Research on RSSI/IMU Integrated Indoor Positioning System Based on Volumetric Kalman Filter
In the era of Internet of Things,tracking and locating objects in the indoor environment is very important.Aiming at the problem of large variance of received signal intensity indication(RSSI)location and cumulative error of Inertial measurement unit(IMU)location,a data fusion method for RSSI location and IMU location using volumetric Kalman filter algorithm was studied and implemented.Using the ZigBee development board as the hardware carrier of RSSI,the centroid positioning method is used to convert RSSI into coordinate information.The target to be tested is equipped with MPU9250 to provide IMU data and conduct indoor tracking and positioning experiments.Volume Kalman filter algorithm is used to improve the experimental data and compare with the original coordinate information data.The results show that the accuracy of the improved data after using the volumetric Kalman filter filter algorithm is 20.8%high-er than that of the original data.This positioning system has certain practical value.
NETL
NSTL
万方数据
维普
