Software Platform Development Of Accurate Indoor Location Finding System Based On Wireless Local Area Network

Along with the large-scale complex modern buildings appeared, such as Grand National Theatre, the Water Cube, Bird's Nest and so on, how to provide navigator fix service in the complex indoor environment, is a question demanding prompt solution. For indoor location, there are many research approaches, for instance infrared ray, ultrasonic, RFID, Bluetooth and so on. These technologies have the same deficiencies, e.g. complicated infrastructure, high costs, poor stability, short transmission distance, low accuracy. The mainly topic of our research is probing into the precise indoor location finding technology base on wireless local area network. This location finding technique utilizes the existing 802.11b Wireless Local Area Network infrastructure, and no additional hardware devices. This approach is different from other proposed solutions which require attaching a tag to the mobile devices, with low costs and high accuracy. It's a hotspot of indoor location finding techniques in present-day society. The goal of our article is to design and develop software platform of precise indoor location finding system based on wireless local area network. The primary coverage as follow: 1) Using C++ Builder 6.0 and SQL Server 2005 to develop the software platform of precise indoor location finding system based on wireless local area network, and establish the receive signal strength database; 2) Compare with other methods of signal extraction, lay heavy stress on analysis the method of signal extraction on the basis of Windows DDK; 3) Using MATLAB and SPSS to analysis the properties of indoor wireless electric wave; 4) Researching the approach of sample points classification in the receive signal strength database. For Windows XP operating system, this indoor location finding system can get relevant information of the wireless network card with disposable type. It is also able to set up the scanning frequency autonomously, realize sample data modeling in one hour, and feed back position coordinates of the mobile termination in ten seconds. The navigator fix result is to display by plane map. Furthermore, according to sample data analysis, we correct matching algorithm with indoor radiotransmission model, and classify sample points in the received signal strength database. Therefore the speed of response and precision for our indoor location finding system are both increased.