Spatially Variant Apodization for Squinted Synthetic Aperture Radar Images

Abstract

Spatially variant apodization (SVA) is a nonlinear sidelobe reduction technique that improves sidelobe level and preserves resolution at the same time. This method implements a bidimensional finite impulse response filter with adaptive taps depending on image information. Some papers that have been previously published analyze SVA at the Nyquist rate or at higher rates focused on strip synthetic aperture radar (SAR). This paper shows that traditional SVA techniques are useless when the sensor operates with a squint angle. The reasons for this behaviour are analyzed, and a new implementation that largely improves the results is presented. The algorithm is applied to simulated SAR images in order to demonstrate the good quality achieved along with efficient computation.

A SAR sidelobe suppression algorithm based on modified spatially variant apodization

“…More generally, to find the minimum of |g′(m)| under the constraints (8), (9), (11) and (12), we can first seek the maximum and minimum of g′(m) respectively, that is min g′(m), s.t. (8), (9), (11), (12), and max g′(m), s.t. (8), (9), (11), (12).…”

“…(8), (9), (11), (12), and max g′(m), s.t. (8), (9), (11), (12). We can use the simplex method [15] or interior point method [16] to solve the linear programming problem.…”

“…Spatially variant apodization (SVA) [5] is able to effectively suppress the sidelobe via sequential nonlinear operations applied to complex-valued SAR imagery without any priori knowledge. SVA has a wide range of applications in super-resolution [6], sparse aperture fill [7], squint SAR [8], interferometric SAR (INSAR) [9], inverse SAR (ISAR) [10] and sounding radar [11], which can achieve high-resolution SAR imaging. Stankwitz proposed SVA [12] which requires that the data be sampled at an integer multiple of the Nyquist frequency.…”

A super-resolution algorithm for synthetic aperture radar based on modified spatially variant apodization

“…The spatially variant apodization (SVA) [5] is able to effectively suppress the sidelobe via sequential nonlinear operations applied to complex-valued SAR imagery without any priori knowledge. The SVA has a wide range of applications in super-resolution [6], sparse aperture fill [7], squint SAR [8], interferometric SAR (INSAR) [9], inverse SAR (ISAR) [10] and sounding radar [11], which can achieve high-resolution SAR imaging. Stankwitz et al [12] proposed the SVA which requires that the data be sampled at an integer multiple of the Nyquist frequency.…”

Sar/Insar Image Processing Based on Modified Spatially Variant Apodization

“…Spatially Variant Apodization (SVA) [5] is able to effectively suppress the sidelobe via sequential nonlinear operations applied to complex-valued SAR imagery without any priori knowledge. SVA has a wide range of applications in super-resolution [6] , sparse aperture fill [7] , squint SAR [8] , interferometric SAR (INSAR) [9] , inverse SAR (ISAR) [10] and sounding radar [11] , which can achieve high-resolution SAR imaging. H. C. Stankwitz proposed SVA [12] which requires that the data be sampled at an integer multiple of the Nyquist frequency.…”