Seunghwan Jeong

Extended Kalman Filter for wireless LAN based indoor positioning

A WLAN (Wireless Local Area Network) based Extended Kalman Filter (EKF) method for indoor positioning is introduced in this paper. WLAN based indoor positioning is more economical than other methods because it does not require any special equipment dedicated to positioning. The most popular technique used for indoor positioning is the fingerprinting method, but the EKF method is easier to deploy because, unlike fingerprinting, it does not require a time consuming off-line phase. This paper also provides experimental comparisons of our EKF method with other indoor positioning methods.

Utilizing Map Information for WLAN-Based Kalman Filter Indoor Tracking

Extended Kalman filter (EKF), which has long been used in the field of GPS positioning, has recently been used for indoor positioning, introduced extended Kalman filter (EKF) indoor positioning method based on Bluetooth signal strength. However, the error range of the EKF is so large when it was applied in WLAN tracking that we modified it to use K-NN method for the measurement of the EKF. Furthermore, this paper proposes an idea of improving accuracy of EKF tracking by adjusting parameter values referring to map information. Experimental results comparing our method with other previous methods are discussed.

Development of Kalman Filters for WLAN Based Tracking

Location based service (LBS) cannot be realized unless the location of the user is available. For indoor LBS, indoor positioning must be utilized and many researchers have been working on indoor positioning and tracking. For example, extended Kalman filter (EKF) was exploited in Bluetooth based indoor positioning. Nowadays, WLAN (wireless local area network) is available virtually everywhere. Thus, WLAN based indoor positioning and tracking is more economical than Bluetooth based ones. The main purpose of this paper is to propose a new WLAN based EKF indoor tracking method by extending existing Bluetooth based EKF positioning method. Experimental results comparing our method with other previous methods are discussed.

Colored Petri Net Representation of RDF Models

This paper proposes a method of transforming RDF (resource description framework) model into a CPN (colored Petri net) model. The method represents the semantics of the RDF model in the CPN model by mapping the classes and properties of RDF model to CPN places and representing the relationships between classes and properties as token transitions on the CPN. In order to represent a RDF statement on the CPN, the method introduces a transition which produces a token consisting of two ordered tokens, one is corresponding to the subject and the other is corresponding to the object of the statement. Applying the proposed method, we built an example CPN model for a RDF model. We also perform simulations on the model to answer to RDF queries.

Integrated Indoor Positioning Systems Reflecting Map Information for Location Based Services

So many location based service systems, including automobile navigation system logistic management, taxi fleet management, and so on, are being used everywhere. However, these are all outdoors. This paper provides a stepping stone for commercial indoor location based services by developing an integrated system of our indoor positioning and map viewer modules. For the indoor positioning, we propose WLAN (Wireless Local Area Network) based EKF (Extended Kalman Filter) which estimates user`s current location and tracts user`s trace in the sequence of time. Our map viewer renders a map recorded in an Autocad DXF file and provides functions of map manipulation such as zoom-in, zoom-out, and move. We integrate our indoor positioning and map viewer modules and discuss the experimental results of the integrated system.