GSM-Based Positioning Technique Using Relative Received Signal Strength

GSM-Based Positioning Technique Using Relative Received Signal Strength

Mohamed H. Abdel Meniem, Ahmed M. Hamad, Eman Shaaban
Copyright: © 2013 |Pages: 14
DOI: 10.4018/ijhcr.2013100103
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Context-aware applications have been gaining huge interest in the last few years. With cell phones becoming ubiquitous computing devices, cell phone localization has become an important research problem. Database Correlation Method (DCM) is a positioning technology that based on a database of a premeasured location dependent variable such as Received Signal Strength (RSS). DCM has shown superior in terms of accuracy. Absolute RSS values received from a base station change with time, but the relative RSS (RRSS) values which refer to the relations of the RSS values between different base stations are more stable. This study proposes and implements a robust RRSS GSM-based technique for both positioning and traffic estimation. The study was tested and analyzed in Egypt roads using realistic data and Android smart phones. The performance evaluation showed good results. Mean positioning accuracy was about 29m in urban areas and velocity estimation was about 1 km/h in rural areas.
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1. Introduction

Locating mobile devices has always been a critical problem. It becomes even more critical today, as the number of context-aware applications is continuously growing. Acquiring the location information of a mobile device allows providing more value-added applications. Recently Several location estimation systems are developed. A vast majority of applications of location estimation use the GPS satellite system, which provides location estimates with an accuracy of a few meters. Alternatives to satellite-based systems are also developed to avoid problems such as lack of coverage between high buildings and indoors. These techniques use signals between the mobile unit and terrestrial transmitters or receivers. The transmitters can be either dedicated for this purpose or be a part of a communication system, such as a cellular telephone network. Cellular positioning techniques can be categorized into terminal-based techniques and network-based techniques. In terminal-based techniques, user equipment (UE) receives beacons and does all necessary processing in to order to calculate its position. In contrast, network-based techniques measurements are received from UE, and its position is calculated silently.

Another alternative is Wireless-Fidelity (WiFi). WiFi has been widely used for localization systems in several researches and commercial efforts (Cheng, Chawathe, LaMarca, & Krumm, 2005; LaMarca et al., 2005; Pahlavan et al., 2010). Moreover, WiFi technology has been used as Floating Car Data (FCD) for traffic prediction systems (Hendricks, Fontaine, & Smith, 2005; Hsiao & Chang, 2005; Thianniwet, Phosaard & Pattara-Atikom, 2009). VTrack ‎(Thiagarajan et al., 2009) proved that it is feasible to accurately estimate road travel times using a sequence of inaccurate WiFi-based position samples. WiFi-based localization techniques might raise privacy concerns, especially when apply the scan process or “War-Driving” (Sathu, 2006). Therefore, GSM-based positioning techniques appeared again with different implementations that using different techniques like Cell-ID, TA, AoA, OTD, and TDoA (Borenovic, Simic, Neskovic, & Petrovic, 2005; Dufková et al., 2008; Küpper, 2005; Varshavsky et al., 2006; Wang, Min, & Yi, 2008). Cell-ID method relies on the fact that mobile networks can identify the approximate position of a mobile handset by knowing which cell site the device is using at a given time. This is usually the cell tower with the strongest Received Signal Strength Indicator RSSI. Such techniques require a database of cell towers’ locations and provide an efficient, though coarse grained localization method. In Time Advance (TA) techniques, positioning information is derived from the absolute time for a wave to travel between a transmitter and a receiver or vice versa. In Angle of Arrival AoA techniques, mobile device can be pinpointed by detecting the angle of arrival of its signal at two Base Transceiver Stations BTSs. In Observing Time Difference (OTD) and Time Difference of Arrival (TDoA) techniques, each TDoA measurement defines a hyperbolic locus on which the mobile terminal must lie. The intersection of the hyperbolic loci will define the position of the mobile device.

Many organisms now use radio fingerprinting for localization as in Chen el al. (2006). GSM-based phones are also used in traffic monitoring services as dynamic probes or Floating Car Data (FCD).

This study proposes a featured positioning technique based on Relative Received Signal Strength RRSS. The study has been tested and analyzed in Egypt roads using realistic data and Android smart phones. This work is part of EgTNS (2011); Egypt Traffic and Navigation System. The rest of this paper is organized as follows. Section 2 gives an insight into localization methods based on RSS. Section 3 presents traffic estimation techniques. Section 4 is describing our proposed Relative RSS approach for accurate localization, followed by field results and performance evaluation in section 5. Section 6 provides a conclusion and possible directions for future research.

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