analyzed, based on which the signal modeling of the F-SCAN SAR is carried out. Then, according to the signal model and echo characteristics, a novel imaging processing method based on the hybrid correlation algorithm is presented for the F-SCAN SAR. First, the dechirp operation is performed to compensate for the quadratic phase of the range time. The range compressed result is obtained after a range Fourier transform, where different range targets are successfully separated and range aliasing is avoided. Then, the modified azimuth reference function is correlated with the echo at each range cell to complete range cell migration correction (RCMC) and azimuth compensation. The received signal parameters and the Doppler parameters of each range cell are derived to update the azimuth reference function. Finally, accurate focused results are obtained in the range-frequency, azimuth-time domain. The simulation results indicate that the signal model based on the STCA can satisfy the requirements of the F-SCAN principle, and the proposed imaging algorithm can complete the precise focusing processing of the F-SCAN SAR echo.

The beam steering of high-squint terrain observation by progressive scans (TOPS) synthetic aperture radar (SAR) mounted on maneuvering platforms causes azimuth spectrum aliasing and nonlinear variation of the Doppler center with target azimuth position. A joint time-Doppler deramp (JTDD) based method is proposed and mainly contains two parts. First, for the azimuth spectrum aliasing, the unfolded 2-D spectrum is obtained by a modified linear deramp function in the azimuth time domain constructed from the 3-D motion parameters. After range cell migration correction (RCMC), the data supporting area in the azimuth time domain is expanded, and thus, aliased because of the nonlinear variation of Doppler center. Then, a nonlinear deramp operation in the Doppler domain is further proposed to obtain a nonaliasing signal. The proposed algorithm is efficient with less zero-padding due to the consideration of nonlinear components of Doppler center variation. Simulation and real SAR data processing are presented to validate the proposed algorithm.

FrFT-CSWSF: Estimating cross-range velocities of ground moving targets using multistatic synthetic aperture radar

This paper proposes the precise spaceborne synthetic aperture radar (SAR) image formation technique based on the analysis of critical error factors that severely degrade the SAR image quality. These are error factors related to the antenna beam pointing, the effective velocity, and the Doppler centroid. We newly developed the spaceborne SAR system simulator which is able to analysis effects that critical errors of the user-designed spaceborne SAR induce on a focused image. Using it, effects of critical errors are analyzed for spaceborne SAR image formation. Analysis results show that these cause phase distortion of rawdata, distort the symmetry of the azimuth impulse response function (IRF) of point targets in the focused image, and defocus the SAR image. To resolve these problems, we suggest to make use of the phase gradient algorithm (PGA) to compensate phase distortion induced by antenna beam pointing errors. Also, the effective velocity of the illuminated beam and the Doppler centroid of spaceborne SAR rawdata are exactly calculated by proposed methods using both orbit state vectors and the rawdata acquisition geometry based on the newly defined twoway slant range equation model. Furthermore, azimuth block processing is used to reduce signal level of ambiguities produced by sidelobes of antenna beam. The experimental results on the simulated SAR data show that proposed methods are able to reduce error effects as well as improve the focused SAR image quality greatly.

Spaceborne synthetic aperture radar (SAR) is a promising remote sensing technique, as it can produce high-resolution imagery over a wide area of surveillance with all-weather and all-day capabilities. However, the spaceborne SAR sensor may suffer from severe radio frequency interference (RFI) from some similar frequency band signals, resulting in image quality degradation, blind spot, and target loss. To remove these RFI features presented on spaceborne SAR images, we propose a multi-dimensional calibration and suppression network (MCSNet) to exploit the features learning of spaceborne SAR images and RFI. In the scheme, a joint model consisting of the spaceborne SAR image and RFI is established based on the relationship between SAR echo and the scattering matrix. Then, to suppress the RFI presented in images, the main structure of MCSNet is constructed by a multi-dimensional and multi-channel strategy, wherein the feature calibration module (FCM) is designed for global depth feature extraction. In addition, MCSNet performs planned mapping on the feature maps repeatedly under the supervision of the SAR interference image, compensating for the discrepancies caused during the RFI suppression. Finally, a detailed restoration module based on the residual network is conceived to maintain the scattering characteristics of the underlying scene in interfered SAR images. The simulation data and Sentinel-1 data experiments, including different landscapes and different forms of RFI, validate the effectiveness of the proposed method. Both the results demonstrate that MCSNet outperforms the state-of-the-art methods and can greatly suppress the RFI in spaceborne SAR.

In studying image formation methods of the spaceborne synthetic aperture radar (SAR), we utilize its modeling and simulation (M&S) to generate its realistic simulated rawdata. Especially, for the spaceborne spotlight SAR, we perform M&S that reflects its real characteristics, and get rawdata that are almost identical to one acquired by the real SAR sensor. Particularly, operations of the spaceborne spotlight SAR are simulated based on models of its dynamics and geometry related to timeline, orbital state vector, antenna beam pattern, azimuth beam steering, and etc. In addition, the target observation of it is modeled as evaluating observation angles related to point targets within the acquisition time. Finally, based on the received echo signal model, rawdata are simulated for point targets taking into account its real operation. For the high resolution SAR image formation, simulated rawdata are focused with the extended chirp scaling algorithm. Especially, its range cell migration (RCM) factor is the key one for the exact range cell migration correction. In order to do it accurately, the Doppler frequency and the effective velocity have to be calculated correctly for all range sample bins. For precise processing, we suggest the method to analyze them using orbital state vectors and scene coordinates based on two way slant range model. In experiments, system parameters and imaging scenarios to simulate rawdata acquisition of the spaceborne spotlight SAR system are defined. The processing results for realistic simulated rawdata of it are presented to evaluate the performance and the effectiveness of proposed methods. Its results show that suggested methods are applicable to form the high resolution spaceborne spotlight SAR image.

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.

To detect and estimate ground slowly moving targets in airborne single-channel synthetic aperture radar (SAR), a road-aided ground moving target indication (GMTI) algorithm is proposed in this paper. First, the road area is extracted from a focused SAR image based on radar vision. Second, after stationary clutter suppression in the range-Doppler domain, a moving target is detected and located in the image domain via the watershed method. The target’s position on the road as well as its radial velocity can be determined according to the target’s offset distance and traffic rules. Furthermore, the target’s azimuth velocity is estimated based on the road slope obtained via polynomial fitting. Compared with the traditional algorithms, the proposed method can effectively cope with slowly moving targets partly submerged in a stationary clutter spectrum. In addition, the proposed method can be easily extended to a multi-channel system to further improve the performance of clutter suppression and motion estimation. Finally, the results of numerical experiments are provided to demonstrate the effectiveness of the proposed algorithm.

Based on the analysis of range-azimuth coupling in two dimensional frequency domain, a modified RD algorithm is proposed to account for the problem of SAR imaging with high squint angle. The measures of decoupling consist of second range compression (SRC), third order coupling compensation and range cell migration correction (RCMC). In addition, the type of RCMC is modified to eliminate target's movement in range direction which will cause the blur of distance. Simulation results verify the proposed algorithm and perfectly focused image is obtained with a squint angle as large as 80 degree.