AmbiLoc: A year-long dataset of FM, TV and GSM fingerprints for ambient indoor localization

Ambient indoor localization - an approach that leverages ambient radio signals - has been previously shown to provide promising positioning performance using the globally available infrastructure of FM, TV and cellular stations. However, the need for specialized equipment and laborious data collection constitute a high entry barrier for follow-up studies. This paper presents AmbiLoc - a dataset of radio signals for ambient indoor localization research. The dataset has been systematically collected in multiple testbeds, including large-scale and multi-floor buildings, over the course of one year. Due to the use of a software-defined radio receiver, raw signal samples in AmbiLoc allow extraction of arbitrary fingerprinting features. The first edition of AmbiLoc, introduced in this paper, includes received signals strength (RSS) fingerprints of FM, TV and GSM signals, along with the relevant metadata (such as weather conditions). The dataset is available online at AmbiLoc.org. As the first public dataset of ambient localization signals, AmbiLoc provides an easy entry and a common reference for researchers exploring novel indoor localization methods

Indoor positioning and floor plan based ground truth: Can you really click where you are?

The increasing accuracy of indoor positioning systems requires an appropriately accurate evaluation, which compares system outputs with the known coordinates of test locations --- the ground truth. Although ground truth data are rarely (if ever) tested, they are traditionally assumed to be perfectly accurate. However, even small errors introduced by inaccurate ground truth need to be taken into account for fair evaluation and comparison between modern high-resolution positioning systems. In this paper we analyze the quality of ground truth data provided by clicking on an interactive floor plan (a method employed by such classical systems as RADAR and Horus). Experimental results show that this method has high precision but low accuracy, and high systematic errors make it unsuitable for evaluation of fine-grained localization systems

Poster: Impact of ground truth errors on Wi-Fi localization accuracy

This study investigates the impact of small ground truth (GT) errors on indoor positioning systems based on Wi-Fi fingerprinting. The results demonstrate that even centimeter-scale GT deviations cause severe degradation of measured localization accuracy

Investigation of indoor localization with ambient FM radio stations

Localization plays an essential role in many ubiquitous computing applications. While the outdoor location-aware services based on GPS are becoming increasingly popular, their proliferation to indoor environments is limited due to the lack of widely available indoor localization systems. The de-facto standard for indoor positioning is based on Wi-Fi and while other localization alternatives exist, they either require expensive hardware or provide a low accuracy. This paper presents an investigation into localization system that leverages signals of broadcasting FM radio stations. The FM stations provide a worldwide coverage, while FM tuners are readily available in many mobile devices. The experimental results show that FM radio can be used for indoor localization, while providing longer battery life than Wi-Fi, making FM an alternative to consider for positioning.Comment: 10th IEEE Pervasive Computing and Communication conference, PerCom 2012, pp. 171 - 17

Activity tracking and indoor positioning with a wearable magnet

This paper presents an unconventional application of digital compass sensors for localization and activity monitoring in ambient assisted living scenarios. Benefits and limitations of the proposed approach are reviewed and compared to these of traditional tracking methods, such as wearable devices, surveillance cameras and device-free localization

Please Stand By: TV-based indoor localization

Despite the decades of efforts, indoor positioning remains an open research challenge. While existing solutions already demonstrate high accuracy, their in-building infrastructure --- such as Wi-Fi access points or Bluetooth beacons --- provides only a limited coverage. This paper investigates feasibility of accurate indoor positioning using broadcast digital TV signals, readily available in populated areas worldwide. We experiment with the classic received signal strength (RSS) fingerprinting, and introduce a novel approach based on channel state information (CSI), which leverages frequency-selective multipath fading of wideband TV signals. The proposed methods are experimentally evaluated on an extensive dataset of DVB-T signals, systematically collected in two large buildings over the course of 8 months. The results show that the proposed approach consistently outperforms RSS fingerprinting and achieves 92--98% localization accuracy. While this study is based on the European DVB-T signals, the proposed method is directly generalizable to other TV standards (such as ATSC, ISDB, DTMB and DMB) and wide-area TV white space (TVWS) networks

Wi-Fi butterfly effect in indoor localization: The impact of imprecise ground truth and small-scale fading

The increasing accuracy of indoor positioning systems makes their evaluation an increasingly challenging task. A number of factors are already known to affect performance of fingerprint-based systems: hardware diversity, device orientation, environment dynamics. This paper presents a new butterfly-like effect in localization experiments. The effect is caused by minor ground truth (GT) errors --- that is, small deviations between calibration and test positions. While such deviations are widely considered as purely additive and thus negligible, we demonstrate that even centimeter-scale GT errors are amplified by small-scale radio fading and lead to severe multi-meter Wi-Fi positioning errors. The results show that fingerprint-based localization accuracy quickly deteriorates as GT errors increase towards 0.4 wavelength (5 cm for 2.4 GHz). Beyond that threshold, system's accuracy saturates to about one-third of its original level achievable with precise GT. This effect challenges the impact of the already known accuracy-limiting factors (such as cross-user tests, receiver diversity, device orientation and temporal variations), as they can be partially explained by minor GT errors. Moreover, for smartphone-in-a-hand experiments, this effect directly associates the evaluation outcomes with experimenters' diligence

Device-free indoor localization using ambient radio signals

This paper investigates feasibility of device-free indoor localization using single passive receiver. Instead of local wireless nodes sharing one frequency channel, this work leverages multiple ambient FM radio stations. Experimental results demonstrate feasibility of the proposed approach and highlight the role of frequency diversity for passive localization

Indoor localization using ambient FM radio RSS fingerprinting: A 9-month study

While indoor positioning systems aspire for higher accuracy, their coverage is typically limited to buildings with dedicated hardware. A possible alternative is offered by infrastructure-free positioning methods. In particular, several studies have demonstrated feasibility of indoor positioning using broadcast FM radio signals, which are available in most populated areas worldwide. However, previous work provides little information about long-term performance of FM-based indoor localization. This paper presents a longitudinal study of FM indoor positioning based on received signal strength (RSS) fingerprinting. We evaluate system's performance on a large dataset of real-world FM signals, systematically collected in several large-scale multi-floor testbeds over the course of 9 months. We also investigate the impact of different classifiers, training schedules and fingerprint sizes on localization accuracy. The results demonstrate that well-trained FM-based system can provide reliable indoor positioning even several months after deployment