Guidelines for Indoor Positioning

Indoor positioning is recognized as one of the upcoming major applications which can be used in wide variety of applications, such as indoor navigation and enterprise asset tracking. Some solutions are built upon standards, e.g. Wi-Fi, while others are proprietary. The purpose of this thesis is to evaluate state of the art solutions for indoor positioning as well as to develop guidelines when dierent solutions are appropriate to use. The scope of this thesis is to investigate on dierent indoor positioning technologies and their characteristics. Each solution has dierent pros and cons and it is important to understand for each technology. Other important aspects are the associated cost where the availability of open source alternatives are important concern as the IPR (Intellectual Property Rights) could become costly, etc. In this thesis we described a deep theoretical investigation on one passive solution for indoor positioning. The requirements, performance, cost, and complexity of UWB (Ultra-wideband) based indoor positioning system are described. On the other hand for active solutions, a user friendly prototype is developed for Wi-Fi based indoor positioning system in C# where a user can identify its position in indoor. However Wi-Fi received signal strength fluctuations over time introduce incorrect positioning. To minimize the impact of fluctuating of RSS values, Particle Filter has been developed with the prototype. A comparison regarding with and without Particle Filter for error performance is presented. Moreover we found calibration data in all directions while constructing a radio map can lead to better accuracy than calibration data in one direction. Finally based on requirements suitable technologies are suggested.Validerat; 20131106 (global_studentproject_submitter

Improving Wi-Fi based Indoor Positioning using Particle Filter based on Signal Strength

Indoor positioning is recognized as one of the upcoming major applications which can be used in wide variety of applications such as indoor navigation and enterprise asset tracking. The significance of localization in indoor environments have made the use of Wi-Fi based indoor positioning so that it can utilize available current wireless infrastructure and perform positioning very easily. In this paper we introduced a user friendly prototype for Wi-Fi based indoor positioning system where a user can identify its own position in indoor. Wi-Fi received signal strength (RSS) fluctuations over time introduce incorrect positioning To minimize the fluctuation of RSS, we developed Particle Filters with the prototype. A comparison between with and without Particle Filter for error performance is presented and at the same time it is also noticed that variation in number of particles could change the positioning accuracy. Moreover comparison between calibration data in all directions and in one direction while constructing a radio map is presented