Adaptive VIRE indoor positioning algorithm based on Kriging interpolation

In traditional VIRE method, the linear interpolation is used to estimate the relationship between RSSI and distance, this increases the positioning error. Moreover, the label elimination threshold is a fixed value that is obtained by repeated adjustment experiments, this increases the time complexity of positioning. For these two problems, an adaptive VIRE indoor positioning algorithm is proposed based on Kriging interpolation. The Kriging interpolation is used to estimate the RSSI value of the virtual tag, and the threshold is automatically adjusted according to the real-time characteristics of the pending tag, so that the number of adjacent tags is nearly optimal, and the interference is more accurately eliminated, thereby the positioning coordinates are obtained. The experimental comparison results show that the algorithm not only saves the positioning cost, but also improves the positioning accuracy.