3,661 research outputs found
Performance evaluation of indoor localization techniques based on RF power measurements from active or passive devices
The performance of networks for indoor localization based on RF power measurements from active or passive devices is evaluated in terms of the accuracy, complexity, and costs. In the active device case, the terminal to be located measures the power transmitted by some devices inside its coverage area. To determine the terminal position in the area, power measurements are then compared with the data stored in an RF map of the area. A network architecture for localization based on passive devices is presented. Its operations are based on the measure of the power retransmitted from local devices interrogated by the terminal and on their identities. Performance of the two schemes is compared in terms of the probability of localization error as a function of the number (density) of active or passive devices. Analysis is carried out through simulation in a typical office-like environment whose propagation characteristics have been characterized experimentally. Considerations obtained in this work can be easily adapted to other scenarios. The procedure used for the analysis is general and can be easily extended to other situations
A Robust Zero-Calibration RF-based Localization System for Realistic Environments
Due to the noisy indoor radio propagation channel, Radio Frequency (RF)-based
location determination systems usually require a tedious calibration phase to
construct an RF fingerprint of the area of interest. This fingerprint varies
with the used mobile device, changes of the transmit power of smart access
points (APs), and dynamic changes in the environment; requiring re-calibration
of the area of interest; which reduces the technology ease of use. In this
paper, we present IncVoronoi: a novel system that can provide zero-calibration
accurate RF-based indoor localization that works in realistic environments. The
basic idea is that the relative relation between the received signal strength
from two APs at a certain location reflects the relative distance from this
location to the respective APs. Building on this, IncVoronoi incrementally
reduces the user ambiguity region based on refining the Voronoi tessellation of
the area of interest. IncVoronoi also includes a number of modules to
efficiently run in realtime as well as to handle practical deployment issues
including the noisy wireless environment, obstacles in the environment,
heterogeneous devices hardware, and smart APs. We have deployed IncVoronoi on
different Android phones using the iBeacons technology in a university campus.
Evaluation of IncVoronoi with a side-by-side comparison with traditional
fingerprinting techniques shows that it can achieve a consistent median
accuracy of 2.8m under different scenarios with a low beacon density of one
beacon every 44m2. Compared to fingerprinting techniques, whose accuracy
degrades by at least 156%, this accuracy comes with no training overhead and is
robust to the different user devices, different transmit powers, and over
temporal changes in the environment. This highlights the promise of IncVoronoi
as a next generation indoor localization system.Comment: 9 pages, 13 figures, published in SECON 201
WiFi emission-based vs passive radar localization of human targets
In this paper two approaches are considered for human targets localization based on the WiFi signals: the device emission-based localization and the passive radar. Localization performance and characteristics of the two localization techniques are analyzed and compared, aiming at their joint exploitation inside sensor fusion systems. The former combines the Angle of Arrival (AoA) and the Time Difference of Arrival (TDoA) measures of the device transmissions to achieve the target position, while the latter exploits the AoA and the bistatic range measures of the target echoes. The results obtained on experimental data show that the WiFi emission-based strategy is always effective for the positioning of human targets holding a WiFi device, but it has a poor localization accuracy and the number of measured positions largely depends on the device activity. In contrast, the passive radar is only effective for moving targets and has limited spatial resolution but it provides better accuracy performance, thanks to the possibility to integrate a higher number of received signals. These results also demonstrate a significant complementarity of these techniques, through a suitable experimental test, which opens the way to the development of appropriate sensor fusion techniques
AROMA: Automatic Generation of Radio Maps for Localization Systems
WLAN localization has become an active research field recently. Due to the
wide WLAN deployment, WLAN localization provides ubiquitous coverage and adds
to the value of the wireless network by providing the location of its users
without using any additional hardware. However, WLAN localization systems
usually require constructing a radio map, which is a major barrier of WLAN
localization systems' deployment. The radio map stores information about the
signal strength from different signal strength streams at selected locations in
the site of interest. Typical construction of a radio map involves measurements
and calibrations making it a tedious and time-consuming operation. In this
paper, we present the AROMA system that automatically constructs accurate
active and passive radio maps for both device-based and device-free WLAN
localization systems. AROMA has three main goals: high accuracy, low
computational requirements, and minimum user overhead. To achieve high
accuracy, AROMA uses 3D ray tracing enhanced with the uniform theory of
diffraction (UTD) to model the electric field behavior and the human shadowing
effect. AROMA also automates a number of routine tasks, such as importing
building models and automatic sampling of the area of interest, to reduce the
user's overhead. Finally, AROMA uses a number of optimization techniques to
reduce the computational requirements. We present our system architecture and
describe the details of its different components that allow AROMA to achieve
its goals. We evaluate AROMA in two different testbeds. Our experiments show
that the predicted signal strength differs from the measurements by a maximum
average absolute error of 3.18 dBm achieving a maximum localization error of
2.44m for both the device-based and device-free cases.Comment: 14 pages, 17 figure
A Real-Time Laboratory Testbed For Evaluating Localization Performance Of WIFI RFID Technologies
A realistic comparative performance evaluation of indoor Geolocation systems is a complex and challenging problem facing the research community. This is due to the fact that performance of these systems depends on the statistical variations of the fading multipath characteristics of the wireless channel, the density and distribution of the access points in the area, and the number of the training points used by the positioning algorithm. This problem, in particular, becomes more challenging when we address RFID devices, because the RFID tags and the positioning algorithm are implemented in two separate devices. In this thesis, we have designed and implemented a testbed for comparative performance evaluation of RFID localization systems in a controlled and repeatable laboratory environment. The testbed consists of a real-time RF channel simulator, several WiFi 802.11 access points, commercial RFID tags, and a laptop loaded with the positioning algorithm and its associated user interface. In the real-time channel simulator the fading multipath characteristics of the wireless channel between the access points and the RFID tags is modeled by a modified site-specific IEEE 802.11 channel model which combines this model with the correlation model of shadow fading existing in the literature. The testbed is first used to compare the performance of the modified IEEE 802.11 channel model and the Ray Tracing channel model previously reported in the literature. Then, the testbed with the new channel model is used for comparative performance evaluation of two different WiFi RFID devices
Acoustical Ranging Techniques in Embedded Wireless Sensor Networked Devices
Location sensing provides endless opportunities for a wide range of applications in GPS-obstructed environments;
where, typically, there is a need for higher degree of accuracy. In this article, we focus on robust range
estimation, an important prerequisite for fine-grained localization. Motivated by the promise of acoustic in
delivering high ranging accuracy, we present the design, implementation and evaluation of acoustic (both
ultrasound and audible) ranging systems.We distill the limitations of acoustic ranging; and present efficient
signal designs and detection algorithms to overcome the challenges of coverage, range, accuracy/resolution,
tolerance to Doppler’s effect, and audible intensity. We evaluate our proposed techniques experimentally on
TWEET, a low-power platform purpose-built for acoustic ranging applications. Our experiments demonstrate
an operational range of 20 m (outdoor) and an average accuracy 2 cm in the ultrasound domain. Finally,
we present the design of an audible-range acoustic tracking service that encompasses the benefits of a near-inaudible
acoustic broadband chirp and approximately two times increase in Doppler tolerance to achieve better performance
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