ETH - Indoor Positioning & Indoor Navigation


10:30 - 11:00	Stefano Maddio (presenting author), Luca Bencini, Alessandro Cidronali, Gianfranco Manes: A Single Anchor Direction of Arrival Positioning System Augmenting Standard Wireless Communication Technology This paper presents an effective, compact and easy to deploy system for DoA indoor localization techniques. It is based on a Switched Beam Antenna (SBA) a signal multiplexer and the Received Signal Strength Indicator, it is fully compatible with available commercial transceivers. We describe the system architecture as well as the approach adopted for the DoA estimation which is a derivation of the widely adopted MUSIC technique. We also propose a demonstration of its characteristics and by the exploitation of the indoor positing features in a realistic indoor environment of about 25 square meters, for which the SBA is the single anchor placed in the centre of the room ceiling. The system is capable to localize a target node with a precision of about 50 cm in the area below the SBA, while an error within 1 m is observed in a region covering about the 90% of the test area of the room. The system is capable to locate a target node and due to its effectiveness to track the motion within the room, finally it is also suitable as part of application layer for the most of the wireless access technologies.

11:00 - 11:15	Jorge Robles (presenting author), Sebastian Tromer, Monica Quiroga and Ralf Lehnert: Enabling Low-power Localization for Mobile Sensor Nodes One of the most challenging issues in the design of localization systems is to improve the battery lifetime of the mobile nodes as much as possible. In a previous work of the authors [1] a novel low-power scheme for RSS-based localization is proposed. This scheme provides, in an efficient way, the necessary information for the position calculation trying to minimize the energy consumption of the mobile node. In this paper we describe the first implementation of our proposal in a non-beacon enabled IEEE 802.15.4 sensor network and evaluate its performance.

11:15 - 11:30	Lujia Wang, Chao Hu (presenting author), Longqiang Tian and Max Q.-H Meng: A Novel 5-Dimentional RF Signal Strength Indoor Localization Method Based on Multipath Propagation Radio received signal strength (RSS) method is widely applied in the indoor localization and navigation system. In order to realize it and get best performance, we have to analyze some factors such as the initial value choosing for Levenberg-Marquardt (LM) nonlinear optimization method, the placement of the RF receivers relative to the source transmitter, the estimation of the noise in the environment, and especially the multipath fading of the electromagnetic wave. The simulation experiments show the feasibility and anti-noise property of the proposed localization method.

11:30 - 11:45	Olga E. Segou (presenting author), Stelios A. Mitilineos, Stelios C.A. Thomopoulos: DALE: A Range-Free, Adaptive Indoor Localization System Enhanced by Limited Fingerprinting A novel range-free algorithm is presented in this paper. DALE (DALE is Adaptive Localization with Enhancements) includes a two-stage algorithm and it is described as adaptive in the sense that it is able to incorporate fingerprints of specific locations when available in order to enhance localization accuracy. The proposed method is aimed in indoor environments and requires a strategic placement of nodes in each room. It is easily scalable to a large number of rooms and adaptable to rooms with complex geometry. Based on plain RSSI measurements, which are easily collected on inexpensive hardware, the range-free method returns an area wherein the mobile node lies, instead of a specific position fix. Simulation results are derived in order to evaluate the proposed algorithm and compared to relative research results in the literature, indicating that the proposed scheme achieves superior robustness and accuracy, while being less computationally extensive and using fewer beacons.

RF RSS (ZigBee, FM, General RF), Fingerprinting, Part 2

Session Chair: Prof. Philippe Canalda, University of Franche-Comte


13:15 - 13:45	Francescantonio Della Rosa (presenting author), Helena Leppäkoski, Stefano Biancullo, and Jari Nurmi: Ad-hoc Networks Aiding Indoor Calibrations Of Heterogeneous Devices for Fingerprinting Applications In this paper we propose a technique able to avoid long time and power-consuming calibration phases to obtain adapted fingerprint databases for multiple heterogeneous devices with different wireless cards. Specifically, we propose to exploit the received signal strength from ad-hoc connections among neighboring mobile stations by evaluating the spatial proximity among them, (by the exploitation of empirical path-loss models for ad-hoc link distance detections), as constraint for the RSS database calibration and final positioning estimation of the mobiles in fingerprinting applications.

