Bistatic Forward-looking Synthetic Aperture Radar Research Articles

A Bidirectional Resampling Imaging Algorithm for High Maneuvering Bistatic Forward-Looking SAR Based on Chebyshev Orthogonal Decomposition

A Bidirectional Resampling Imaging Algorithm for High Maneuvering Bistatic Forward-Looking SAR Based on Chebyshev Orthogonal Decomposition

A Modified NLCS Algorithm for High-Speed Bistatic Forward-Looking SAR Focusing with Spaceborne Illuminator

The coupling and spatial variation of range and azimuth parameters is the biggest challenge for bistatic forward-looking SAR (BFSAR) imaging. In contrast with the monostatic SAR and translational invariant bistatic SAR (TI-BSAR), the range cell migration (RCM), and Doppler parameters of high-speed bistatic forward-looking SAR (HS-BFSAR) have two-dimensional spatial variation characteristics, which makes it difficult to obtain SAR images with satisfactory global focusing. Firstly, based on the configuration of the spaceborne illuminator and high-speed forward-looking receiving platform, the accurate range-Doppler domain expression of the echo signal is derived in this paper. Secondly, using this analytical expression, a range nonlinear chirp scaling (NLCS) is proposed to equalize the RCM and equivalent range frequency modulation (FM) rate so that they can be uniformly processed in the two-dimensional frequency domain. Next, in the azimuth processing, the proposed method decomposes the Doppler contribution of the transmitter and receiver, respectively. Then, an azimuth NLCS is used to eliminate the spatial variation of the azimuth FM rate. Finally, a range-dependent azimuth filter is constructed to achieve azimuth compression. Simulation results validate the efficiency and effectiveness of the proposed algorithm.

Estimation of Doppler Parameters Based on PSO for BFSAR Ship Target Imaging

Bistatic forward-looking synthetic aperture radar (BFSAR) can create a highly focused image of a target in the flight direction of the receiver. However, most research on BFSAR imaging is aimed at stationary targets, with relatively few studies on ship targets. We propose DPEP, an estimate of Doppler parameters, based on particle swarm optimization (PSO) for ship target imaging in the BFSAR system. The relationship between the Doppler parameters and those of the motion of a ship target is derived from the geometry of the BFSAR system. PSO is adopted to accurately estimate the Doppler parameters, so as to construct the functions for compression. The proposed algorithm is validated and compared to traditional algorithms through simulations.

Bistatic Forward-Looking SAR Imaging of Uniformly Moving Target Based on Improved BP Algorithm

Bistatic Forward-Looking SAR Imaging of Uniformly Moving Target Based on Improved BP Algorithm

Analysis of Modeling and 2-D Resolution of Satellite–Missile Borne Bistatic Forward-Looking SAR

Analysis of Modeling and 2-D Resolution of Satellite–Missile Borne Bistatic Forward-Looking SAR

An Efficient Backprojection Algorithm Based on Wavenumber-Domain Spectral Splicing for Monostatic and Bistatic SAR Configurations

This paper introduces a fast backprojection synthetic aperture radar (SAR) imaging algorithm based on wavenumber-domain spectral splicing. The traditional fast backprojection (FBP) algorithm establishes the polar coordinate system with the center of the sub-aperture as the origin. Therefore, the coordinates of the image obtained from each sub-aperture are different. Sub-aperture images must be projected to a uniform coordinate system before they can be coherently superimposed to form the final image, which requires a large amount of calculation. In order to deal with this problem, this paper proposes a novel imaging method, which uses the same polar coordinate system for each sub-aperture. The sub-aperture images are then spliced in the wavenumber-domain, and directly added after upsampling. This method avoids the projection from each sub-aperture to the uniform coordinate system, thus improving the imaging accuracy and efficiency. At the same time, the algorithm is suitable for various configurations, and can achieve good imaging results for bistatic forward-looking SAR and high-speed mobile platform. Finally, simulations are presented to demonstrate the effectiveness of the algorithm.

