上海航天（中英文）2026，Vol.43Issue(1)：42-53,62,13.DOI:10.19328/j.cnki.2096-8655.2026.01.004
赋能空天海洋遥感:基于声学信道状态信息与人工智能算法的众包盐度感知技术
Enabling Spaceborne Ocean Remote Sensing:An Acoustic CSI-based Crowdsourced Salinity Sensing Technology
摘要
Abstract
Addressing the limitation of insufficient spatial resolution in space-based ocean remote sensing satellites and their heavy reliance on sparse and high-cost in-situ ground truth data for calibration,this paper proposes a smartphone-enabled salinity detection technique based on acoustic channel state information(CSI).The method leverages the propagation characteristics of acoustic waves in liquids.With proper designedorthogonal frequency division multiplexing(OFDM)signals,both the amplitude and phase features of the acoustic CSI are extracted and analyzed,enabling non-contact salinity measurement.The feasibility of constructing a high-density and low-cost nearshore salinity ground truth network is analyzed,and experimental validation under various salinity levels and environmental conditions is conducted.The analysis based on laboratory scenarios demonstrates that the method achieves excellent separation for eight distinct salinity levels with intervals of 5‰.By leveraging the widespread prevalence of smartphones,this salinity detection approach can potentially establish a'capillary-level'ground observation network through a crowdsourcing model.This network could provide massivereal-time calibration and validation support for ocean salinity satellites,offering a potential technical pathway to alleviate the current bottleneck of'sufficient space-borne capacity but inadequate ground-based data'and meet the closed-loop requirements of a'space-ground collaborative'ocean salinity remote sensing system.关键词
海洋遥感/盐度检测/信道状态信息(CSI)/智能手机传感/地面真值/天地协同/众包监测Key words
ocean remote sensing/salinity detection/channel state information(CSI)/smartphone sensing/ground truth/space-ground collaboration/crowdsourced monitoring分类
航空航天引用本文复制引用
董润扬,刘海峰,薛广涛,陈潜,杨岚青,马融..赋能空天海洋遥感:基于声学信道状态信息与人工智能算法的众包盐度感知技术[J].上海航天（中英文）,2026,43(1):42-53,62,13.基金项目
上海市"科技创新行动计划"自然科学基金面上资助项目(24ZR1439100) （24ZR1439100）
