Date Added: Nov 2009
Wireless sensor networks are well suited for tracking targets carrying RFID tags in indoor environments. Tracking based on the Received Signal Strength Indication (RSSI) is by far the cheapest and simplest option, but suffers from secular biases due to effects of multi-path, occlusions and decalibration, as well as large unbiased errors due to measurement noise. The authors propose a novel algorithm that solves these problems in a distributed, scalable and power-efficient manner. Firstly, their proposal includes a tandem incremental estimator that learns and tracks the radio environment of the network, and provides this knowledge for the use of the tracking algorithm, which eliminates the secular biases due to radio occlusions etc.