Research And Implementation Of Indoor Positioning System Based On Wireless Signals

Pervasively deployed wireless local network(WLAN) has made indoor positioning system based on wireless signals got focused widely. Kalman Filter is one of the most commonly used optimal estimation algorithms in indoor positioning field to do system states estimation. However, Kalman Filter only adopts to linear system. The observation model or equation, which describes the relation between signal measurements and positions of mobile unit, is not linear due to those special features in indoor environment, such as small size of area, much non-line of sight area, random changes of signal channel state and unpredictable moving directions or velocities of mobile unit.Moreover, in order to meet large demands of indoor positioning service, service providers should be able to develop, deploy and update systems following progress of market and technology rapidly. This requires those systems have a well-designed extension mechanism. Unfortunately, there are no published papers discussing software extension mechanisms for indoor positioning system so far.Therefore, this dissertation focuses on two points:1. Applying Extended Kalman Filter to indoor positioning system based on wireless signals. Extended Kalman Filter is an extension of Kalman Filter to non-linear situations. One indoor positioning system supporting two positioning methods(Time of Arrival and Received Signal Strength) is developed in this dissertation. The system is coded by C++ and uses EKF as its core estimation algorithm. Before passed to EKF algorithm to do positioning task, received measurements are taken in two preprocessing steps: Non-line of Sight Measurements Detection and Noise Mitigation. Due to the resources limitation, only RSS method is tested in this dissertation. Mean deviation error of positioning results is 5.99 meters.2. Designing a software extension mechanism for indoor positioning system. Drawbacks of indoor positioning systems which lack of software extensibility were concluded firstly. Then, summarizing and subtracting the common procedures of indoor positioning systems were done. Finally, Configurable Filter and Process software extension mechanism is designed referring to packages filtering mechanism in network routing area, Open Service Gateway, Component Object Model and Process Definition Language Based on Extensive Markup Language.Refactoring of developed system was implemented according to the designed CFP mechanism. Analysis of refactored system shows that CFP enables: dynamically create, remove, modify relations between measurements and positioning methods; dynamically add and remove activities in positioning process; dynamically modify the sequence of activities in positioning process. All those activities are operated dynamically without re-coding, re-compiling, re-deploying whole system.