Optimally Matched Space-Time Filtering Technique for BFSAR Nonstationary Clutter Suppression

Clutter suppression in synthetic aperture radar (SAR) is one of the urgent and attractive problems in ground moving target indication (GMTI) application. With separate transmitter and receiver, ground clutter is nonstationary in bistatic forward-looking SAR (BFSAR), which directly leads to the inaccurate clutter covariance matrix (CCM) estimation. As a consequence, the traditional space-time adaptive processing (STAP) will suffer from a serious performance deterioration. In this article, an optimally matched space-time filtering (MSTF) technique is proposed to suppress nonstationary clutter for BFSAR systems. The main idea of the proposed method is to directly design and generate a suppression filter in space-time domain, whose space-time frequency response is matched with clutter spectrum. To construct the matched space-time filter, clutter modeling with arbitrary BFSAR configuration is first proposed to acquire space-time information of clutter spectrum. And then, the suppression filter can be designed and the design process is transferred into a constrained optimization problem (COP), according to the obtained clutter space-time information. Finally, the particle swarm optimization (PSO) algorithm is applied to solve the COP and obtain the optimal solution, i.e., the desired matched space-time filter weight, for BFSAR nonstationary clutter suppression. Since the generation of the designed filter circumvents CCM estimation, the proposed method will not be affected by the nonstationary characteristic of BFSAR clutter. In October 2020, the first airborne BFSAR-GMTI experiment in the world has been successfully conducted by us, and the experimental results are given to validate the effectiveness of the proposed method.

Hybrid SAR-ISAR Image Formation via Joint FrFT-WVD Processing for BFSAR Ship Target High-Resolution Imaging

Bistatic forward-looking synthetic aperture radar (BFSAR) is a kind of bistatic SAR system that can image forward-looking terrain in the flight direction of the receiver. Current literature and reports about BFSAR mainly concentrate on the stationary scene and ground-moving target imaging. Unlike stationary and ground-moving targets, the translational and rotational movements of ship targets usually lead to complicated range cell migration (RCM) and Doppler frequency migration (DFM). Moreover, the characteristics of RCM and DFM for different scattering points of the ship target are significantly different, i.e., the characteristics of the RCM and DFM are 2-D spatial variation, ultimately leading to severe defocusing of ship target in the SAR image. To solve these problems, a kind of hybrid SAR-ISAR imaging formation is proposed for BFSAR ship target imaging. First, to solve the problem of the Doppler ambiguity caused by the forward-looking mode of the receiver, an efficient ambiguity estimation method based on the minimum entropy criterion is presented. Then, keystone transform and range alignment processing can be applied to correct the spatial variant range walk and higher order RCM, respectively. Moreover, in order to obtain a high-resolution and well-focused image after translational compensation, a new method based on the fractional Fourier transform (FrFT) and the Wigner–Ville distribution (WVD) is proposed, where FrFT is applied to separate the multiple main scattering points in each range cell, and WVD is applied to obtain the high-resolution time–frequency distribution of each scattering point. Compared with the conventional ISAR range-Doppler (RD) algorithm and time–frequency estimation-based imaging methods, this method not only has no cross terms but also has high processing accuracy and better antinoise performance.

A Novel CFFBP Algorithm With Noninterpolation Image Merging for Bistatic Forward-Looking SAR Focusing

Fast factorized back-projection (FFBP) has significant advantages for bistatic forward-looking synthetic aperture radar (BFSAR) imaging with arbitrary geometry and complex configuration. Conventional FFBP is generally based on the polar coordinate system (PCS) for recursive processing; however, it involves huge interpolations and causes computational inefficiency. In this article, a novel FFBP is developed for BFSAR focusing based on the Cartesian coordinate system (CCS), which is referred to as Cartesian fast factorized back-projection (CFFBP). In the new algorithm, a two-step spectrum correction is designed to avoid spectrum aliasing, and the Nyquist sampling requirement (NSR) for the BFSAR image spectrum can be decreased significantly. With low NSR in CCS, subimage merging can be implemented with noninterpolation processing, so that the proposed algorithm can achieve high performance in both accuracy and efficiency. Moreover, the practical problem of motion error is particularly considered in algorithm development, and well-adapted data-driven motion compensation (DDMC) is integrated with CFFBP based on which a new Cartesian fast time-domain (CFTD) processing framework is developed for BFSAR application. Promising results from both simulation and raw data experiments are provided and analyzed to validate the high performance of the proposed algorithm.

