Optimization of Indoor Bluetooth Ranging Model Based on RSSI

Abstract

Because the received signal strength indication (RSSI) ranging technology has problems with line-of-sight and multipath effects in indoor environments, the actual received RSSI value is unstable. In order to reduce the influence of RSSI value volatility on ranging accuracy, according to the fluctuation characteristics of the signal itself, a combined filtering method of Gaussian, median and mean is proposed to process the collected RSSI values, and the least squares method is used to fit and optimize the ranging parameter. Experiments show that using the RSSI intensity value processed by the combined filtering method to establish a model to achieve ranging, the maximum absolute error is about 2 m, and the absolute average error is about 0.763 m. The accuracy of the ranging has been significantly improved, and the ranging model has been optimized.