Design And Implementation Of Indoor Positioning System

With the continuous development of positioning technology, especially wireless location technology becomes more and more mature, and based on location-based services (LBS) has become popular in the modern communication technology, a series of development brought to positioning system research and attention. More and more large indoor places for indoor positioning system has a relatively strong demand, and geographic location can be described is one of the important foundation of human behavior and indoor environment is day of activity time the place for a long time, so if you can the indoor location information and user data, user information successfully to combine, indoor positioning system based on position information also must have a very broad application prospects.Through the study of the special factors of indoor environment, this paper decided to use the WiFi signal strength based fingerprint positioning technology. In order to further improve the accuracy of the fingerprint positioning system to consider the indoor map with vector representation of the cover part of the consideration. To achieve a by layout of the indoor environment, such as walls, doors, corridor effect of state transfer probability based on post test probability adaptive grid set selection mechanism of indoor positioning system, and the combination of indoor maps of the vector scalar results show. The results of the experiments show that the system can be considered as a whole, and some errors can be eliminated more accurately.In this paper on the existing research on indoor positioning system based on for the system structure and the main location algorithm in the cause of the problem proposed improvements to existing systems including the upper vector of indoor maps covering analysis, use and correction of the core model of system positioning. This system has mainly taken by matching the fingerprint database by WiFi signal strength (RSSI) to establish the fingerprint information in real time to estimate the user’s location, according to the function is divided into two stages of discussion and implementation. The first is the off-line phase, the collection module collects the position information into the data processing module, then the fingerprint can be stored in the data storage module to establish the fingerprint database. Followed by the online stage, real time collection module to collect user WiFi signal strength information, location fingerprint module according to the model of the location fingerprint matching position estimation, the module of positioning results show.