Abstract: Abstract: ZigBee indoor positioning technology has developed rapidly in recent years， but the traditional algorithm using fixed path loss model has poor adaptability to the environment， resulting in large positioning errors and affecting positioning accuracy. This paper proposes an indoor location algorithm based on ZigBee platform with dynamic correction of logarithmic path loss model parameters. First， the RSSI value obtained is filtered and optimized by Gaussian filtering， and then the parameters of the logarithmic path loss model are dynamically modified according to the distance between anchor nodes and the RSSI value， including the path loss factor and the signal strength value from the node to be measured， so the specific logarithmic path loss model in the current environment is obtained； Then the Kalman filter is used to modify the existing positioning parameters twice， which can correct the positioning deviation caused by the environment change caused by the time change in the above algorithm. Experimental results show that the positioning performance of this algorithm is 46.8% higher than that of the fixed path loss model based on ZigBee， which can improve the positioning error caused by environmental changes.

Key words: Key words: indoor positioning, ZigBee, Gaussian filtering, logarithmic path loss model, Kalman filtering