The Research And Application Of Indoor Positioning Algorithm Based On WLAN Location Fingerprint

With the extensive application of wireless communication technology and intelligent terminal,applications of location based service(LBS)have been extended from outdoor to indoor gradually.Because indoor WLAN deployment is extensive and mobile terminal is easy to receive signal strength,the fingerprinting positioning algorithm in WLAN has gained the attention of domestic and foreign scholars.The performance of RSS-based technology,however,is usually instability due to two major reasons,that is: the RSS signal time-varying,and different terminal signal receiving ability.In order to handle such performance issue of RSS-based WLAN fingerprint positioning,we propose a novel algorithm based on the linearly dependent of RSS space.Furthermore,the fingerprint algorithm is optimized.Finally,we develop a set of indoor positioning systems.The main work and creative points of this dissertation are listed as follows.(1)Due to RSS signal time-varying and difference of signal receiving ability of different terminals,the performance of RSS-based technologies is usually instability.In order to handle such problem,a novel fingerprint localization algorithm based on the linear spatial dependence of RSS was proposed.Multiple sets of RSS samples were collected at each reference point to form a feature matrix and an offline location fingerprint database was conducted.When the real-time RSS matrix was used to calculate the correlation between the real-time RSS matrix and the reference point of the fingerprint library,the k-reference points were obtained,and the final position of the user was calculated by the quadratic weighted centroid algorithm.In order to effectively reduce the influence of signal time-varying,the sampling and sorting process were carried out,and the number of sampling times was increased as much as possible when constructing the offline fingerprint database,but the samples needed to be aggregated to fit the positioning correlation calculation.(2)To decrease the computation overhead in location matching calculation process,we propose a location fingerprint clustering method.It takes RSS characteristic matrix as clustering sample,makes use of related coefficients as similarity metrics and divides fingerprint database into relatively small fingerprint sub-library through K-means clustering method.During matching computation,it hasadopted dynamic screening strategy to judge fingerprint sub-library and estimated the final location through matching the selected fingerprint sub-library.In this way,it can decrease the fingerprint searching space in matching computation process and improve the efficiency of location system.(3)Different AP layouts will have different influence on location performance.We have taken the maximization of fingerprint segmentation at reference point as the aim and proposed an AP layout planning reference scheme.It has taken the sum of distance between reference point and Euclidean distance of adjacent reference point as fingerprint segmentation of reference point,defined the sum of finger segmentation of all reference points as current AP layout segmentation degree SD,taken the SD maximization as condition to arrange the AP location,in this way,it can improve the location accuracy of the system effectively.