小波变换与滑动窗口相结合的GNSS-IR雪深估测模型

doi:10.11947/j.AGCS.2020.20200268

测绘学报 ›› 2020, Vol. 49 ›› Issue (9): 1179-1188.doi: 10.11947/j.AGCS.2020.20200268

小波变换与滑动窗口相结合的GNSS-IR雪深估测模型

边少锋¹, 周威¹, 刘立龙^2,3, 李厚朴¹, 刘备¹

1. 海军工程大学导航工程系, 湖北武汉 430079;
2. 桂林理工大学测绘地理信息学院, 广西桂林 541004;
3. 广西空间信息与测绘重点实验室, 广西桂林 541004

收稿日期:2020-06-24 修回日期:2020-08-23 发布日期:2020-09-19
通讯作者: 周威 E-mail:boy123455@126.com
作者简介:边少锋(1961-),男,博士,教授,研究方向为大地测量学。E-mail:sfbian@sina.com
基金资助:
国家自然科学基金（41631072； 41971416）；海军工程大学自主立项项目（2019055）；广西空间信息与测绘重点实验室开放基金（19-050-11-02）；湖北省杰出青年科学基金（2019CFA086）；广西自然科学基金（2018GXNSFAA294045）

GNSS-IR model of snow depth estimation combining wavelet transform with sliding window

BIAN Shaofeng¹, ZHOU Wei¹, LIU Lilong^2,3, LI Houpu¹, LIU Bei¹

1. Department of Navigation Engineering, Naval University of Engineering, Wuhan 430079, China;
2. College of Geomatics and Geoinformation, Guilin University of Technology, Guilin 541004, China;
3. Guangxi Key Laboratory of Spatial Information and Geomatics, Guilin 541004, China

Received:2020-06-24 Revised:2020-08-23 Published:2020-09-19
Supported by:
The National Natural Science Foundation of China (Nos. 41631072;41971416);The Independent Project of Naval University of Engineering (No. 2019055);The Open Fund of Guangxi Key Laboratory of Spatial Information and Geomatics (No. 19-050-11-02);The Natural Science Foundation for Distinguished Young Scholars of Hubei Province of China (No. 2019CFA086);The Guangxi Natural Science Foundation of China (No. 2018GXNSFAA294045)

摘要/Abstract

摘要： GNSS干涉反射技术（GNSS interferometric reflectometry）是一种新型的地表雪深监测方式。针对当前信号分离不佳和随机估测偏差的问题，提出联合小波变换和滑动窗口构建一种多卫星融合的GNSS-IR雪深估测精化模型。该模型采用离散小波变换代替常用的多项式方法，获取高质量的信噪比序列。通过利用阈值约束下的滑动窗口筛选多卫星有效反射高度，并进行等权平均。以PBO H₂O和SNOTEL的雪深数据为参考值，利用2016—2017年雪季的GNSS观测数据建立模型并验证精度。结果表明：①GNSS-IR精化模型估测结果与实测数据在整体趋势上保持高一致性；②与单颗卫星结果相比，多卫星融合估测结果在精度和稳定性方面明显改善，其均方根误差（RMSE）为10 cm，相较于PBO H₂O减少了近50%。此外，考虑到地表粗糙度作为一种误差影响因素，采用新的反射高度基准修正的雪深估测相对RMSE误差约4 cm，同时估测值与实际值的相关系数达到0.98。

关键词: 全球卫星导航系统干涉反射技术, 小波变换, 滑动窗口, 雪深估测, 地表粗糙度

Abstract: Currently, GNSS interferometric reflectometry technology has become a high-precision method for monitoring land surface snow depth. Aiming at the problems of signal separation and random estimation biases, we developed a GNSS-IR refined model with multi-satellite fusion for snow depth estimation combining wavelet transform with sliding window. The common polynomial method was replaced by discrete wavelet transform to obtain the high-quality SNR sequences of the reflected signals which can calculate the reflected height of GPS antenna. Then, these reflected heights from SNR observations of multi-satellite were effectively selected and averaged using the sliding window under a constrained threshold. The refined model was established using GNSS observations for snow season from 2016 to 2017, and then the snow depth datasets of both PBO H₂O and SNOTEL were regarded as reference to verify the performance of the refined model. The results show that there is a high agreement between snow depths derived from the refined model and in situ measurements, and the RMSE is 10 cm. Compared with the results of a single satellite, the accuracy and the stability of the refined model with multi-satellite fusion are obviously better. In terms of RMSE, the accuracy of the refined model has been improved by 50% when compared with PBO H₂O dataset. In addition, taking into consideration that land surface roughness is an error factor, a relative RMSE value of snow depth estimations corrected by a new datum of the reflection height is approximately 4 cm, and the correlation coefficient between snow depth estimations and in situ measurements reaches 0.98.

Key words: global navigation satellite system interferometric reflectometry, wavelet transform, sliding window, snow depth estimation, land surface roughness

中图分类号:

P228

边少锋, 周威, 刘立龙, 李厚朴, 刘备. 小波变换与滑动窗口相结合的GNSS-IR雪深估测模型[J]. 测绘学报, 2020, 49(9): 1179-1188.

BIAN Shaofeng, ZHOU Wei, LIU Lilong, LI Houpu, LIU Bei. GNSS-IR model of snow depth estimation combining wavelet transform with sliding window[J]. Acta Geodaetica et Cartographica Sinica, 2020, 49(9): 1179-1188.

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小波变换与滑动窗口相结合的GNSS-IR雪深估测模型

GNSS-IR model of snow depth estimation combining wavelet transform with sliding window

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