Sidelobe artifacts are a common problem in image reconstruction from finite-extent Fourier data. Conventional shift-invariant windows reduce sidelobe artifacts only at the expense of worsened mainlobe resolution. Spatially variant apodization (SVA) was previously introduced as a means of reducing sidelobe artifacts, while preserving mainlobe resolution. Although the algorithm has been shown to be effective in synthetic aperture radar (SAR), it is heuristically motivated and it has received somewhat limited analysis. In this paper, we show that SVA is a version of minimum-variance spectral estimation (MVSE). We then present a complete development of the four types of two-dimensional SVA for image reconstruction from partial Fourier data. We provide simulation results for various real-valued and complex-valued targets and point out some of the limitations of SVA. Performance measures are presented to help further evaluate the effectiveness of SVA.

We consider the application of an alternative imaging algorithm to the inversion of strip-mapping synthetic aperture radar (SAR) data. The algorithm was originally developed and successfully applied in the area of geophysics to estimate the conductivity distribution from wellbore induction measurements. The SAR measurement relation satisfies the same form of integral equation describing the wellbore problem. By exploiting the form of the measurement kernel, we derive a SAR image formation algorithm involving deconvolution-backprojection. Unlike correlation-based SAR image formation, our approach is more general, without simplifying assumptions on the range function, and is robust to measurement noise, at the expense of increased computational complexity. Simulation results are presented that demonstrate the effectiveness of the proposed algorithm.

We consider high-resolution radar imaging of an airport runway and environs from an approaching aircraft. Such a radar could provide successful imaging in all-weather conditions. We show the feasibility of using synthetic aperture radar (SAR) to achieve high-resolution reflectivity imagery of a runway region. A formula is given specifying the data collection time required to achieve a desired cross-range resolution. Traditional polar-format processing is inaccurate for this scenario because the required plane-wave assumption is violated. We explore two alternative approaches to SAR image formation based on the exact form of the range function: a general SAR inversion algorithm and the w-k algorithm. We present simulation results for these algorithms, based on realistic SAR parameters.

Sidelobe artifact is a common problem in image reconstruction from finite-extent Fourier data. Conventional shift-invariant windows applied to the Fourier data, reduce sidelobe artifacts at the expense of worsened mainlobe resolution. Stankwitz et al. (1995) have suggested spatially-variant apodization (SVA) as a means of reducing the sidelobe artifacts, while preserving the mainlobe resolution. SVA adaptively selects windows from a set of raised-cosine weighting functions. The algorithm is heuristically motivated, and is known to be effective in synthetic aperture radar (SAR) imaging. However, this technique has received only limited analysis. In this paper, we formulate SVA as a spectral estimator, and show that SVA is a special version of the minimum variance spectral estimator (MVSE). We study the properties of SVA that are inherited from MVSE. Then, we consider the application of SVA to spectral estimation and Fourier reconstruction. Although SVA is effective in SAR, we show that it has limitations for reconstructing real-valued extended targets.

The tomographic formulation of spotlight-mode synthetic aperture radar (SAR) is based on a plane-wave assumption that requires the dimension of the target scene to be much smaller than the range to the target. When this assumption is violated, the resulting image exhibits target smearing and target shift. For severely squinted SAR operation, which arises in runway imaging (for aircraft landing applications), the authors have observed that the smearing is not serious, but that targets are shifted considerably from their correct locations, especially for targets near the edges of the scene. They analyze this problem by first deriving an expression for the spatial shift of a reconstructed point reflector for bandpass Fourier data with phase error. Then, they analyze the point target shift in squint-mode SAR, by incorporating the higher-order terms of the range function. Simulation results for isolated point reflectors are presented.>