Research On Indoor Localization Algorithm Of IoT Based On BLE5.0 Technology

With the continuous iterative update of intelligent surveying and mapping geographic information technology and Internet of things(IOT)wireless sensor network(WSN)technology,location based services(LBS)based on IOT technology has been widely concerned.As one of the landing application technologies of location-based service,indoor positioning accuracy depends on the complexity of indoor environment.Among many indoor positioning technologies,low-power Bluetooth(ble)technology has the advantages of large bandwidth and long communication distance,which makes low-cost and high-precision ble indoor positioning a reality.BLE indoor positioning technology based on received signal strength indication(RSSI)has some problems in practical application,such as RSSI ranging accuracy is not enough and positioning algorithm is not perfect.(1)To solve the problem of RSSI ranging accuracy,a BLE signal optimization algorithm and a dynamic updating algorithm of log path loss model parameters are studied.Considering the advantages of common filtering algorithms,a hybrid filtering model is established to process BLE signal strength,so as to obtain more stable RSSI value;At the same time,an optimization algorithm is designed for the RSSI ranging model parameter path loss factor and the reference path loss between anchor nodes,which can quickly get the model parameters suitable for the current environment,so as to improve the RSSI ranging accuracy and lay the foundation for the subsequent accurate BLE positioning.(2)In the BLE positioning stage,the current solutions often sample weighted centroid positioning,least square positioning or fingerprint positioning algorithm,but do not consider the impact of the weight matrix error on the positioning results.In view of the imperfection of the above algorithm,a weighted method based on pseudo range difference is introduced in the least square positioning on the basis of more accurate ranging information,which effectively reduces the weight matrix error caused by the parameter error of logarithmic path loss model.(3)In this paper,an improved particle filter algorithm is used to correct the Gauss Newton positioning error.According to the number of effective particles,the optimal number of particles in the current environment is determined for filtering operation,and the waste of computing resources can be effectively reduced by dynamically updating the number of particles;In order to solve the problem of filter degradation,the layered resampling method is used to filter particles in the filtering process,so as to improve the calculation efficiency of target point coordinates.The accuracy of the indoor location algorithm based on Low Power Bluetooth RSSI is improved by 12.5%,which has a certain reference value for the follow-up study of BLE indoor location algorithm.