Sea clutter suppression plays a crucial role in maritime moving target indication. However, in the bistatic SAR (BiSAR) system, traditional space-time adaptive processing (STAP) method can’t satisfy the expected performance due to severe range cell migration (RCM), Doppler frequency migration (DFM), nonstationary clutter, and spatio-temporal spectrum expansion caused by the internal motion of sea clutter. To issue these problems, a matrix sparse model based spatio-temporal spectrum recovery method is proposed. The proposed method mainly consists of three steps. Firstly, Generalized Keystone transform in preprocessing stage is used for RCM correction and DFM compensation. Then, multiple spatio-temporal samples acquisition strategy for cell under test is designed, to enhance the solution robustness. Next, a matrix sparse model for BiSAR spatio-temporal spectrum recovery is constructed and solved. Finally, the sea clutter suppression performance is verified with numerical simulations.

In high sea states, ship targets often exhibit intense and complex rotational movements due to sea waves, leading to defocused and time-varying imaging results for bistatic synthetic aperture radar (SAR). This paper introduces a novel strategy for selecting optimal imaging times of ship targets by analyzing image projection plane (IPP). Utilizing short-time Fourier transform (STFT) on target echoes, rotation parameters of the ship are estimated via differential evolution (DE) method, to determine IPP throughout the entire observation period, so that the optimal imaging moments can be selected. By comparison of image contrasts and entropies, the optimal imaging time lengths are also refined. Overall, this paper offers an optimal time section strategy ensuring clear views of ship targets, and simulation results verify its effectiveness.

Sea clutter suppression plays a crucial role in maritime moving target indication. However, in the bistatic SAR (BiSAR) system, traditional space-time adaptive processing (STAP) method can’t satisfy the expected performance due to severe range cell migration (RCM), Doppler frequency migration (DFM), nonstationary clutter, and spatio-temporal spectrum expansion caused by the internal motion of sea clutter. STAP based on sparse recovery (SR-STAP) is an effective method for clutter suppression, but two major problems still remain. (1) The multiple samples for solution need to satisfy the same spatio-temporal distribution characteristics. Nevertheless, such consistency is not applicable when considering violent internal motion of sea clutter. (2) The computational complexity is exceedingly high. To issue these problems, an efficient matrix sparse recovery STAP (MSR-STAP) method based on Kronecker transform is proposed. The proposed method mainly consists of three steps: (1) Generalized Keystone transform in preprocessing stage is used for RCM correction and DFM compensation. (2) Multiple spatio-temporal samples acquisition strategy for CUT is designed, to enhance the solution robustness. (3) An efficient MSR-STAP model is established and solved. Subsequently, the space-time filter is designed without clutter covariance matrix estimation, to facilitate effective sea clutter suppression. Compared with existing SR-STAP methods, computational complexity of the proposed method decreases by orders of magnitude, and the spatio-temporal spectrum expansion effect is greatly reduced. The sea clutter suppression performance is verified with numerical simulations.

Localization and tracking are important components for ground-moving target indication (GMTI). The traditional range-Doppler (RD) localization model is always applied to locate stationary targets in bistatic synthetic aperture radar (BiSAR). However, for moving targets, this localization model is no longer applicable due to the strong coupling of position and velocity with Doppler frequency. To address the severe challenge, this article proposes a joint moving target localization and tracking method for BiSAR-GMTI via transmitter–receiver trajectories extraction and inversion. The key innovation is the derivation of closed-form localization results for moving targets, which is beneficial for the quantitative analysis of localization error. The proposed method is structured into three main parts. First, to accurately capture the range history trajectory information, a segmented fitting extraction and inversion framework is designed. Second, to estimate the moving target’s initial state and demonstrate localization observability, joint range localization equations are established where the closed-form localization result of the moving target is derived. Finally, by defining the appropriate state transition equation and observation equation, and incorporating particle filtering (PF), the position measurement errors of bistatic platforms are weakened, and accurate tracking of moving targets is realized. The proposed method only utilizes range information, mitigating localization errors caused by Doppler estimation inaccuracies effectively. Simulation experiments and real data both demonstrate the localization and tracking accuracy of moving targets.

