Precision SAR processing using chirp scaling

Abstract

Abstmct-A space-variant interpolation is required to compensate for the migration of signal energy through range resolution cells when processing synthetic aperture radar (SAR) data, using either the classical rangelDoppler (RID) algorithm or related frequency domain techniques. In general, interpolation requires significant computation time, and leads to loss of image quality, especially in the complex image. The new chirp scaling algorithm avoids interpolation, yet performs range cell migration correction accurately. The algorithm requires only complex multiplies and Fourier transforms to implement, is inherently phase preserving, and is suitable for wide-swath, largebeamwidth, and large-squint applications. This paper describes the chirp scaling algorithm, summarizes simulation results, presents imagery processed with the algorithm, and reviews quantitative measures of its performance. Based on quantitative comparison, the chirp scaling algorithm provides image quality equal to or better than the precision rangel Doppler processor. Over the range of parameters tested, image quality results approach the theoretical limit, as defined by the system bandwidth.

A Novel Imaging Algorithm for Focusing High-Resolution Spaceborne SAR Data in Squinted Sliding-Spotlight Mode

“…RANGE PROCESSING BASED ON MODIFIED CS KERNEL From (3), the signal in the 2-D frequency domain is different from that in [15], which means that the traditional CS kernel cannot be used to process the data directly. Therefore, the chirp scaling factor and the range compensation filter of the traditional CS kernel should be modified if the CS kernel is used to process the data.…”

Extension of the chirp scaling algorithm to 3-D near-field wideband radar imaging

“…The drawback of this technique is the introduction of an interpolation stage that implies a high computational cost and slows down the image generation. As an alternative, the chirp-scaling algorithm (CSA) [2,1] avoids this interpolation, since its implementation requires only Fourier Transforms and complex products. Therefore, it is more efficient than the RMA.…”

“…Starting with the conventional formulation of the CSA, an analytical expression of the IRF in the frequency domain can be derived in a three-stage procedure [1,2]. Consider the measurement set-up shown in Fig.…”

Bandwidth Segmentation Method for Ultra-High Resolution SAR Imaging

“…In this methodology, the decomposed sub bandwidth signals are compressed first by CSA [10] and then combined in 2-D frequency domain to obtain the final image. Performance analysis and simulation indicate that this novel method can improve focal quality of SAR image effectively, and compensate for most of the phase differences between sub pulses in one burst.…”