Using data mining and fingerprinting extension with device orientation information for WLAN efficient indoor location estimation

Abstract

Research based on indoor location systems has recently been developed due to growing interest in locationaware services to be implemented in light mobile devices. Most of this work is based on received signal strength (RSS) from access points. However, a major drawback from using RSS is its variability due to indoor multipath effect caused by reflection, diffraction and scattering of signal propagation. Therefore, different device orientations in a fixed location provide significant and different RSS values. In this paper, we propose to extend fingerprinting with device orientation information. Implementation of our location system is based on data mining techniques employing decision tree algorithms. Experimental results demonstrate that using RSS samples with the device orientation information improves the location estimation with high accuracy.

Compensating for Orientation Mismatch in Robust Wi-Fi Localization Using Histogram Equalization

“…Finally, the proposed algorithm is compared with four traditional approaches for addressing the problem of orientation variation: the compass-assisted method [50], [51], the orientation classifier [56], the compressive sensing [53], [54] and the radio map filtering methods [52]. The compass-assisted approach involves the assumption that both the device and radio map contain real-time orientation information and estimating the testing measurement according to the orientationmatched radio map only.…”

“…A similar approach was presented in [51] and [52], in which fingerprinting is extended with orientation information. These approaches effectively reduce the orientation mismatch effect; however, they require prior orientation data to enrich the radio map and real-time feedback from a digital compass.…”

WiFi Positioning Based on User Orientation Estimation and Smartphone Carrying Position Recognition

“…During online phase, based on the estimated user orientation information, new measured RSS vector samples are only compared with the selected fingerprints sharing a similar user orientation. Similar approaches have been proposed in [27,28], in which the radio map is extended with user orientation information. However, two problems still need to be solved to enhance the reliability and applicability of fingerprinting based positioning.…”