Auto calibration in drift aware wireless sensor networks using the interacting multiple model algorithm

The purpose for wireless sensor networks is to deploy low cost sensors with sufficient computing and communication capabilities to support networked sensing applications. The emphasis on lower cost led to sensors that are less accurate and less reliable than their wired sensor counterparts. Sensors usually suffer from both random and systematic bias problems. Even when the sensors are properly calibrated at the time of their deployment, they develop drift in their readings leading to biased sensor measurements. The drift in this context is defined as a unidirectional long-term change in the sensor measurement. Assuming that neighboring sensors have correlated measurements and noting that the instantiation of drift in a sensor is uncorrelated with other sensors, we present the methodology for detecting and correcting sensors smooth and steep drifts. The methodology improves the reliability and the effective life of the network.