Kalman filter with a linear state model for PDR+WLAN positioning and its application to assisting a particle filter
Research output: Contribution to journal › Article › Scientific › peer-review
|Journal||Eurasip Journal on Advances in Signal Processing|
|Publication status||Published - 1 Dec 2015|
|Publication type||A1 Journal article-refereed|
Indoor positioning based on wireless local area network (WLAN) signals is often enhanced using pedestrian dead reckoning (PDR) based on an inertial measurement unit. The state evolution model in PDR is usually nonlinear. We present a new linear state evolution model for PDR. In simulated-data and real-data tests of tightly coupled WLAN-PDR positioning, the positioning accuracy with this linear model is better than with the traditional models when the initial heading is not known, which is a common situation. The proposed method is computationally light and is also suitable for smoothing. Furthermore, we present modifications to WLAN positioning based on Gaussian coverage areas and show how a Kalman filter using the proposed model can be used for integrity monitoring and (re)initialization of a particle filter.
ASJC Scopus subject areas
- Computational modeling, Indoor positioning, Pedestrian dead reckoning, Wireless LAN