Different sea states make maritime ship targets move three-dimensionally, causing imaging results severely defocused. Therefore, selection of proper imaging time has attracted global attention in the field of ISAR imaging. This paper proposes an imaging time and plane selection algorithm based on short-time fractional Fourier transform (STFrFT). By STFrFT, time-frequency curves of the target echo for different fractional orders are obtained, and probability density functions of frequency distributions are offered to estimate when Doppler frequency of the target changes most stably. Then, different imaging planes of different STFrFT orders are analyzed to select the optimal imaging time moment. Finally, by comparing image contrasts of various imaging lengths, the optimal imaging time is selected. In general, this method can select the optimal imaging moment, imaging length and imaging plane, and simulation verifies the effectiveness of this imaging method.

Moving target indication (MTI) plays an important role in both military and civilian applications. However, the performance of MTI has deteriorated dramatically due to clutter interference. In bistatic synthetic aperture radar (BiSAR), MTI mainly faces three challenges: First, BiSAR has large range cell migration (RCM); Second, the Doppler spectrum is severely extended; Third, the clutter presents nonhomogeneity and nonstationarity. In order to solve these problems, a novel MTI method for single channel BiSAR is proposed. At first, the first-order keystone transform (KT) is performed to remove linear range walk (RWK) regardless of unknown motion parameters. Then, the high-order RCMC is realized by reference compensation function. It is extremely difficult to achieve MTI because moving target is submerged in clutter whether in azimuth time domain or Doppler domain. So, to achieve separation of moving target from stationary clutter effectively, a novel procedure named increased dimension rotation (IDR) processing is introduced. Thereafter, the distribution characteristic of moving target and stationary clutter after rotation processing is analyzed exhaustively. Naturally, the optimal filter is constructed for clutter suppression in the light of the distribution characteristic. Finally, the energy of moving target can be accumulated after inverse increased dimension rotation and Fractional Fourier Transform (FrFT). And the MTI in BiSAR can be easily achieved.

Moving target indication (MTI) in bistatic synthetic aperture radar (BiSAR) is a promising task in both civilian and military fields. However, it suffers severe challenges under the influence of clutter. MTI in BiSAR mainly faces three challenges: 1) the range cell migration (RCM) of BiSAR is larger than that of monostatic synthetic aperture radar; 2) the clutter range-Doppler spectrum is severely extended; and 3) the clutter characteristic is closely related to geometrical configuration, with nonhomogeneity and nonstationarity. To solve these problems, based on single-channel BiSAR, a joint clutter suppression and MTI method is proposed. First, to ensure that the energy of an arbitrary target is concentrated in one range cell, RCM correction (RCMC) is completed by the first-order keystone transform (KT) and high-order RCMC. Then, an important step named increased dimension rotation (IDR) is applied, which mainly consists of two stages. One is increased dimension processing, which introduces a 2-D azimuth rotated time domain (ARTD). The other is rotation processing, which makes signals in one range cell rotated to 2-D ARTD. After that, the distribution characteristic between the moving target and stationary clutter in 2-D ARTD is analyzed. Next, an optimal filter for clutter suppression is designed according to the characteristics of signal distribution in 2-D ARTD. Furthermore, the corresponding inverse IDR processing and fractional Fourier transform (FrFT) are performed, and finally, MTI can be realized accurately. Generally, the proposed method has good robustness and low system complexity, and its effectiveness is proven by numerical simulations.

Bistatic synthetic aperture radar (BiSAR) has been attracting worldwide attention because of its forward-looking imaging and high anti-interference. In harsh environment, it is vital for BiSAR to conduct extensive surveillance, imaging, and recognition of maritime ship targets. However, under the disturbance of sea waves, the ship target has an unknown and massive three-dimensional (3-D) rotation, so that its imaging projection plane (IPP) is also undetermined. Thus, high-dimensional random distortion appears in imaging results, making it difficult to recognize the target through two-dimensional distorted images effectively. To solve these problems, bistatic SAR maritime ship target 3-D image reconstruction method without distortion in local Cartesian coordinate (LCC) is proposed. In this paper, according to positions of scatterers and rotation parameters, significant differences of different scatterers of maritime ship targets have been found in bistatic range, Doppler centroid (DC), and Doppler frequency rate (DFR), which lays a solid foundation for the scatterer separation of ship targets. On this basis, a 3-D R-DC-DFR domain is constructed, and 2-D echoes of the maritime ship target are projected into R-DC-DFR domain to separate scatterers. Then, by remapping data of transmitter and receiver in R-DC-DFR domain to LCC, as well as evaluating their similarity metric, the optimal rotation parameters of the ship target can be obtained via the maximal similarity. Therefore, the image distortion caused by the unknown IPP has been removed, and 3-D image reconstruction of ship targets can be realized without distortion in the LCC. Furthermore, to evaluate performances of 3-D image reconstruction for different rotation parameters and bistatic configurations, 3-D reconstruction index is proposed and analyzed. Both point-targets and maritime ship targets are simulated to emphasize the effectiveness of the proposed method.

