Particle Methods for Indoor Tracking in WiFi Networks
This thesis treats the problem of positioning in WiFi networks and proposes a solution using hidden Markov models and particle lters based on sequential importance sampling with resampling. Hidden Markov models prove to be a powerful framework for this type of problem exhibiting both an intuitive and adaptive model structure. One of the diculties encountered when ltering this model is that it is i