田冲宵,谢先明

• 1:广西科技大学自动化学院
• 2:广西科技大学电子工程学院

摘要(Abstract)：

相位解缠（phase unwrapping, PU）是干涉合成孔径雷达（interferometric synthetic aperture radar, InSAR）技术的关键步骤。在多基线高程重建算法中，聚类分析算法是一种极具潜力的高效率算法，但其噪声鲁棒性有待于进一步提高。针对这一问题，提出一种基于深度学习的平方根容积卡尔曼滤波多基线相位解缠算法。首先，构建一种多通道边缘检测网络，用于从多通道干涉图中提取边缘信息；其次，根据边缘信息将多通道干涉图分为突变区域与连续区域，对于突变区域采用聚类分析算法反演高程，连续区域使用平方根容积卡尔曼滤波进行预测。实验结果表明，该方法具有较好的高程重建精度和噪声鲁棒性。

关键词(KeyWords)： 卡尔曼滤波;相位解缠（PU）;干涉合成孔径雷达（In SAR）;多基线;聚类分析;深度学习

Abstract:

Keywords:

基金项目(Foundation): 国家自然科学基金项目(62161003);; 广西自然科学基金项目(2023GXNSFAA026024)资助

作者(Author): 田冲宵,谢先明

DOI: 10.16375/j.cnki.cn45-1395/t.2025.04.011

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