星载SAR成像中基于熵的多普勒质心估计与斑点噪声抑制
Entropy-Based Doppler Centroid Estimation and Speckle Noise Reduction for Spaceborne SAR Imaging
AI总结：
针对星载SAR成像中多普勒质心频率未补偿导致散焦、斑点噪声降低图像质量的问题，提出基于图像熵的多普勒质心小数部分估计方法与斑点噪声抑制算法，经RADARSAT-1卫星数据验证有效提升了成像质量。
摘要：
本文研究条带模式星载合成孔径雷达（Synthetic Aperture Radar, SAR）成像，重点关注多普勒质心频率估计。非零多普勒质心频率由非零斜视角导致，若不进行补偿会造成图像散焦。我们提出一种基于重建图像熵的高效方法，用于估计多普勒质心频率的小数部分。此外，本文探讨了会大幅降低重建图像质量的斑点噪声，并尝试有效减轻其影响。在实施斑点噪声抑制算法后，重建图像的质量得到显著提升。最后，我们利用加拿大温哥华地区的RADARSAT-1卫星采集的实验数据，验证了所提技术的准确性与有效性。
英文摘要：
In this paper, we present strip-map mode spaceborne Synthetic Aperture Radar (SAR) imaging with the focus on Doppler centroid frequency estimation. The non-zero Doppler centroid frequency is the result of non-zero squint angle which if it is not compensated it can de-focus the image. We present an efficient method based on the entropy of the reconstructed image to estimate the fractional part of the Doppler centroid frequency. Furthermore, we discuss the speckle noise, which degrades the quality of the reconstructed images considerably, and attempt to alleviate its effect efficiently. Following the implementation of the speckle noise reduction algorithm, a significant improvement in the quality of the reconstructed images is achieved. Finally, we utilize the experimental data gathered from the RADARSAT-1 satellite of Vancouver Canada to verify the accuracy and effectiveness of the proposed techniques.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
