基于压缩感知地质灾害监测系统研究

Research on and Monitoring System of Geological Disaster Based on Compress Sensing

对各类地质灾害产生的监测一直是我国研究的主要方向和内容。目前我国已将无线传感网络应用于地质灾害的监测过程中,通过信息采集以及实时监测,降低损失。然而,在监测系统中,存在数据传输量大和功率损耗大的问题。压缩感知作为新兴的理论,收到广大研究人员的关注。该文在前人算法研究基础上,通过对压缩感知理论和重构算法的分析研究,提出基于自适应子空间追踪算法,通过逐次增加迭代向量,进行小范围数据更替,实现了稀疏度的预估计。仿真实验证明,该文算法能够较精确的重构复杂的原始信号。在保证算法精度的同时,减少数据冗余,加快传输效率。

The monitoring of various types of geological disasters has always been the main direction and content of our research.At present,China has wireless sensor network used in the monitoring process of geological disasters,through information collection and real-time monitoring,reduce losses.However,in the monitoring system,there is a problem that the data transmission amount is large and the power loss is large.Compressed perception as a new theory,received the attention of the majority of researchers.Based on the research of predecessor algorithm,this paper proposes an adaptive subspace tracking algorithm Based on the analysis of compression perception theory and reconstruction algorithm.By increasing the iterative vector successively,the small-scale data replacement is carried out to realize the prediction of sparseness The The simulation results show that the proposed algorithm can reconstruct the complex original signal accurately,reduce the data redundancy and speed up the transmission efficiency while ensuring the accuracy of the algorithm.