RSSI-Based Indoor Mobile Localization in Wireless Sensor Network
Location techniques play an important part in wireless sensor network. The Received Signal Strength Indicator (RSSI) based localization is a promising technique since it requires relatively low configuration and energy. The received signal strength is mainly influenced by propagation environment in wireless sensor network. So, the authors proposed an Indoor Mobile Location Algorithm (IMLA). They firstly introduce a signal propagation model. And then they employ the least squares and maximum likelihood estimation to estimate the parameters of signal model. Finally the extended Kalman filter is used to filter the RSSI values and convert the measured RSS value to distance.