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UBC Theses and Dissertations

Improved Doppler centroid estimation algorithms for satellite SAR data Li, Shu

Abstract

In high-quality SAR data processing, accurate estimation of the Doppler centroid frequency is essential for obtaining good image focus. However, existing Doppler centroid estimation algorithms cannot obtain reliable Doppler ambiguity estimates, especially in areas with low SNR and low contrast. This thesis presents several techniques for improving existing Doppler ambiguity estimators, thereby achieving more accurate absolute Doppler centroid estimates for high-quality SAR data processing. Following an introduction of the existing Doppler centroid estimation algorithms for baseband Doppler centroid and Doppler ambiguity estimation, we present two methods for improving the sensitivity of the Multi-Look Beat frequency (MLBF) Doppler ambiguity estimator. One method uses range cell migration correction (RCMC) to straighten the target trajectories before applying the beat frequency estimator. The other applies more accurate frequency estimators to the beat signal. We then discuss possible improvements to slope-based Doppler ambiguity resolvers. The method using the Radon transform to estimate the slope of target trajectories has been well explained and examined on real satellite SAR data. We propose a simpler method that uses Azimuth integration with RCMC to find the correct ambiguity number. Our experimental results show that it has a similar or better performance than the Radon Transform method. We have tested all of the improved Doppler ambiguity estimators using real satellite SAR data, RADARSAT-1 Vancouver scene. Our results show that the proposed methods significantly improve the performance of the existing Doppler Ambiguity estimators, and can achieve accurate Doppler centroid estimates in most areas, even with medium to low contrast scenes.

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