摘要
在遥感测绘、爆炸场测试和物流安全等领域,往往需要高精度测量二维温度场信息。由于测量面积较大或者监测设备有限,经常导致温度场测试精度和分辨率较低。为此,本文结合压缩感知与分段Hermite插值理论提出一种二维温度场压缩重构方法。该方法首先对温度场进行随机欠采样;然后对采样结果进行分段Hermite插值以提高采样率;最后利用插值结果进行OMP高概率重构。该方法可以有效降低二维温度场测试的测量点数量。试验表明,在压缩率为75%情况下,二维温度场的重建误差不大于6.5%。
In the fields of remote sensing mapping,explosion field testing and logistics security,it is often necessary to measure two-dimensional temperature field information with high precision.Due to the large measurement area or limited monitoring equipment,temperature field measurement accuracy and resolution are often low.Therefore,this paper proposes a two-dimensional temperature field compression and reconstruction method combining compressive sensing and piecewise Hermite interpolation theory.Firstly,the temperature field is undersampled randomly.Secondly,the sampling results are interpolated by Hermite interpolation to improve the sampling rate.Finally,the interpolation results are used to reconstruct by OMP with high probability.This method can effectively reduce the number of measuring points in two-dimensional temperature field measurement.The experimental results indicate that the reconstruction error of two-dimensional temperature field is no more than 6.5%when the compression rate is 75%.
作者
许富景
杜少成
荆蕊蕊
Xu Fujing;Du Shaocheng;Jing Ruirui(School of Automation and Software Engineering,Shanxi University,Taiyuan 030013,China)
出处
《电子测量与仪器学报》
CSCD
北大核心
2022年第4期40-47,共8页
Journal of Electronic Measurement and Instrumentation
基金
国家自然科学基金(61903240)项目资助
关键词
温度场
压缩感知
随机采样
分段Hermite插值
temperature field
compressed sensing
random sampling
piecewise Hermite interpolation
作者简介
通信作者:许富景,2011年于中北大学获得学士学位,2016年于中北大学获得博士学位,现为山西大学副教授,主要研究方向为动态测控与智能仪器、智能物联网技术。E-mail:xufujing@126.com;杜少成,2020年于长安大学获得学士学位,现为山西大学研究生,主要研究方向为信息获取与信息处理。E-mail:dushaocheng2020@163.com;荆蕊蕊,2020年于山西大学获得学士学位,现为山西大学研究生,主要研究方向为复杂环境下煤层气储运安全评估技术研究。E-mail:jrrly0207@163.com