Focusing High-Maneuverability Bistatic Forward-Looking SAR Using Extended Azimuth Nonlinear Chirp Scaling Algorithm

In high-maneuverability bistatic forward-looking synthetic aperture radar (HMBF-SAR) imaging, the acceleration leads to an increased residual range curve and a deepened two-dimensional spatial variance of Doppler parameters, which cannot be processed by the traditional algorithms. To address these problems, this paper establishes a more accurate digital representation for HMBF-SAR model and investigates an extended azimuth nonlinear Chirp Scaling (EANLCS) imaging method. In the flowchart of this paper, we first propose a more precise slant range model with improved expansion coefficients, and defines the range and azimuth direction of HMBF-SAR imaging. Then, a novel fast reference point (i.e., azimuth and range reference point) selection method is proposed to analyze two-dimensional spatial variance of signal characteristics, which is used to construct a high order model of residual range cell migration and Doppler parameters. Based on above analysis, we put forward an advanced imaging algorithm of combining the Second-order keystone and extended azimuth nonlinear chirp scaling (EANLCS) to compensate the increased residual range curve and two-dimensional spatial variance of Doppler parameters. Finally, the effectiveness of the proposed HBMF-SAR method is verified by several numerical simulations and comparative studies based on both the simulated and raw data.

Focusing High Maneuvering Bistatic Forward-Looking SAR With Stationary Transmitter Using Extended Keystone Transform and Modified Frequency Nonlinear Chirp Scaling

This article presents an imaging solution for high maneuvering bistatic forward-looking SAR with stationary transmitter (STHM-BFSAR). In STHM-BFSAR configuration that the transmitter is mounted on a stationary platform in side-looking mode while the receiver does high-speed maneuvering in forward-looking mode, high speed and acceleration induced by high dynamic characteristics of receiver in both along-track and height direction cause larger range cell migration (RCM) and more severe 2-D spatial variation of Doppler characteristics, which makes it more difficult to obtain well-focused bistatic SAR image. Furthermore, different from the general airborne bistatic SAR, STHM-BFSAR has a larger azimuth cubic phase term that exceeds <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\pi /4$</tex-math></inline-formula> rad, which seriously affects the image quality. To deal with these problems, an imaging algorithm based on extended keystone transform (EKT) and modified frequency nonlinear chirp scaling (FNCS) is proposed in this article. EKT can correct spatial variant range curvature and bulk linear RCM, and the residual RCM is smaller than traditional keystone transform. The proposed modified FNCS is used to equalize the azimuth-range-dependent Doppler parameters in the frequency domain, which produces lower side-lobes and higher accuracy by compensating for the second-order spatial variation of the azimuth cubic coefficients. The final simulation results in this article verify the effectiveness of the proposed algorithm.

Focusing Translational-Variant Bistatic Forward- Looking SAR Data Using the Modified Omega-K Algorithm

Accurate 2-D frequency spectrum (2-D FS) with acceleration, two-way range coupling terms, and spatial-variant Doppler parameters are the main problems to be solved in translational-variant bistatic forward-looking synthetic aperture radar (SAR) (TV BFSAR) with curved trajectory. For these issues, a modified omega-K imaging algorithm is derived in this article. The maximum usage of 2-D FS based on the method of series reversion (MSR) is achieved by linear range cell migration correction, and 2-D FS is linearized in bistatic range by using high-order polynomial fitting. Then, a method of azimuth resampling is introduced to implement compensation of spatial-variant Doppler parameters. Different from other bistatic omega-K methods, our newly proposed method focuses on the small-aperture data in the azimuth frequency domain to avoid azimuth aliasing without padding zeros and uses the frequency focusing position to study the model of spatial-variant phase. Simulation results and real data verify the effectiveness of the proposed method.

