Design And Implementation Of RSSI Indoor Positioning Tracking Algorithm Based On Adaptive Kalman Filter

With the development of related technologies of the Internet of Things,the related services based on Location Based Service are increasing and showing a huge application market space.Compared with other indoor positioning technologies,the fingerprint based on RSSI can meets the positioning requirements of most occasions with the advantages of high positioning accuracy,low cost,low power consumption and high reliability.It has been widely used in the field of indoor positioning.However,the complex indoor environment makes the intensity of the RSSI signal fluctuate greatly,which seriously affects the accuracy and stability of the positioning.Therefore,whether the random error can be reduced and the impact of the indoor environment is reduced play an important role in improving the performance of the indoor location tracking algorithm.In this thesis,the RSSI indoor positioning and tracking algorithm based on adaptive Kalman filter is studied and improved.Due to the Kalman filter cannot update the state variables in time when the state of the pedestrian motion changes,the velocity variables and covariance parameters in the state variables cannot follow the actual state and cause inaccurate of Kalman gain which resulting in the final positioning tracking error.The angle change of the motion trajectory is analyzed with the application of the angle formula.Then updates the error covariance in real time according to the trajectory judgment result.The particle swarm optimization algorithm is used to solve the optimal value of the covariance and obtain the optimal estimation of the state.The initial value is provided by the fingerprint localization based on the hidden Markov model.The positioning system is realized in the range of 15m×10m based on CC2640.The experimental data shows that the average positioning error is within 2m,and the standard deviation of mean error is stable within 1m.The RSSI indoor positioning and tracking algorithm based on adaptive Kalman filter meets the design requirements in both function and performance,which can realize the trajectory tracking of indoor pedestrians.It has certain engineering application value for indoor positioning and tracking system using RSSI.