Research Of Indoor Positioning Based On The Bluetooth 4.0

In recent years,with the rapid development of science and technology,Location Based Services are becoming more and more popular,including navigation,consumer recommendation and so on.Global Positioning System has been able to achieve a high positioning accuracy outdoors,but it can't work well indoors.Therefore,indoor positioning has become a hot topic.This paper will study the indoor positioning.Indoor positioning refers to using wireless communication technology formats positioning system which monitors localization.Bluetooth 4.0 has the advantages of low power consumption,low cost,easily deploying and so on.This paper uses Bluetooth 4.0 technology as the way of positioning.The main work of this paper is as follows:In the second chapter,we firstly introduce three kinds of traditional wireless indoor positioning method and location fingerprint positioning method;Then,through the analysis of the collected signal strength value,kalman filtering is introduced to filter the signal strength value,and it is improved in determining whether the signal strength value is normal jump or not.This method can eliminate the noise in signal well,and lays the foundation for accurate positioning.In the third chapter,the static localization algorithm based on K nearest neighbor and adaptive bandwidth Mean Shift is proposed.In this method,the K nearest neighbor algorithm firstly is used to locate initially and generate the candidate coordinate set.Then,through adaptive bandwidth Mean Shift algorithm,the final position is located accurately.The validity of the algorithm is verified by experiments.In the fourth chapter,a dynamic tracking algorithm based on K nearest neighbor and kalman filtering is proposed.In this algorithm,the position coordinates of the initial point and other points in the trajectory are calculated by using velocity and acceleration.On the basis of this,the kalman filtering is used for dynamic positioning.The following three kinds of locomotion trajectories are respectively positioned by this method.That is,the relative time of the direction change and the direction unchanged is different,and the number of direction changes is fewer and more.The experimental results show the effectiveness of the proposed algorithm.In the fifth chapter,the full text is summarized,and the future work has been made a further prospect.