Bistatic Forward-Looking SAR MP-DPCA Method for Space–Time Extension Clutter Suppression

Echoes of bistatic forward-looking synthetic aperture radar (BFSAR) disperse to multiple range cells and exist spatial frequency extension as well as Doppler spectrum extension (i.e., namely space–time extension). Furthermore, the characteristics of BFSAR clutter are strongly nonstationary and spatial variants. Because of the abovementioned issues, clutter and moving targets are fully overlapped in the initial 3-D space–time–range raw data domain, and the clutter cannot be suppressed effectively. To solve this problem, a BFSAR multipulse displaced phase center antenna (MP-DPCA) method is proposed in this article. First, keystone transform without Doppler ambiguity is applied to remove the coupling between the space–time and range domains. Hence, the overall complex 3-D processing in the space–time–range domain is reduced to independent 2-D processing in each space–time domain. Subsequently, a spatial-dechirp processing is applied in the space–time domain to eliminate the spatial frequency extension. Meanwhile, Doppler parameters of clutter point scatterers are equalized by nonlinear chirp scaling processing in the frequency and time domains. Accordingly, the Doppler spectrum extension of point scatterers can be eliminated by a uniform azimuth dechirp processing. After aforesaid three steps, the clutter and moving targets are separated in the space–time domain. Finally, based on the linear phase difference of clutter between the channels, a multipulse canceller can be designed to suppress the clutter. Compared with the existing space–time adaptive procession (STAP) and DPCA methods, this method not only overcomes the nonstationary problem in BFSAR but also conquers the strict application conditions of DPCA. Simulation results are given to verify the effectiveness of the proposed method.

An Improved Frequency-Domain Image Formation Algorithm for Mini-UAV-Based Forward-Looking Spotlight BiSAR Systems

Mini-unmanned aerial vehicle (UAV)-based bistatic forward-looking synthetic aperture radar (SAR) (mini-UAV-based BFSAR) is much more attractive than the monostatic one because of the flexibility of the system geometry selection as well as its simplicity of system operation, especially with the mini-UAV platform. However, the trajectory of the mini-UAV needs to be accurately modeled since it is very sensitive to the external environment, and the forward-looking configuration results in more severe spatial variance in image formation processing. In the paper, an improved frequency-domain imaging algorithm based on a very accurate slant range model is proposed for mini-UAV-based BFSAR with spotlight illumination. First, a more accurate slant range expression considering the motion characteristics of the UAV and bistatic spotlight configuration is re-derived. Second, a new range nonlinear chirp scaling (NLCS) operator was derived based on the accurate bistatic slant range model. Third, an improved azimuth NLCS operator in the Doppler frequency domain was established for the spotlight illumination of the transmitter and receiver in mini-UAV based BFSAR systems. Finally, the proposed algorithm is validated by both simulations and real datasets.

Squint‐minimised chirp scaling algorithm for bistatic forward‐looking SAR imaging

A new focusing solution for one-stationary bistatic forward-looking synthetic aperture radar (BFSAR) is presented in this study. Due to the potential applications of BFSAR, such as aircraft self-landing, missile terminal guidance, BFSAR technique receives considerable attention. However, the BFSAR system usually has a large forward-looking (or squint) angle. It brings severe range cell migration and strong range dependence of effective frequency-modulation rate. Therefore, the focusing depths of traditional imaging algorithms, such as the range Doppler algorithm, chirp scaling algorithm (CSA), are not enough to process the BFSAR data. To accommodate for this problem, a squint-minimisation method for BFSAR is studied in thisarticle. Squint-minimisation method is used to shear the highly squint data to small squint data. Then, the authors propose a modified CSA based on the sheared data to implement imaging. Numerical simulations are carried out and show that the proposed algorithm still has a good focusing depth under a large forward-looking angle.

Bistatic Forward-Looking SAR KDCT-FSFT-Based Refocusing Method for Ground Moving Target With Unknown Curve Motion

In real application scenario of bistatic forward-looking synthetic aperture radar (BFSAR), ground moving target (GMT) is generally smeared severely in SAR image, due to its unknown range cell migration (RCM) and Doppler frequency migration (DFM). When GMT moves along an unknown curve trajectory, its high-order RCM and DFM (including the second- and third-order terms) would further aggravate the difficulty of GMT refocusing. To address this issue, an efficient GMT refocusing method via keystone-based delay-correlation transform and fast searching Fourier transform (KDCT-FSFT) is proposed. First, the KDCT is proposed to correct the first- to third-order RCMs regardless of target's motion state and position information. Meanwhile, the order of GMT's phase response is reduced as well. Then, FSFT is applied to estimate the third-order Doppler parameter of GMT. In the following, a 2-D fast Fourier transform (2D-FFT) can be applied to integrate the target signal coherently in Doppler parameters domain, where the Doppler centroid and Doppler frequency rate of GMT can be estimated. Finally, with the aforesaid estimated Doppler parameters, RCM and DFM can be well corrected and target with unknown curve motion can be finely refocused. Compared with the existing methods, not only the refocusing accuracy of the proposed method is higher, but also its processing is more efficient, since the procedures in the proposed method are performed with respect to all the range cells in the corresponding aperture, i.e., GMT refocusing is achieved by the 2-D data received in one aperture, rather than along every single range cell. Both the simulation and experimental results are given to validate the effectiveness of the proposed method.

