Abstract

The determination of Doppler ambiguity number (DAN) is indispensable for the generation of high-quality synthetic aperture radar (SAR) images. An incorrect DAN leads to lower image signal-to-noise ratio and degradation in the system impulse response function. Based on the relationship between DAN errors and the image quality, a novel DAN estimation algorithm named image-quality-based Doppler ambiguity resolver is presented. In the proposed algorithm, the DAN-dependent linear range cell migration correction and DAN-dependent azimuth compression are carried out in subscenes to obtain 2-D compressed SAR images, which are further employed to estimate DAN via minimizing the entropy. The presented algorithm is more robust than conventional methods to cope with demands of both low- and high-contrast scene applications. In addition, the approach is computationally efficient because it can be properly applied to segments of range-compressed data in small size and only a few sets of short fast Fourier transforms are required. Finally, experiments over real data of airborne X-band and spaceborne C-band are carried out to demonstrate the performance of the proposed approach.

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