Indoor-positioning-system-based RSSI Kalman filtering method

Disclosed in the invention is an indoor-positioning-system-based received signal strength indication (RSSI) Kalman filtering method. The method comprises the following steps: step one, constructing a bluetooth Beacon environment of an indoor scene and establishing a signal strength map (SSMap); step two, selecting an actual measurement point, obtaining RSSI data from N bluetooth Beacons and storing the data into N channels; and step three, configuring a Kalman filter to carry out filtering processing on the received signal RSSI of the N channels. With the method, a defect that RSSI fluctuation dynamic ranges of all bluetooth Beacons received by a client are large due to the indoor electromagnetic environment influence can be overcome; and with control of the dynamic ranges of RSSI of all channels, the indoor positioning precision is effectively improved.