13:45 - 14:15	Ana M. Bernardos, (Data Processing and Simulation Group at the Universidad Politécnica de Madrid), Henar Martin (presenting author, Data Processing and Simulation Group at the Universidad Politécnica de Madrid), José R. Casar, Paula Tarrío: Real time calibration for RSS indoor positioning systems Most current indoor localization systems usually work with received signal strength (RSS) measurements gathered from different wireless technologies (WiFi, Bluetooth, ZigBee, etc.). The RSS signal random nature makes that most of the systems, either map-based or channel model based, need an off-line calibration phase, at least when starting the location system for the first time. Calibration usually is a resource and time consuming task, and its validity expires after a period of time, mainly due to continuous and unavoidable physical variations of the environment (e.g. changing people flow during the day, open or closed doors, furniture redistributions, etc.). In this contribution we present an algorithm which allows dynamic calibration of a channel model-based localization technique. The algorithm uses a Least Mean Squares technique to adaptively estimate the constants of the propagation model, using reference beacons, aiming at minimizing the error of a hyperbolic triangulation method. Simulated and real data show that the location error is effectively minimized after a number of training samples, making possible to avoid manual calibration and recalibration procedures when deploying a localization system.

14:15 - 14:45	Katrin Achutegui (at the Universidad Carlos III de Madrid, presenting author), Javier Rodas, Carlos J. Escudero, Joaquín Míguez: A Model-Switching Sequential Monte Carlo Algorithm for Indoor Tracking with Experimental RSS Data We address the problem of indoor tracking using received signal strength (RSS) as a position dependent data measurement. This type of measurements are very appealing because they can be easily obtained with a variety of wireless technologies however are very unstable for indoor scenarios due to multipath propagation. For that reason we propose the use of a compound model that combines several sub-models, whose parameters are adjusted to specific and different propagation environments. This methodology, called IMM, has been used in the past to model the motion of maneuvering targets. We extend its application to also handle the uncertainty of the RSS observations. The flexibility of the approach is attained at the expense of an increase in the number of random processes that must be accurately tracked. To overcome this difficulty, we introduce a Rao-Blackwellized sequential Monte Carlo tracking algorithm that exhibits good performance both with synthetic and experimental data.

14:45 - 15:00	Janire Larrañaga (presenting author), Leire Muguira, Juan-Manuel Lopez-Garde, Juan-Ignacio Vazquez: An Environment Adaptive ZigBee based Indoor Positioning Algorithm We present a robust, easy to deploy and flexible indoor location system based on ZigBee Wireless Sensor Networks. To this end, we have developed a descendent gradient iteration algorithm which lets us calculate the blind node’s position in a very accurate way. Such algorithm is based on a matrix system that is used to represent the information received from the reference nodes, and update it whenever is necessary. This way, the environment’s changes can be recorded in this matrix system. Our location system is based on RSSI level measurements since no extra hardware is required. The location system consists of two phases: calibration and location. Anytime a blind node needs to be located, our system performs the calibration, so that the environment can be characterised and we can obtain a more reliable result (an average error of 3 meters). So, this ZigBee location algorithm provides very promising results.

