Water Salinity Sensing with UAV-Mounted IR-UWB Radar

被引:0
|
作者
Wang, Xiaocheng [1 ]
Fan, Guiyun [1 ]
Ding, Rong [1 ]
Jin, Haiming [1 ]
Hao, Wentian [2 ]
Tao, Mingyuan [2 ]
机构
[1] Shanghai Jiao Tong Univ, Dongchuan Rd 800, Shanghai 200240, Peoples R China
[2] Alibaba Grp, Damo Acad, Hangzhou 310000, Zhejiang, Peoples R China
关键词
Water salinity sensing; UAV; IR-UWB radar; deep learning; NETWORKS; RAMAN;
D O I
10.1145/3633515
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The quality of surface water is closely related to human's production and livelihood. Water salinity is one of the key indicators of water quality assessment. Recently, there has been an increased salinization problem of surface water in many regions of the world, making it necessary to timely monitor the salinity of surface water. Water salinity sensing could be challenging when it comes to surface water with complicated basin and tributaries, where existing methods fail to satisfy both efficiency and accuracy requirements. To address this problem, we propose a novel water salinity sensing system USalt, which leverages the high mobility of UAV and the contactless sensing ability of IR-UWB radar, and realizes fast and accurate water salinity sensing for surface water. Specifically, we design novel methods to eliminate the contamination in raw received radar signals and extract salinity-related features from radar signals. Furthermore, we adopt a neural network model ssNet to precisely estimate water salinity using the extracted features. To efficiently adapt ssNet to different environments, we customize meta learning and design a meta-learning framework mssNet. Extensive real-world experiments carried out by our UAV-based system illustrate that USalt can accurately sense the salinity of water with an MAE of 0.39 g/100 mL.
引用
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页数:37
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