Imaging for High-Resolution Wide-Swath Spaceborne SAR Using Cubic Filtering and NUFFT Based on Circular Orbit Approximation

ABSTRACTRecently, the performance of high-resolution spaceborne synthetic aperture radar (SAR) data for urban landscape monitoring has attracted increased interest, in particular for regions where rainy weather prevails throughout of year. In this study, the phase component of SAR data was exploited for landscape monitoring in the western area of Nanjing city, China. Twenty-six scenes of TerraSAR-X single-look complex (SLC) interferometric images were acquired for the period of May 2013 to February 2015 and applied for urban change detection as well as surface subsidence monitoring by means of interferometric SAR (InSAR) technologies. Firstly, a small baseline strategy in conjunction with a fast statistically homogeneous pixel selection (FaSHPS) approach were applied for the coherence imagery generation and for the coherent change detection, resulting in a correct probability of better than 90%. Second, the surface deformation was derived with millimetre accuracy using an enhanced multi-temporal InSAR (MT-InSAR) tool by synergistically analyzing the amplitudes and phases of the SAR acquisitions. This study indicates that high-resolution SAR data have the potential for urban landscape monitoring by taking advantage of the interferometric performance and the all-day and all-weather imaging capability.

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.

Introduction. Range Cell Migration (RCM) is a source of image blurring in synthetic aperture radars (SAR). There are two groups of signal processing algorithms used to compensate for migration effects. The first group includes algorithms that recalculate the SAR signal from the "along–track range – slant range" coordinate system into the "along-track range – cross-track range" coordinates using the method of interpolation. The disadvantage of these algorithms is their considerable computational cost. Algorithms of the second group do not rely on interpolation thus being more attractive in terms of practical application.Aim. To synthesize a simple algorithm for compensating for RCM without using interpolation.Materials and methods. The synthesis was performed using a simplified version of the Chirp Scaling algorithm.Results. A simple algorithm, which presents a modification of the Keystone Transform algorithm, was synthesized. The synthesized algorithm based on Fast Fourier Transforms and the Hadamard matrix products does not require interpolation.Conclusion. A verification of the algorithm quality via mathematical simulation confirmed its high efficiency. Implementation of the algorithm permits the number of computational operations to be reduced. The final radar image produced using the proposed algorithm is built in the true Cartesian coordinates. The algorithm can be applied for SAR imaging of moving targets. The conducted analysis showed that the algorithm yields the image of a moving target provided that the coherent processing interval is sufficiently large. The image lies along a line, which angle of inclination is proportional to the projection of the target relative velocity on the line-of-sight. Estimation of the image parameters permits the target movement parameters to be determined.

A nonlinear chirp scaling algorithm (NCSA) is proposed for bistatic SAR data processing with high squint angles in tandem configuration. Besides the dependence of the azimuth frequency, the dependence of range is considered for the Doppler chirp rate of tandem bistatic SAR. The proposed algorithm can compensate the range dependence of both the range cell migration (RCM) and the second range compression (SRC) terms well by appropriately setting the coefficients of the phase term, which is obtained after the nonlinear chirp scaling process in the two-dimensional wavenumber domain. Only fast Fourier transforms (FFTs) and phase multiplies are required, and fast imaging is implemented in the frequency domain. Satisfying focusing qualities verify the effectiveness of the proposed algorithm by simulations.

Synthetic aperture radar imaging at high resolution and highly squint angle is confronted with several difficulties, such as the spatial variance of range cell migration (RCM) and the azimuth-dependent property of high-order terms. In order to address the above-mentioned problems, an improved non-linear chirp scaling algorithm based on keystone transform (KT) and linear range walk correction (LRWC) is proposed. First, KT is applied to correct the second-order RCM in range frequency and azimuth time domain. Then the spatial variance of linear RCM (LRCM) is analysed, and range–azimuth coupling is alleviated through LRWC, in this way, azimuth-variant RCM can be removed by phase multiplication, which avoids the approximate error of RCMC in two-dimensional frequency domain. Taking both the spatial variance of LRCM and the difference of the minimum bistatic slant range caused by LRWC into consideration, high-precision approximation of azimuth-dependent coefficients for azimuth signal are deduced, based on which the Doppler centroid, azimuth FM rate and cubic phase can be equalised by selecting proper perturbation coefficients. The proposed algorithm leads to a large depth of focusing in both range direction and azimuth direction. Simulation results prove the effectiveness of the proposed method.

