The beacons whose position have been known to receive the signal from the goal nodes and read out the Receive Signal Strange Indicator(RSSI),then look for its position the data table.

The coordinate system,which denotes the mobile robot s state and navigation space,is set up based on the RSSI potential field.

By analyzing the solutions of localization model and the environmental affects for RSSI(Received Signal Strength Indication),a localization algorithm based on RSSI practical measurement was provided.

No need of the accurate position and speed information of the mobile host,it takes into account the influence of velocity based on the history results of received signal strength measurements.

According to the moving speed and excursion angle, a threshold value of distance and received signal strength (RSS) is determined between mobile nodes (MNs) and the connecting AP.

A statistical learning technique named support vector regression was applied to the problem of indoor positioning based on the nonlinear and non-Gaussian statistical character of the received signal strength(RSS)in Wireless Local Area Networks.

With this interval mapping technique,an unknown node got the energy intervals through received signal strengths(RSS),and then determined which distance intervals of the transmission range it was located in from beacons.