An RSSI-Based MAP Localization Method with Channel Parameters Estimation in Wireless Sensor Networks

This paper proposes a received signal strength indicator (RSSI)-based maximum a posteriori (MAP) localization method with channel parameters estimation in wireless sensor networks. The proposed method makes use of not only likelihood value of the location of a target but also a priori knowledge of the target location. Furthermore, the proposed method also estimates channel model parameters with an maximum likelihood (ML) estimation technique, therefore, it can be realized with no troublesome pre-measurement on the channel parameters. Our theoretical analyses and experimental results demonstrate that the proposed MAP location estimation method is superior to a conventional ML location estimation method in term of location estimation accuracy.