Given its capacity to generate 2-D fine images of observation areas, very high-resolution (VHR) synthetic aperture radar (SAR) has become increasingly popular in myriad fields, including remote sensing, geoscience, and surveillance. In this article, we present a comprehensive overview of VHR SAR systems and imaging to highlight the related research and promote further development. First, we provide a summary of VHR SAR applications and summarize the typical airborne and spaceborne systems. Subsequently, a detailed overview is provided to demonstrate the range VHR technologies by introducing dechirp processing, stepped-frequency, and microwave photonic. Additionally, VHR imaging methods on different platforms, i.e., ideal trajectory, airborne, and spaceborne, are reviewed. Finally, the challenges and prospects of VHR SAR are presented to inform future research directions. This work provides a valuable resource to improve the system design and signal processing of VHR SAR.

The video synthetic aperture radar (ViSAR) is a new application in radar techniques. ViSAR provides high- or moderate-resolution SAR images with a faster frame rate, which permits the detection of the dynamic changes in the interested area. A moving target with moderate velocity can be detected by shadow detection in ViSAR. This paper analyses the frame rate and the shadow feature, discusses the velocity limitation of ViSAR moving target shadow detection and quantitatively gives the expression of velocity limitation. Furthermore, a fast factorized back projection (FFBP) based SAR video formation method and a shadow-based ground moving target detection method are proposed to generate SAR videos and detect the moving target shadow. The experimental results with simulated data prove the validity and feasibility of the proposed quantitative analysis and the proposed methods.

Wavenumber domain algorithms have unique advantages in processing highly squinted synthetic aperture radar (SAR) data. This paper studies the performance of three commonly used wavenumber domain algorithms including the classical wavenumber domain (CWD) algorithm, extended wavenumber domain (EWD) algorithm, and squint wavenumber domain (SWD) algorithm. First, the wavenumber domain signal expression under the zero-Doppler (ZD) and acquisition-Doppler (AD) reference geometries are both derived. Second, the internal relationship between three wavenumber domain algorithms is analyzed. A new interpretation of the relationship between the three algorithms and an interpolation strategy are given. The analysis not only provides a deeper understanding of the three algorithms, but also provides a basis for comparing them. Then, the performance of the three wavenumber domain algorithms is evaluated from the perspectives of computational complexity, image quality and geometric position through theoretical analysis and simulation experiments. Aiming at the problem that the range and azimuth profiles are not orthogonal, a method to calculate resolution and extract profile is proposed. The results show that all three algorithms can obtain a well-focused images if full-resolution interpolation is performed, and the computational complexityies of CWD and SWD are less than that of EWD.

The high-resolution low frequency synthetic aperture radar (SAR) has serious range-azimuth phase coupling due to the large bandwidth and long integration time. High-resolution SAR processing methods are necessary for focusing the raw data of such radar. The generalized chirp scaling algorithm (GCSA) is generally accepted as an attractive solution to focus SAR systems with low frequency, large bandwidth and wide beam bandwidth. However, as the bandwidth and/or beamwidth increase, the serious phase coupling limits the performance of the current GCSA and degrades the imaging quality. The degradation is mainly caused by two reasons: the residual high-order coupling phase and the non-negligible error introduced by the linear approximation of stationary phase point using the principle of stationary phase (POSP). According to the characteristics of a high-resolution low frequency SAR signal, this paper firstly presents a principle to determine the required order of range frequency. After compensating for the range-independent coupling phase above 3rd order, an improved GCSA based on Lagrange inversion theorem is analytically derived. The Lagrange inversion enables the high-order range-dependent coupling phase to be accurately compensated. Imaging results of P- and L-band SAR data demonstrate the excellent performance of the proposed algorithm compared to the existing GCSA. The image quality and focusing depth in range dimension are greatly improved. The improved method provides the possibility to efficiently process high-resolution low frequency SAR data with wide swath.

Due to geosynchronous synthetic aperture radar’s (GEO SAR) high orbit and low relative speed, the integration time reaches up to hundreds of seconds for a fine resolution. The short revisit cycle is essential for remote sensing applications such as disaster monitoring and vegetation measurements. Three-dimensional (3D) scene imaging mode is crucial for long-term observation using GEO SAR. However, this mode will bring a new kind of space-variant error in elevation. In this paper, we focus on the analysis of the elevation space-variant error. First, the decorrelation problems caused by the spatial variation are presented. Second, by combining with the SAR imaging geometry, the elevation spatial variation is decomposed into two-dimensional (2D) space variation of range and azimuth. Third, an imaging algorithm is proposed to solve the 3D space variation and improve the focusing depth. Finally, simulations with dot-matrix targets and distributed targets are performed to validate the imaging method.

Due to differences in synthetic aperture radar (SAR) and optical imaging modes, there is a considerable degree of nonlinear intensity difference (NID) and geometric difference between the two images. The SAR image is also accompanied by strong multiplicative speckle noise. These phenomena lead to what is known as a challenging task to register optical and SAR images. With the development of remote sensing technology, both optical and SAR images equipped with sensor positioning parameters can be roughly registered according to geographic coordinates in advance. However, due to the inaccuracy of sensor parameters, the relative positioning accuracy is still as high as tens or even hundreds of pixels. This paper proposes a fast co-registration method including 3D dense feature description based on a single-scale Sobel and the ratio of exponentially weighted averages (ROEWA) combined with the angle-weighted gradient (SRAWG), overlapping template merging, and non-maxima suppressed template search. In order to more accurately describe the structural features of the image, the single-scale Sobel and ROEWA operators are used to calculate the gradients of optical and SAR images, respectively. On this basis, the 3 × 3 neighborhood angle-weighted gradients of each pixel are fused to form a pixel-wise 3D dense feature description. Aiming at the repeated feature description in the overlapping template and the multi-peak problem on the search surface, this paper adopts the template search strategy of overlapping template merging and non-maximum suppression. The registration results obtained on seven pairs of test images show that the proposed method has significant advantages over state-of-the-art methods in terms of comprehensive registration accuracy and efficiency.