Correction of ``A Frequency-Domain Imaging Algorithm for Translational Variant Bistatic Forward-Looking SAR''

In [1] , the result of Fig. 13(b) was incorrectly provided. Now, we provide the corrected result, as shown in Fig. 1 .

A Frequency-Domain Imaging Algorithm for Translational Variant Bistatic Forward-Looking SAR

Bistatic forward-looking synthetic aperture radar (BFSAR) breaks through the limitations of the conventional monostatic SAR on the forward-looking imaging. However, the problems of range cell migration (RCM) caused by the linear range walk and 2-D spatial variability of Doppler parameters become more serious and complicated in translational variant BFSAR. In this article, a keystone transform is introduced to correct the linear RCM. Based on the characteristics of a small aperture, the nonlinear chirp scaling (NCS) is discussed in the frequency domain to equalize the azimuth-range-dependent Doppler parameters. The improved NCS in our newly proposed BFSAR imaging algorithm, especially the re-definition of range direction and the model of spatial variant phase, differentiates this article from all the existing studies in the literature on BFSAR signal processing. Simulation results and real data processing further validate the effectiveness of the proposed algorithm.

Fast Factorized Backprojection Imaging Algorithm Integrated With Motion Trajectory Estimation for Bistatic Forward-Looking SAR

A bistatic forward-looking synthetic aperture radar (BFSAR) is increasingly in the focus of study, as it breaks through the limitations of imaging on a forward-looking terrain of a moving platform. Fast factorized backprojection (FFBP) is a reliable BFSAR imaging algorithm, with both imaging precision and efficiency being taken into consideration. In FFBP imaging, compensation of the motion errors is important to obtain a well-focused image. To accomplish an accurate motion compensation in image processing, a high-precision navigation system is needed. However, in many cases, because of the accuracy limit of such systems, motion errors are difficult to be compensated correctly, resulting chiefly in resolution decrease in the final images. To deal with such a problem, we propose an FFBP imaging algorithm integrated with motion trajectory estimation for BFSAR. First, a coarse-to-fine residual range cell migration (RCM) correction scheme is applied to ensure the residual RCM within a range resolution. Then, an optimization model with respect to motion trajectory estimation under the criterion of maximum image sharpness is built during FFBP imaging. According to the coarse-to-fine residual RCM correction scheme and the motion trajectory estimation model, a block coordinate descent technique based on steepest descent optimization method integrated with residual RCM correction is proposed to estimate the motion errors in FFBP imaging. We empirically compare the proposed method with several state-of-the-art BFSAR imaging and autofocus algorithms. Simulations on BFSAR data show that the proposed method is more accurate and has similar computational cost.

Focusing Bistatic Forward-looking Synthetic Aperture Radar Based on An Improved Hyperbolic Range Model and A Modified Omega-K algorithm.

For parallel bistatic forward-looking synthetic aperture radar (SAR) imaging, the instantaneous slant range is a double-square-root expression due to the separate transmitter-receiver system form. The hyperbolic approximation provides a feasible solution to convert the dual square-root expression into a single-square-root expression. However, some high-order terms of the range Taylor expansion have not been considered during the slant range approximation procedure in existing methods, and therefore, inaccurate phase compensation occurs. To obtain a more accurate compensation result, an improved hyperbolic approximation range form with high-order terms is proposed. Then, a modified omega-K algorithm based on the new slant range form is adopted for parallel bistatic forward-looking SAR imaging. Several simulation results validate the effectiveness of the proposed imaging algorithm.