Synthetic aperture radar on geosynchronous orbit (GEOSAR) can realize the continuous image on the larger coverage area in the short revisit period of nearly 24h. The four-order slant range model based on the “stop-and-go” supposition for the curve track has been proposed in the some literatures. Owing to the high attitude and the wide swath of GEOSAR, effect of the signal propagated delay and range displacement of point target on the slant range model can lead to the defocused imaging results. Hence, in this paper, we firstly infer the advance slant range model using Taylor expansion considering to the path delay and the position of point target. Then, we deduce the point target two dimensional frequency spectrum and the improved CS imaging method based the above range model. Finally, the correctness of the CS imaging method based on the improved slant range model is verified by the simulation.

In this paper, considering the relative motion between satellite and earth during signal propagation time, the accurate analysis method for propagation slant range is presented in geosynchronous SAR. Furthermore, the difference between accurate analysis method and `Stop-and-Go' assumption is analytically obtained. Meanwhile based on the derived accurate slant range model, it is found that the corresponding range migration correction and azimuth reference function must consider the high order term, and therefore the modified SPECAN algorithm is proposed. The simulation results verify the correctness of `Stop-and-Go' assumption error derivation and SPECAN algorithm modification.

In view of the azimuth resolution of the helicopter-borne rotating array synthetic aperture radar (RoASAR) depending on the azimuth reconstruction angle and the sector distortion caused by the azimuth Deramp processing, this paper proposes an efficient helicopter-borne RoASAR high-resolution imaging algorithm based on two-dimensional (2-D) chirp-z transform (CZT). First, the high-order Taylor series expansion is performed on the slant range, and the accurate 2-D spectral expression of the point target is obtained by using the method of series reversion (MSR). Based on that, the space-variant characteristics of the range cell migration (RCM) terms are analyzed. After that, the space-variant RCM and the sector distortion effect caused by the azimuth Deramp processing are removed by using efficient 2-D CZT, thereby increasing the azimuth reconstruction angle and improving the azimuth resolution. The proposed algorithm is efficient without the interpolation operation, and it is easy to implement in real-time. Finally, the simulations are provided to verify the effectiveness of the proposed algorithm.

Spaceborne Synthetic Aperture Radar (SAR) can be applied for monitoring tropical cyclones (TCs), but co-polarized C-band SAR suffers from signal saturation such that it is improper for high wind-speed conditions. In contrast, cross-polarized SAR data does not suffer from this issue, but the retrieval algorithm needs more deliberation. Previously, many geophysical model functions (GMFs) have been developed using cross-polarized data, which obtain wind speeds using the complex relationships described by radar backscatter, incidence angle, wind direction, and radar look direction. In this regard, the rapid development of artificial intelligence technology has provided versatile machine learning methods for such a nonlinear inversion problem. In this study, we comprehensively compare the wind-speed retrieval performance of several models including Back Propagation Neural Network (BPNN), Support Vector Machine (SVM), Random Forest (RF), and Deep Neural Network (DNN), which were developed based on spatio-temporal matching and correlation analysis of stepped frequency microwave radiometer (SFMR) and dual-polarized Sentinel-1 SAR data after noise removal. A data set with ~2800 samples is generated during TCs for training and validating the inversion model. The generalization ability of different models is tested by the reserved independent data. When using similar parameters with GMFs, RF inversion has the highest accuracy with a Root Mean Square Error (RMSE) of 3.40 m/s and correlation coefficient of 0.94. Furthermore, considering that the sea surface temperature is a crucial factor for generating TCs and influencing ocean backscattering, its effects on the proposed RF model are also explored, the results of which show improved wind-speed retrieval performances.

A space-variant chirp scaling algorithm based on the range cell migration (RCM) equalization and azimuth subband synthesis has been studied to process simulated geosynchronous synthetic aperture radar (GEO-SAR) data. The acceptable order of terms in polynomials for the slant range models in the RCM correction and phase error compensation, division of subband, and suppression of grating lobes of the subbands was investigated. Qualitatively and quantitatively, the method was able to focus simulated GEO-SAR signals well. Finally, the constraint on the spatial extent of azimuth and range dimensions using the algorithm was assessed.