15:00 - 15:15	Luis Brás (presenting author at University Aveiro), Marco Oliveira, Pedro Pinho, Nuno Carvalho: Low Power Location Protocol based on ZigBee Two of the main characteristics desired for indoor location systems are low power consumption and resolution. A proper protocol communication development is a crucial issue to have in consideration for global performance of the system, being a key element for power consumption reduction and for a correct forwarding of useful information for location process. The purpose of this paper is to present an implementation of a low power ZigBee location protocol which provides the location based on: detection by Highest Received Signal Strength Indication (HiRSSI), and the base for more complex algorithms such as triangulation or fingerprinting. This selection of the location mode is managed by a graphical interface based in Java language, with the characteristic of easy and intuitive use. It is described the consumption performance description of mobile nodes, where using a battery of 650mAH can achieve a life time from several months until few years.

Oral Presentations (Poster Teasers)

Wednesday, September 15
Auditorium G7


15:15 - 15:17	Juan Carlos Garcia (presenting author), Jesús Ureña, Jesús García: Improving ZigBee 2D5 localization in large buildings using Metric Description Graphs (Poster Teaser) This work will propose a way of improving location estimations of a ZigBee RSSI based Indoor Localization System (ILS) in large buildings. ILS beacons are a network of fixed sensor nodes, linked with ZigBee protocol, installed in convenient locations. A set of unknown objects, equipped also with ZigBee devices (blind nodes), can be located and tracked by ILS. Localization system will provide 2’5 dimensions data (2D5) about blind nodes location: 2D metric information (X and Y axis) in every floor plus an indication of floor number in height (Z). Positioning of blind nodes is improved fitting initial estimations into a building metric description graph which include connectivity among rooms and relative distances between graph nodes.

15:17 - 15:19	Ada Vittoria Bosisio: User Positioning by means of pre-computed Attenuation Maps (Poster Teaser) The proposed positioning technique is based on pre-computed attenuation maps of the received signal inside an indoor environment characterized by dense multipath fading effects. The attenuation maps are obtained through ray tracing modeling and they are validated against measurements by means of several Crossbow MICA2 devices operating at 433 MHz. The scenario is a conference room equipped with 8 transmitting anchor nodes (AP’s). A network of calibration points is composed by 27 probe nodes. The goal is to obtain a satisfactory estimate of an user position based on the tuple {ak} of the attenuation values, where k indexes the AP nodes.

15:19 - 15:21	Andrei Popleteev (presenting author, at University of Trento and Create-Net), Aleksandar Matic, Venet Osmani, Oscar Mayora-Ibarra: Indoor positioning using off-the-shelf FM radio devices (Poster Teaser) Current de-facto standard of indoor positioning are Wi-Fi-based systems. However, Wi-Fi coverage is limited. In cases when Wi-Fi infrastructure is not readily present, its deployment is expensive in terms of hardware costs and required personnel qualification. A cost-effective alternative to Wi-Fi is localization using FM radio signals. Previous works on FM positioning considered only outdoor environments and used specialised hardware. This paper, in contrast, focuses on indoor scenarios and FM modules already present in many mobile devices, such as cellphones, MP3 players, etc. The short-range FM transmitters used as beacons are available from conventional electronics shops, and are significantly cheaper than Wi-Fi access points. In this paper we present the results of experimental comparison of FM and Wi-Fi indoor positioning performance. Also, we describe and evaluate a method for maintaining the system accuracy over time without any additional hardware.

15:21 - 15:23	Paolo Barsocchi, Francesco Furfari, Paolo Nepa, Francesco Potortì (presenting author): RSSI localization with sensors placed on the user (Poster Teaser) The goal of this work is to use a detailed ray-tracing simulation, in order to investigate the performance of indoor, single-room localization when multiple sensor nodes are placed on the mobile. This study does not lend itself to practical implementation of a localization method, but rather provides insight into comparing the performance by using either one or more sensor nodes placed on the user. In other words, this study aims at answering the following questions: How the localization performance increases by using multiple sensors placed on the user? Is it possible to understand the direction where the user is facing? We answer these questions by using a parameter estimation approach and by comparing three scenarios. The first one with only one sensor per user, and the other two scenarios with two and three sensors, respectively.

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