一个基于近邻距离的定向算法,用于从浅水中的太空光子计数LiDAR中提取信号光子
Shibin Zhao1,2,3,4, Zhenwei Shi1,2,3, Tingting Jin1,2,3
1Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China.
Sensors (Basel, Switzerland)
|March 14, 2026
概括
一个新的基于距离的DNNDA (Directional Nearest Neighbor Distance-based Algorithm) 有效地消除了冰,云和陆地高度卫星-2 (ICESat-2) 光子数据中的噪声. 这种方法通过在噪音条件下改善海底信号提取来增强浅水浴度.
科学领域:
- 地理空间科学是一个科学领域.
- 海洋学 海洋学 海洋学
- 遥感是一种远程传感.
背景情况:
- 使用ICESat-2数据的卫星衍生的浴度测量对浅水有希望,因为它的532nm激光.
- 由于太阳背景和仪器噪声,对光子计数数据的有效消极是至关重要的.
- 现有的无声化方法在高噪音环境中扎.
研究的目的:
- 为ICESat-2浅水数据提出一种新的光子消噪算法 (DNNDA).
- 从杂的ICESat-2数据中强大提取海底信号光子.
- 为了提高卫星衍生浴度的准确性.
主要方法:
- 开发了基于距离的方向近邻算法 (DNNDA).
- DNNDA利用了调整尺度的空间关系和定向光子分布.
- 将方向特征纳入密度表示中,以增强信号光子对比度.
主要成果:
- 在全球ICESat-2数据集上,DNNDA实现了卓越的海底光子提取,F1得分超过95%.
- 对CUDEM数据的回归分析显示,平方根平均误差低于0.57m.
- 该算法使用设计的评估指数自动确定最佳参数.
结论:
- 在复杂的,高噪音环境中,DNNDA为浅水浴度提供了强大的解决方案.
- 该方法可在本地和全球范围内实现可靠和适应的信号光子提取.
- 通过考虑定向光子特性,DNNDA克服了现有方法的局限性.
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