Research And Implementation Of Positioning Algorithm Based On Positioning Terminal And Acceleration Sensor

In recent years,with the development of the era of network information,the performance of the sensor has been greatly excavated,the wide application of indoor positioning has been widely concerned by domestic and foreign scholars,and at present,Bluetooth-based indoor positioning algorithm is generally less accurate,The location of the jump,high cost,deployment and maintenance problems,Bluetooth positioning terminal by the human block,shadow fading,multipath effect,resulting in the final 10 m target is always out of reach,in view of this,this paper in the summary of Bluetooth Signal propagation model,directional angle ranging model,Euclidean distance weighting model,antenna array configuration model and sensor performance index.Based on the RSSI indoor positioning algorithm,the main work is as follows:In the offline stage,a fingerprint mapping algorithm combining LSM303 DLHC sensor is proposed.The LSM303 DLHC acceleration sensor is integrated into the nRF51822 positioning terminal.The real-time position of the positioning terminal is measured by the sensor and the real-time signal strength RSSI of the acquisition terminal is surveyed by the Bluetooth AP node.Will be collected RSSI,MAC address,terminal orientation and other information clustering,and design an APP link server PgAdmin database,to be positioned in the room to specify the location of the coordinates of the Bluetooth beacon node launched RSSI clustering average Will be through the APP all the data information pushed to the database,the formation of offline fingerprint library.In the positioning stage,a positioning algorithm based on antenna AOA and RSSI is proposed.A Bluetooth-based positioning base station based on antenna array is designed.The base station adopts pulse rotation amplitude measurement instead of pulse arrival time difference measurement.By directional pattern and RSSI When the positioning terminal enters the coverage area of the Bluetooth beacon node,the different beacon nodes receive the real-time vector(terminal MAC address,RSSI mean value,AOA value,and the AOA value)at the time point when the anchor node reaches the AOA.Time frame),the real-time vector is matched with the data in the fingerprint database.AOA matches the angle of real-time survey in the fingerprint stage,and the fingerprint entry with the strongest real-time vector and the strongest AP node threshold is selected.Real-time vector and Euclidean distance of these fingerprint vectors,the Euclidean distance is integrated into the corresponding weight coefficient.After normalizing the weight,the coordinate point and the weight are weighted to obtain the final coordinate point.Firstly,the validity of the experiment is proved by simulation experiments.Then,the algorithm is arranged in the exhibition environment and compared with the classical localization algorithm.The experimental results show that the algorithm has high precision and developed the positioning system Easy to deploy,easy to maintain,with a high promotional value.