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李春, 李家莹, 李蓉, 等. 基于封闭聚类与无味信息滤波的多基线高程重建算法J. 桂林电子科技大学学报, 2025, 45(2): 144-150. DOI: 10.16725/j.1673-808X.2022120
引用本文: 李春, 李家莹, 李蓉, 等. 基于封闭聚类与无味信息滤波的多基线高程重建算法J. 桂林电子科技大学学报, 2025, 45(2): 144-150. DOI: 10.16725/j.1673-808X.2022120
LI Chun, LI Jiaying, LI Rong, et al. A multi-baseline elevation reconstruction algorithm based on closed-form clustering and unscented information filterJ. Journal of Guilin University of Electronic Technology, 2025, 45(2): 144-150. DOI: 10.16725/j.1673-808X.2022120
Citation: LI Chun, LI Jiaying, LI Rong, et al. A multi-baseline elevation reconstruction algorithm based on closed-form clustering and unscented information filterJ. Journal of Guilin University of Electronic Technology, 2025, 45(2): 144-150. DOI: 10.16725/j.1673-808X.2022120

基于封闭聚类与无味信息滤波的多基线高程重建算法

A multi-baseline elevation reconstruction algorithm based on closed-form clustering and unscented information filter

  • 摘要: 针对干涉合成孔径雷达高程重建技术在复杂地形下的地形重建效率较低的问题,提出一种基于封闭聚类与无味信息滤波的多基线高程重建算法。首先,利用封闭聚类算法粗略估计地形高度,随后利用残差点识别算法及边缘检测算子等辅助信息获取地形突变点,从而获取突变区域高程值;其次,构建抗噪性能较好的多基线无味信息滤波相位解缠模型,利用效率较高的堆排序路径跟踪策略引导相位解缠路径,进行逐像元解缠;最后,通过比较以不同权重概率密度函数为检测标准的可信度的大小,判断每个像元的最终估计高程。研究结果表明,该算法效率较高,能处理大规模干涉数据集情况下地形快速高程重建问题,同时实验结果也充分验证了算法的可行性。

     

    Abstract: Aiming at the difficulty of low terrain reconstruction efficiency of interferometric synthetic aperture radar in complex terrain, a multi-baseline elevation reconstruction algorithm based on closed-form clustering and unscented information filter was presented. Firstly, this algorithm roughly estimated the terrain height using a closed-form clustering algorithm, and then obtained the terrain abrupt areas using the phase residue recognition, edge detection operator and other auxiliary information. Secondly, an unscented information filtering phase unwrapping (UIFPU) model with better anti-noise performance was constructed, and an efficient heap-sort path-following strategy was used to guide the path of phase unwrapping of the UIFPU model. Finally, the final estimated elevation of each pixel was determined according to comparing probability density functions of the estimated phase by using different approaches. The experimental results show that the proposed algorithm is efficient and can deal with the problem of terrain rapid elevation reconstruction in the case of large-scale interference data sets, and the feasibility of the proposed algorithm is fully verified by experimental results.

     

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