A Bayesian Theory of Cooperative Calibration and Synchronization in Sensor Networks
A Bayesian Theory of Cooperative Calibration and Synchronization in Sensor Networks
复制标题
传感器网络中协同校准和同步的贝叶斯理论
DOI：
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发表时间：
2006
期刊：
影响因子：
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通讯作者：
Nobutaka Ono
中科院分区：
文献类型：
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作者：
S. Ando;Nobutaka Ono
提出了一种利用多个传感器间的局部重复测量值对网络化传感器进行标定的方法。在贝叶斯框架中，我们展示了用于最佳协作校准/同步的系统和过程由以下组成：1）偏移值和估计误差协方差矩阵的逆矩阵的对应列的传感器级维护（置信度矩阵），2）用重复测量的置信度增量更新耦合传感器的置信度矩阵元素，以及3-1）集中计算，用于将置信矩阵逆变换为估计误差协方差矩阵，以及传感器级计算，用于获得偏移值的更新估计，或者3-2）在所有传感器之间的更新估计的全局迭代计算。
This paper proposes a method for calibrating networked sensors from local duplicated measurements in couples of sensors among them. In the Bayesian framework, we show the system and procedure for the optimum collaborative calibration/synchronization is composed by: 1) sensor-wise maintenance of the offset values and a corresponding column of inverse of the estimation error covariance matrix (confidence matrix), 2) incremental updates of the confidence matrix elements for the coupled sensors with the confidence of the duplicated measurement, and 3-1) centralized computation for inverting the confidence matrix into the estimation error covariance matrix and sensor-wise computation for obtaining updated estimates of the offset values, or 3-2) global iterative computation of the updated estimates among all the sensors.