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首页> 外文会议>Information Sciences and Systems, 2009. CISS 2009 >Using field data to design a sensor network
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Using field data to design a sensor network

机译：使用现场数据设计传感器网络

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Distributed sensing and data acquisition in field applications is a labor intensive and expensive process. In such applications, measurements need to be performed in thousands of points. To design a sensor network for soil moisture measurement, we introduce a two step design procedure; in the first step, the data of soil moisture experiments known as SMEX03 (in Little Washita watershed, Oklahoma) is used to approximate the spatial variability of moisture data. Based on the numerical data of SMEX03, the spatial correlation of soil moisture is approximated. Our numerical analysis shows that the spatial correlation of moisture measurements of two points behaves similar to an exponentially decaying function of the distance of those points. The analysis also shows that the moisture measurements for the points with distance up to 150m show a high correlation, while the spatial correlation is practically zero for points that are more than 400 m apart. In the second step, we use the spatial correlation of soil moisture to design a sensor network. It is assumed that the sensors are placed sparsely in the field, but it is desirable to estimate the soil moisture at any arbitrary point of the field based on the measurements of the nearby sensors. We use a linear estimator, and give the coefficients that minimize its variance. The value of the minimum variance of the linear estimator depends on the location. We give a closed form formula for the coefficients of the linear minimum variance estimator and the upper bound for the its variance as a function of spatial separation of sensors. Assuming a known value for the maximum allowable moisture estimation variance, we find the optimal placement of the sensors. The results show that in a grid like placement of the sensors in the field, with average separation of distance of 50-100 m between neighboring sensor pairs, the soil moisture can be approximated with a good accuracy at any arbitrary point of the field, while increasing the -ndistance of neighboring senors beyond 200 m degrades the performance significantly.
机译：现场应用中的分布式传感和数据采集是劳动密集型且昂贵的过程。在此类应用中，需要在数千个点中执行测量。为了设计用于土壤水分测量的传感器网络，我们引入了一个两步设计程序。第一步，使用土壤水分实验数据SMEX03（位于俄克拉何马州Little Washita流域）来近似估算水分数据的空间变异性。根据SMEX03的数值数据，可以估算出土壤水分的空间相关性。我们的数值分析表明，两个点的湿度测量值的空间相关性表现得与这些点的距离的指数衰减函数相似。分析还表明，距离最大为150m的点的湿度测量值显示出高度相关性，而相距超过400 m的点的空间相关性实际上为零。在第二步中，我们使用土壤水分的空间相关性来设计传感器网络。假定传感器稀疏地放置在田野中，但是希望基于附近传感器的测量值来估计田野中任意点的土壤湿度。我们使用线性估计量，并给出最小化其方差的系数。线性估算器的最小方差值取决于位置。我们给出了线性最小方差估计量的系数及其方差的上限的封闭形式公式，该系数是传感器空间间隔的函数。假定最大允许湿度估计方差的已知值，我们找到传感器的最佳位置。结果表明，在类似传感器放置在网格中的网格中，相邻传感器对之间的平均距离为50-100 m，可以在该区域的任意点以良好的精度近似估算土壤湿度，而如果将相邻传感器的距离增加到200 m以上，则会大大降低性能。

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