Application of Kalman Filter to Estimate Position of a Mobile Node in Indoor Environments

摘要

Indoor location estimation is an important problem for many emerging applications that involve networked embedded systems. We present an approach to estimate the location of a mobile node using a Kalman Filter. The system model comprises four anchor nodes and one or more mobile nodes. Each mobile node uses the average value of the received signal strength to each anchor node to estimate its position using an extended Kalman Filter. These data are fused with data from a local accelerometer to improve the estimate. We present experimental results to demonstrate the precision of our location estimates. In the future, this work can be extended to reduce the error in the location estimates.