Center for Embedded Network Sensing

Numerous factors contribute to errors in sensor measure- ments. In order to be useful, any sensor device must be calibrated to adjust its accuracy against the expected measurement scale. In large- scale sensor networks, calibration will be an exceptionally dicult task since sensor nodes are often not easily accessible and manual device-by- device calibration is intractable. In this paper, we present a two-phase post-deployment calibration technique for large-scale, dense sensor de- ployments. In its �rst phase, the algorithm derives relative calibration relationships between pairs of co-located sensors, while in the second phase, it maximizes the consistency of the pair-wise calibration func- tions among groups of sensor nodes. The key idea in the �rst phase is to use temporal correlation of signals received at neighboring sensors when the signals are highly correlated (i.e. sensors are observing the same phenomenon) to derive the function relating their bias in amplitude. We formulate the second phase as an optimization problem and present an algorithm suitable for localized implementation. We evaluate the perfor- mance of the �rst phase of the algorithm using empirical and simulated data.