基于压缩感知的定向遥感理论研究

项目名称： 基于压缩感知的定向遥感理论研究

项目编号： No.41461082

项目类型： 地区科学基金项目

立项/批准年度： 2015

项目学科： 天文学、地球科学

项目作者： 程涛

作者单位： 广西科技大学

项目金额： 44万元

中文摘要： 由于地表变化区域的不确定性和不可预知性，很难定向采集数据。传统的面向全域的数据采集又会导致对非变化区域的重复工作和资源资金等的严重浪费。基于变化区域的稀疏假设，可采用压缩感知理论研究变化区域的定向遥感问题。不同时相压缩感知测量数据的差值可用于无损重构变化区域，所需数据量仅为变化区域数据量的3倍。本研究拟基于线阵推扫模式，以理想情况下的定向遥感为研究对象，通过理论分析、数学证明和实验验证初步解决定向遥感的基础理论问题。为将来定向遥感的工业应用研究奠定基础。本研究拟充分利用变化区域时空连续性和结构等先验信息，从二维的角度开展约束等向性、优化矩阵重构性能、测量矩阵设计和新型重构算法的理论和实验研究。最终实现海量测量数据的高效采集和重构。本研究不仅为遥感影像的采集和更新提供新的理论和技术，还为压缩感知研究开辟新的领域。因此，本研究不但具有极大的理论价值，而且具有广阔的工程应用前景和巨大的经济价值。

中文关键词： 定向遥感；压缩感知；约束等向性；测量矩阵设计；结构先验信息

英文摘要： It's very difficult to sample change area data directionally due to uncertainty and unpredictability of sampling objects. Conventional data collecting of entire zone leads to repeat work towards unchanged areas so that capital and resource are wasted. Compressive sensing (CS) theory can be used properly in directional remote sensing research of urban change area by virtue of the sparsity hypothesis of change area. It has been demonstrated in our early experiments that change area can be reconstructed losslessly by 3 times as much as its data based on the difference of unlike temporal CS measurement values. This study would solve primarily the basic theory problem of directional remote sensing through theoretical analysis, mathematical proof and experimental validation based on linear push-broom mode and the directional remote sensing ideally as the object of study. It lays the foundation for the future industrial application of directional sensing. In order to use change areas' prior information such as spatio-temporal continuity and structure, restricted direction property, reconstruction ability of optimal matrix, design of measurement matrix and novel reconstruction algorithm are studied by theory and experiment from two-dimension. Efficient acquisition and reconstruction of the massive measurement data would be implemented at last. This study not only provides a new theory and technology for remote sensing image acquisition and update, but also opens up new field for the research on compressed sensing. Therefore, the study, in addition to the great theoretical value, but also had a broad engineering application prospect and great economic value.

英文关键词： directional remote sensing;compressive sensing;restricted direction property;design of measurement matrix;structure prior information