Localization plays an important part in the application field of bistatic SAR (BiSAR). The accuracy of traditional localization method for BiSAR depends on the measurement precision of platform. The lower measurement precision, the higher localization error of targets. However, due to the size, cost, and technical limitations of existing attitude measurement devices, it is difficult to satisfy the requirement of high-precision target positioning in BiSAR. This paper proposes a blind locali-zation method based on monostatic equivalent model for BiSAR, which has high tolerance and low sensitivity for measurement error. First, the BiSAR is equivalent to monostatic SAR system based on the principle of Equivalent Phase Center (EPC). Next, the Range-Doppler localization model is applied to fix position for EPC and the relative position of multi-targets are obtained subsequently. At last, establishing localization equation with bistatic range of multi-targets, and the Newton iteration algorithm is devoted to solving localization model constructed above. The effectiveness of the localization method proposed in this paper has been demonstrated and illustrated by numerical simulations.

In recent years, many imaging algorithms for highly squint synthetic aperture radar (SAR) have been proposed. An algorithm based on keystone transform (KT) and azimuth Extended Nonlinear Chirp Scaling (ENLCS) is widely used in highly squint SAR imaging processing. It's effective in solving spatial-variant linear range cell migration (LRCM) and azimuth-variant Doppler parameters. However, due to the highly squint configuration, the beam center crossing time of many illuminated targets are not included in the track. We need extend the azimuth data length to ensure the targets a corresponding position in the data, which leads to an increase in computational complexity. And the imaging result also has geometric distortion. This paper proposes an improved ENLCS method with lower complexity combined with fast KT. First, we use the low complexity KT without interpo-lation in the RCM correction (RCMC) process. Then, we find a solution to reduce the extended data length by adding a time shift factor in the ENLCS process, saving data storage space and operation cost. Finally, geometric correction is performed by the grid mapping. The effectiveness of the proposed method is verified by numerical simulation and real data processing.

Bistatic synthetic aperture radar (BiSAR) has received more and more attentions because of its forward-looking imaging capability and configuration flexibility. For BiSAR moving target imaging, its non-cooperative motion leads to unknown range cell migration (RCM) and additional phase modulation. Consequently, moving target imaging in BiSAR face two main challenges: 1) The unknown RCM correction and Doppler parameter estimation are tightly coupled. 2) The Doppler parameters of the extended moving target’s different scattering points are different, i.e., the Doppler parameters are spatially variant. To cope with these problems, an optimal polar format refocusing method for bistatic SAR moving target imaging is proposed. First, the main part of tight coupling and spatial variation effects caused by the BiSAR platforms are eliminated, while the moving target is two-dimensional (2-D) defocused and shifted. Then, we analyze the characteristics of two-dimensional defocused and shifted of the moving target in BiSAR, and give the analytical expressions. On this basis, a new bistatic polar format transformation is introduced, in which the degree of freedom of defocusing result is reduced from 2-D to only one-dimension. After that, the parameter estimation and refocusing issues are transformed into a constrained optimization problem (COP), and differential evolution (DE) is applied to solve the COP and obtain the refocusing results. Finally, considering the spatial variation of the extended moving target, the compensation processing is performed to relocate each scattering point. Numerical simulations verify the effectiveness of the proposed method.

The echo signal of slow-moving target is usually submerged in clutter signal. As a consequence, ground moving target (GMT) separation is challenging because of the decreasing of detection performance. To solve this problem, this paper proposes a moving target detection method with single-channel for bistatic forward-looking SAR (BFSAR) which mainly contains three steps. First, range cell migration (RCM) is corrected by Keystone transform. Next, Extended Nonlinear Chirp Signal (NLCS) algorithm is applied to equalize the spatial variant Doppler parameters and subpress clutter spectrum broadening. At last, according to the difference of Doppler FM rate between GMT and the stationary clutter, the Short Time Fourier Transform (STFT) is devoted to separate GMT from the stationary clutter. The effectiveness of the detection method proposed in this paper has been demonstrated and illustrated by numerical simulations.