基于压缩感知的植物微环境及生理参数采集方法研究

发布时间：2018-03-30 16:50

本文选题：微环境及生理参数　切入点：数据采集　出处：《农业机械学报》2017年03期

【摘要】：在ARM平台上,设计了基于压缩感知的采集算法,极大地减少了数据存储量,提高了传输效率。分别选择离散傅里叶变换基(DFT)、离散余弦变换基(DCT)作为稀疏基,测试了该算法在2种基底下的工作性能。通过实验仿真分析,在相同稀疏度条件下,DCT具有更小的稀疏化误差,但是DFT具有更好的去噪效果、更低的观测维度和更高的数据压缩比;随着稀疏度的增大,两者的稀疏化误差减小,观测维度升高,数据压缩比降低。与此同时,还在ARM平台上测试了基于DFT压缩采集系统的压缩比和功耗,与常规植物微环境及生理参数监测系统相比,该系统的压缩比达到4.24,并能够节省13.62%的功耗。综上所述,基于压缩感知的植物微环境及生理参数采集方法由于数据压缩比高,在节省数据存储空间和降低数据传输量的同时,达到了降低系统功耗的目的,间接增强了系统的续航能力。
[Abstract]:In the ARM platform, the design of acquisition algorithm based on compressed sensing, greatly reducing the amount of data storage, improve the transmission efficiency. Respectively select discrete Fourier transform based discrete cosine transform (DFT), medium (DCT) as sparse basis and performance test of 2 kinds of base under the algorithm through simulation experiments. Analysis on the same sparsity conditions, sparse DCT has smaller error, but DFT has better denoising effect, observation of lower dimension and higher compression ratio; with the increase of sparsity, reduce the sparse error of the two observation dimension increased, the data compression ratio is reduced. At the same time, still ARM the test platform of DFT compression acquisition system and compression ratio based on power consumption, compared with the conventional micro environment and plant physiological parameters monitoring system, the system of the compression ratio reaches 4.24, and the power consumption can save 13.62%. In summary, based on Compressed sensing plant microenvironment and physiological parameters acquisition method, because of high data compression ratio, saves data storage space and reduces data transmission. Meanwhile, it achieves the purpose of reducing system power consumption and indirectly enhances the endurance of the system.

【作者单位】：北京林业大学工学院;北京林业大学城乡生态环境北京实验室;
【基金】：国家自然科学基金项目(31371537) 中央高校基本科研业务费专项资金项目(BLX2015-36) 北京市共建项目
【分类号】：S126;TP274.2

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