WiFi fingerprinting has been a popular approach for indoor positioning in the past decade. However, most existing fingerprint-based systems were designed as an on demand service to guide the user to his wanted destination. This article introduces a novel feature that allows the positioning system to predict in advance which walking route the user may use, and the potential destination. To achie...

The occurrence of cycle slips is a major limiting factor for achievement of sub-decimeter accuracy in positioning with GPS (Global Positioning System). In the past, several authors introduced a method based on different combinations of GPS data together with Kalman filter to solve the problem of the cycle slips. In this paper the same philosophy is used but with discrete wavelet transforms. For...

With the rapid development of communication and information technology, our demand of wireless localization is increasing day by day. This paper gives an overview of the existing wireless indoor positioning techniques. Several typical indoor positioning systems and the techniques they have used are described and analyzed. The possible trend of positioning system research are presented.

WLAN positioning systems are a promising approach to determine a users location in In-Building environments. The motivation for developing, the possible utilization as well as known issues are discussed. Physical fundamentals and technical aspects of the WLAN technique are explained to examine the positioning potential in detail. Furthermore, an example positioning system is presented and analy...

We present preliminary results of the design of a mini in-parallel 3-d.o.f. positioning system called MIPS. MIPS degrees of freedom are one translation and two orientations, which are obtained by the motions of linear magnetic actuators acting within a special in-parallel mechanical architecture. Its overall width will be about 1cm for a length of about 3cm. MIPS should be useful in medical app...

Indoor and urban positioning is an important market which is foreseen to grow significantly in the future years. Unfortunately, in indoor and urban environment the classical mean of positioning based on Global Navigation