Research On Mine Personnel Positioning Technology Based On WLAN And RFID Cooperation

With the continuous improvement of mine mining level and the development of the mine Internet of things,the existing underground personnel positioning technology has been unable to meet the daily production management requirements,especially when the safety accident occurs,whether the location information of the underground personnel can be accurately obtained in time is the key to carry out the rescue work.The underground laneway different from the ground,if directly transplant the existing indoor location method to the underground environment,it will cause low positioning accuracy and poor adaptability,therefore,it is meaningful to study the personnel positioning technology suitable for underground environment.Based on the analysis of the existing location methods,aiming at the WLAN location fingerprint matching as the core,the RFID cooperative fingerprint partition fast index of the underground personnel positioning technology is studied in the following three aspects.First,aiming at the huge workload and the fluctuation of sampling value,a database building method based on data preprocessing and piecewise linear Lagrange interpolation is proposed.The Gauss filter model filter out the small probability sampling value,and to store the location fingerprint database after calculating the mean value in the high probability interval,which effectively improves the accuracy of the sampling fingerprint;A piecewise linear Lagrange interpolation function is established based on the spatial attribute relation between reference points,based on the established propagation distance loss model of underground wireless signal,combined with some measured signal data,a complete position fingerprint library can build by interpolation calculation.The interpolation method is verified by experiments,which ensures the accuracy of fingerprint data,at the same location accuracy,it reduces at least 50% of the database workload.Secondly,in order to improve the positioning performance of WLAN fingerprint matching algorithm in the downhole environment,making full use of the statistical characteristics of the signal distribution in the environment,the fingerprint matching algorithm based on optimized Bayes is proposed.Using the weighted Euclidean distance formula to select the position reference point of the matching and improve the matching efficiency;Distance difference is used to represent the prior probability of target location at different reference points,which solves the problem that the prior probability of Bayes fingerprint matching algorithm is not reasonable.The experiments prove that the optimization algorithm can improve the positioning accuracy and reduce the occupancy of the matching resources.Finally,study the problem of matching algorithm traversing search in underground environment,which leads to large computation and low efficiency,analyze the feasibility of RFID aided fingerprint retrieval,propose a fast index mechanism of fingerprint partition based on RFID and WLAN.The laneway is divide into some sub regions,and the rule of regional decision for continuous positioning is given,the location of the laneway is first judge by the radio frequency induction,then quickly index the fingerprint data in the subregion to complete the matching location.Simulation experiments show that the average single positioning time is reduce by 53.8% after the fast indexing of zoning,which greatly improves the location response speed.