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A comparative analysis between an hybrid MUSIC-LS algorithm and the standard MUSIC for volume height estimation in tomography-SAR

机译:混合音乐-LS算法与体积高度估计标准音乐的比较分析 - SAR

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This paper deals with an application of Multi-baseline-SAR (Synthetic Aperture Radar) that estimates the biomass in forested area. Tomography is a technique that acquires N images of the study area at different altitudes to retrieve the backscattering signal parameters. This work focuses on inversion algorithms applied to SAR signal. The proposed procedure is based on the fusion of MUSIC (Multiple Signal Classification) and LS (Least Squares) inversions. We used the MUSIC inversion as a reference for the evaluation of the algorithm while the LIDAR height was exploited as ground truth for the inversion. Results of the inversion are validated qualitatively and quantitatively by comparing between the estimated volume backscatter signal (MUSIC and MUSIC-LS) and the DSM (Digital Surface Model) obtained from LIDAR (Laser Detection and Ranging) data.
机译:本文涉及多基线-SAR(合成孔径雷达)的应用,估计森林地区的生物质。断层扫描是一种在不同高度的研究区域获取N图像的技术,以检索反向散射信号参数。这项工作侧重于应用于SAR信号的反演算法。所提出的程序基于音乐(多信号分类)和LS(最小二乘法)endersions的融合。我们使用音乐反转作为评估算法的参考,而激光雷达高度被利用为反演的原始事实。通过比较从LIDAR(激光检测和测距)数据获得的估计体积反向散射信号(音乐和音乐)和DSM(数字表面模型)之间的估计体积反向散射信号(音乐和音乐)和DSM(数字表面模型)进行定性和定量验证反演的结果。

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