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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 However, for moving targets, this localization model is no longer applicable due to the strong coupling of position and velocity with Doppler frequency.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.

Sea clutter suppression plays a crucial role in maritime moving target indication. However, in the bistatic synthetic aperture radar (BiSAR) system, traditional space-time adaptive processing (STAP) method cannot 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 and, nevertheless, such consistency is not applicable when considering violent internal motion of sea clutter and 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 cell under test (CUT) is designed, to enhance the solution robustness; and 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.

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 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 2-D distorted images effectively. To solve these problems, BiSAR maritime ship target 3-D image reconstruction method without distortion in local Cartesian coordinate (LCC) is proposed. In this article, 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.

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.