Airborne synthetic aperture radar with an imaging resolution of up to 0.03m is developed. The imaging process, however, suffers from motion errors with 2-dimensional spatial-variant characteristics that invalidate approximations suitable for motion compensation (MOCO) in a sub-meter resolution SAR system. To estimate and compensate for 2-dimensional spatial-variant motion errors (2-D SVME), we propose a novel two-stage processing framework for the ultrahigh-resolution microwave photonic (UHR MWP) airborne SAR imaging. In the first stage, the two-step MOCO compensates for the spatial-invariant and range-variant motion errors. Range down-sampling and azimuth windowing are adopted to increase the robustness of the method. Afterward, the coupling of the 2-D SVME is greatly decreased, and a coarse-focused image is obtained. In stage two, an extended autofocusing method in the 2-D wavenumber domain based on the extended range migration algorithm (ERMA) compensates for the azimuth-variant motion errors and non-systematic range cell migration (NsRCM) for 2-D wide swath stripmap SAR data. After the ERMA and obtaining the coarse-focused image, the analytical structure of the residual 2-D phase error in the wavenumber domain is revealed. A nonlinear scaling equation is developed, relating the 1-D azimuth phase error to the 2-D phase error correction. The Ku-band stripmap ultrahigh-resolution microwave photonic (0.03 m) airborne SAR data are analyzed to verify the necessity and effectiveness of the proposed framework. A well-focused stripmap SAR image is obtained.

Geosynchronous-Earth-orbit (GEO) synthetic aperture radar (SAR) provides excellent continuous observing capability and large swath. However, the extremely long synthetic aperture time, the curved orbit, and the nonplanar ground surface cause serious spatial variance in the GEO SAR signal. In this article, a novel fast Cartesian back-projection (BP) algorithm based on subaperture imaging on ground and multistage fusion is proposed for accurately and efficiently imaging of GEO SAR. The imaging grids are arranged on the ground surface to avoid the azimuth defocusing caused by the flat ground approximation. Then, a new two-step spectrum compression method is derived to solve the spectrum aliasing of subaperture images. Also, a multistage image fusion method is adopted to combine all the subaperture images with high efficiency. The computational complexity and the approximation of the proposed algorithm are also discussed. Simulation results verify the effectiveness of the proposed algorithm.

Image formation of large scenes is still challenging in medium-earth-orbit (MEO) synthetic aperture radar (SAR) due to the existence of severe 2-D space variance. In this paper, the properties of space variance are analyzed in detail, and then a variable-coefficient fourth-order range model is adopted to model the space-variant range history of every target in a large scene accurately. A method integrating a modified chirp scaling algorithm with joint time-Doppler resampling is proposed to address the range-variant range cell migration, as well as the azimuth-variant frequency-modulation rate and higher order Doppler parameters. The computational burden and alternative implementation approaches are also discussed. Finally, processing of simulated data for MEO SAR with 2-m resolution is presented to validate the proposed algorithm.

The available focusing algorithms for medium-Earth-orbit (MEO) SAR are all based on the complex nonhyperbolic range equation, which may make it more difficult in imaging processing. In this paper, we model the range equation as the standard hyperbolic form based on the motion compensation (MOCO) principle. However, the conventional two-step MOCO may introduce azimuth spectrum expansion due to the potential large motion error, which can lead to severe azimuth ambiguity. To resolve this problem, we develop an omega-K algorithm based on a modified two-step MOCO and an adaptively straight equivalent (ASE)-velocity model. The algorithm is implemented through three-step processing: 1) the modified two-step MOCO does not compensate for the quadratic motion error (the main factor for the spectrum expansion); 2) an ASE-velocity model is introduced to compensate for the quadratic motion error; and 3) an extended Stolt mapping is proposed to perform the accurate range cell migration correction, and the tandem singular value decomposition-nonlinear chirp scaling algorithm is to correct the azimuth-variant phase error and to perform the azimuth compression. Processing of simulated data and airborne SAR real data validates the effectiveness of the proposed algorithm.

Signal bandwidth and integration time are two significant parameters of a geosynchronous synthetic aperture radar (SAR) sensor. They directly determine the resolution characteristic of SAR imagery. Because their contributions to the ground impulse response width (IRW) curve (consists of −3-dB resolutions in every direction) are severely coupled, an analytical extraction method of the ground IRW curve is studied to analyze the coupling characteristic. Due to the coupling, the IRW curve is generally spatially variant and, thus, can degrade the quality of SAR imagery. To minimize the variation, the two parameters are optimized. However, the optimized signal bandwidth is found to be satellite position varied, which complicates the system design. To solve this problem, a parameter optimization model is built to obtain one optimal signal bandwidth as well as to decrease the variation.

Ship motions during long coherent processing interval (CPI) have six degrees of freedom, and the oscillatory motions are roughly periodical. The traditional ship imaging methods usually use a short time interval to form an image, while the image quality may suffer from low resolution, poor signal-to-noise ratio (SNR), and scatter scintillation. Using a longer CPI to generate an image may improve the quality but, however, largely increase the focusing difficulty. In this article, we investigate the focusing challenges of oscillatory ships with long CPI. Through analyzing the relative motion between the radar and the ship, the properties of wavenumber domain support (WDS) and point spreading function (PSF) of oscillatory ship imaging are studied. It is illustrated that the WDS is a 3-D sparse curved surface generated by the complex relative motion, with a time-variant energy density, nonparallel spectrum boundaries, and a complex structure. The PSF of an oscillatory ship may have a 3-D resolution but also multiple high-level sidelobes. The relationship between the WDS and the nonideal PSF is illustrated with the projection slice theorem (PST). Moreover, it is discussed that the scatterers distributed on a 3-D ship cannot be focused uniformly on a 2-D imaging plane (IP) due to the variation of the slant-range plane (SRP). The projection relationships of the resolutions and focusing positions between the SRP and the IP are also derived. Simulation results are presented to validate the analyses throughout this article.