Indoor RSSI Trilateral Algorithm Considering Piecewise and Space-Scene

Indoor positioning methods based on RSSI-distance mapping were mass used for less surveying or mapping preparations or seldom additional devices, while the bottleneck is stability, complexity and less positioning accuracy. An optimization method aimed at this problem considering piecewise transmission model and indoor space-scene is proposed in this paper. Firstly, based on the collected RF signals, a piecewise fitting model for RF is constructed with Matlab fitting tool, and then a piecewise characteristic constraint factor and its value sets is proposed as constraint Factor for filtering RSSI value. Secondly, based on the space scene characteristics classification for pedestrian space scene, an accuracy constraint is proposed as goal position precognition. On these basis, an model for optimizing indoor RSSI Trilateration is proposed binding real-time RSSI filtering Factor and target space presetting constraint. Comparative experiments show that the proposed positioning algorithm has higher accuracy and significant stability. And in one more 20 square meter indoor space scene, experimental results show having reached less 1 meter accuracy and 100% optimized.