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Airborne synthetic aperture radar (SAR) is susceptible to atmospheric disturbance and other factors that cause the position offset error of the antenna phase center and motion error. In close-range detection scenarios, the large elevation angle may make it impossible to directly observe areas near the underlying plane, resulting in observation blind spots. In cases where the illumination elevation angle is extremely large, the influence of range variant envelope error and phase modulations becomes more serious, and traditional two-step motion compensation (MOCO) methods may fail to provide accurate imaging. In addition, conventional phase gradient autofocus (PGA) algorithms suffer from reduced performance in scenes with few strong scattering points. To address these practical challenges, we propose an improved phase-weighted estimation PGA algorithm that analyzes the motion error of UAV SAR under a large elevation angle, providing a solution for high-order range variant motion error. Based on this algorithm, we introduce a combined focusing method that applies a threshold value for selection and optimization. Unlike traditional MOCO methods, our proposed method can more accurately compensate for spatially variant motion error in the case of scenes with few strong scattering points, indicating its wider applicability. The effectiveness of our proposed approach is verified by simulation and real data experimental results. [ABSTRACT FROM AUTHOR]

For unmanned aerial vehicle (UAV) synthetic aperture radar (SAR) imaging, motion errors cannot be obtained accurately when high precision motion sensors are not equipped on the platform. This means that traditional data-based motion compensation (MOCO) cannot be directly implemented due to large measurement errors. In addition, classic autofocusing techniques, such as phase gradient autofocus (PGA) or map-drift algorithm (MDA), do not perform well with spatially variant errors, greatly affecting the imaging qualities, especially for high-resolution and large-swath cases. In this study, an improved spatially variant MOCO approach based on an MDA is developed to effectively eliminate the spatially variant errors. Based on the coarse and precise MDA chirp rate error estimation, motion errors are optimally acquired by the random sample consensus (RANSAC) iteration. Two-dimensional (2D) mapping is used to decouple the spatially variant residual errors into two linear independent dimensions so that the chirp-z transform (CZT) can be performed for echo data correction. Unlike traditional approaches, the spatially variant components can be compensated without any measured motion information, which indicates that the proposed approach can be applied to the common UAV SAR system with significant measurement errors. Simulations and real data experiments were used to evaluate the performance of the proposed method. The simulation results show that the proposed algorithm is able to effectively minimize spatially variant errors and generate much better imaging results. [ABSTRACT FROM AUTHOR]

As a transition platform between aircraft and satellite, hypersonic vehicle-borne (HSV) synthetic aperture radar (SAR) could offer many advantages such as strong survival ability, fast response, and wide detection range. However, due to the complex aerodynamic configuration and flight characteristics of the hypersonic platform, the HSV SAR faces new challenges including serious cross-couplings and spatial variations. In order to deal with these issues, a radius/angle algorithm (RAA) is devised, which has a similar processing flow as that of the conventional polar format algorithm (PFA). In the RAA, a novel 2-D interpolation function, similar to that of the PFA which is performed in the Cartesian coordinates, is derived in the curvilinear coordinate system. Due to the high accuracy of the multi-decomposition by using the polar radius and polar angle, the RAA has a much larger depth-of-focus than that of the PFA. Moreover, the RAA approach is insensitive to the height variations for the HSV SAR with curved trajectory flight, whereas the PFA is not because of the out-of-plane projection effect. Simulation results verify the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

This letter proposes an omega-K algorithm for missile-borne synthetic aperture radar (SAR) diving with constant acceleration. The essence of the novel method is to derive a reference function multiplication from the equivalent range history. The true range history is divided into two parts: range independent and range dependent. After compensating the range-independent part with considering all the terms, we can regard the range-dependent part as an equivalent range history with a form similar to that of conventional SAR. Then, an analytical 2-D spectrum can be used for the omega-K algorithm. The proposed algorithm can handle general missile configurations with wide swaths and high squint angles. Simulation results are presented to validate the proposed method. [ABSTRACT FROM PUBLISHER]

The spaceborne transmitter/missile-borne receiver (ST/MR) synthetic aperture radar (SAR) could provide several unique advantages, such as wide coverage, unrestricted geography, a small detection probability of the missile, and forward-looking imaging. However, it is also accompanied by problems in imaging, including geometric model establishment and focusing algorithm design. In this paper, an ST/MR SAR model is first presented and then the flight-path constraint, characterized by geometric configurations, is derived. Considering the impacts brought about by the maneuvers of the missile, a non-'Stop-Go' mathematical model is devised and it can avoid the large errors introduced by the acceleration, which is neglected in the traditional model. Finally, a two-dimensional (2-D) scaling algorithm is developed to focus the ST/MR data. Without introducing any extra operations, it can greatly remove the spatial variations of the range, azimuth, and cross-coupling phases simultaneously and entirely in the 2-D hybrid domain. Simulation results verify the effectiveness of the proposed model and focusing approach. [ABSTRACT FROM AUTHOR]