Learning and Recovery Algorithms for Multi-Sensor Data Fusion and Spectral Unmixing in Earth Observation

地球观测中多传感器数据融合和光谱分解的学习和恢复算法

• 批准号: 273264444
• 负责人: Professor Dr. Massimo Fornasier
• 金额: --
• 依托单位: Lehrstuhl für Nachrichtentechnik (LNT)
• 依托单位国家: 德国
• 项目类别: Priority Programmes
• 财政年份: 2015
• 资助国家: 德国
• 起止时间: 2014-12-31 至 2021-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/273264444?language=en
• 关键词: Learning; Recovery; Algorithms; Multi; Sensor

This project will explore machine learning and recovery algorithms for multi-sensor data fusion and spectral unmixing signal processing in earth observation. The satellite signals are modeled as being encoded by distributed and non-linear compressed sensing, where the non-linearities arise due to quantization and/or measurement matrices that are data-dependent. The data will be obtained from German Aerospace Center (DLR) instruments.

该项目将探索用于对地观测中多传感器数据融合和光谱分解信号处理的机器学习和恢复算法。卫星信号被建模为由分布式和非线性压缩感知编码，其中非线性是由于依赖于数据的量化和/或测量矩阵而产生的。数据将从德国航空航天中心(DLR)仪器获得。