Squint multi-receiver synthetic aperture sonar (SAS) data is more challenging to process than data about its common side-looking counterpart because the geometry is complicated. While traditional multi-receiver algorithms mainly handle general side-looking cases, they do not work well for squint cases. Up to now, no multi-receiver algorithm for handling squint multi- receiver SAS data has been reported. This paper focuses on an imaging algorithm for the squint multi-receiver SAS. Firstly, the “non-stop-go-stop” signal model is established for squint multi- receiver SAS. Then a squint multi-receiver nonlinear chirp scaling algorithm (SMANLCSA) is proposed that is suited to process multi-receiver SAS data with small squint angle and SMANLCSA involves three key steps. The first step is to turn squint multi-receiver data into squint single-receiver data. The second step is a Doppler centroid frequency shift. The third step is range cell migration correction using nonlinear chirp scaling. Simulations have shown that SMANLCSA can handle squint multi-receiver data more accurately and effectively than the previous algorithm..

Forward-looking imaging has extensive potential applications, such as self-navigation and self-landing. By choosing proper geometry, bistatic synthetic aperture radar (BiSAR) can break through the limitations of monostatic SAR on forward-looking imaging and provide possibility of the forward- looking imaging. In this special bistatic conflguration, two problems involving large range cell migration (RCM) and large range-azimuth coupling are introduced by the forward-looking beam, which make it di-cult to use traditional data focusing algorithms. To address these problems, a novel Omega-K algorithm based on two-dimensional non-uniform FFT (2-D NUFFT) for translational variant (TV) bistatic forward-looking SAR (BFSAR) imaging is proposed in this paper. In this study, we derive an accurate spectrum expression based on two-dimensional principle of stationary phase (2-D POSP). 2-D NUFFT is utilized to eliminate the range-variant term, which can make full use of the data and improve the computational e-ciency as well. The experimental results, presented herein, demonstrate the efiectiveness and advantages of the proposed algorithm.

Geosynchronous (GEO) SAR is a radar satellite running in the inclinational geosynchronous orbit (36000km). During the long signal propagation delay time, the relative motion between satellite and target cannot be ignored. In this paper, the two-way slant range is analytically obtained from vector derivation. Meanwhile, it is found that the image formation must consider the non-uniform velocity in a long synthetic aperture time, and therefore, based on the derived slant range and the instantaneous velocity of satellite, a modified back projection algorithm is put forward to overcome the error of the “stop-and-go” error as well as the effects of the non-uniform satellite velocity. Simulation results validate the correctness of the improved imaging algorithm.

The traditional 2-D multiplication modulation jamming (2D-MMJ) method is widely used in synthetic aperture radar (SAR) deception jamming due to its simple hardware implementation and convenient template preparation. However, it suffers from serious defocusing in high-resolution spaceborne SAR deception jamming. To improve the fidelity of deception jamming, this letter proposes an improved 2D-MMJ method based on defocus correction (2D-MMJDC). First, the defocus correction phase is designed by analyzing the range cell migration (RCM) curves between the real and jamming signals. Next, considering the false point-target azimuth deviation caused by the defocus correction, the azimuth deviation correction phase is designed. Finally, two phases are added to the 2D-MMJ method, and a template preparation process based on the 2-D fast Fourier transform (2D-FFT) is designed. Simulation results show that the 2D-MMJDC method effectively solves the problem of defocusing on the 2D-MMJ method and greatly improves the fidelity of the deception jamming.

An important standard to measure the effectiveness of radar acquisition systems is the accuracy of target parameter estimation. To solve the estimation problem, the echo model of moving targets is established and the FRactional Fourier Transform (FRFT) is subsequently used to estimate the acceleration; further, data fusion is used to raise estimation accuracy. Finally, Range Cell Migration (RCM) and Doppler ambiguity are solved by using the Keystone transform and the ambiguity channels based on the estimated acceleration. The simulation results show high accuracy, complexity, and noise robustness.