3,094 research outputs found
Map-Aware Models for Indoor Wireless Localization Systems: An Experimental Study
The accuracy of indoor wireless localization systems can be substantially
enhanced by map-awareness, i.e., by the knowledge of the map of the environment
in which localization signals are acquired. In fact, this knowledge can be
exploited to cancel out, at least to some extent, the signal degradation due to
propagation through physical obstructions, i.e., to the so called
non-line-of-sight bias. This result can be achieved by developing novel
localization techniques that rely on proper map-aware statistical modelling of
the measurements they process. In this manuscript a unified statistical model
for the measurements acquired in map-aware localization systems based on
time-of-arrival and received signal strength techniques is developed and its
experimental validation is illustrated. Finally, the accuracy of the proposed
map-aware model is assessed and compared with that offered by its map-unaware
counterparts. Our numerical results show that, when the quality of acquired
measurements is poor, map-aware modelling can enhance localization accuracy by
up to 110% in certain scenarios.Comment: 13 pages, 11 figures, 1 table. IEEE Transactions on Wireless
Communications, 201
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 Dopplerâs 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
Location-free Spectrum Cartography
Spectrum cartography constructs maps of metrics such as channel gain or
received signal power across a geographic area of interest using spatially
distributed sensor measurements. Applications of these maps include network
planning, interference coordination, power control, localization, and cognitive
radios to name a few. Since existing spectrum cartography techniques require
accurate estimates of the sensor locations, their performance is drastically
impaired by multipath affecting the positioning pilot signals, as occurs in
indoor or dense urban scenarios. To overcome such a limitation, this paper
introduces a novel paradigm for spectrum cartography, where estimation of
spectral maps relies on features of these positioning signals rather than on
location estimates. Specific learning algorithms are built upon this approach
and offer a markedly improved estimation performance than existing approaches
relying on localization, as demonstrated by simulation studies in indoor
scenarios.Comment: 14 pages, 12 figures, 1 table. Submitted to IEEE Transactions on
Signal Processin
Anticipatory User-Association for Indoor Visible Light Communications: Light, Follow Me!
In this paper, a radically new anticipatory perspective is taken into account when designing the user-to-Access Point (AP) associations for indoor Visible Light Communications (VLC) networks, in the presence of users' mobility and wirelesstraffic dynamics. In its simplest guise, by considering the users' future locations and their predicted traffic dynamics, the novel anticipatory association prepares the APs for users in advance, resulting in an enhanced location- and delay-awareness. This is technically realised by our contrived design of an efficient approximate dynamic programming algorithm. More importantly, our study is in contrast to most of the current research in the area of indoor VLC networks, where static network environment was mainly considered. Hence, our study is able to draw insights on the performance trade-off between delay and throughput in dynamic indoor VLC networks. It is shown that the novel anticipatory design is capable of significantly outperforming the conventional benchmarking designs, striking an attractive performance trade-off between delay and throughput. Quantitatively, the average system queue backlog is reduced from 15 [ms] to 8 [ms], when comparing the design advocated to the conventional benchmark at the per-user throughput of 100 [Mbps], in a 15Ă15Ă5 [m 3 ] indoor environment associated with 8Ă8 APs and 20 users walking at 1 [m/s]
Hidden Markov models for radio localization in mixed LOS/NLOS conditions
AbstractâThis paper deals with the problem of radio localization of moving terminals (MTs) for indoor applications with mixed line-of-sight/non-line-of-sight (LOS/NLOS) conditions. To reduce false localizations, a grid-based Bayesian approach is proposed to jointly track the sequence of the positions and the sight conditions of the MT. This method is based on the assumption that both the MT position and the sight condition are Markov chains whose state is hidden in the received signals [hidden Markov model (HMM)]. The observations used for the HMM localization are obtained from the power-delay profile of the received signals. In ultrawideband (UWB) systems, the use of the whole power-delay profile, rather than the total power only, allows to reach higher localization accuracy, as the power-profile is a joint measurement of time of arrival and power. Numerical results show that the proposed HMM method improves the accuracy of localization with respect to conventional ranging methods, especially in mixed LOS/NLOS indoor environments. Index TermsâBayesian estimation, hidden Markov models (HMM), mobile positioning, source localization, tracking algorithms
Map matching by using inertial sensors: literature review
This literature review aims to clarify what is known about map matching by
using inertial sensors and what are the requirements for map matching, inertial
sensors, placement and possible complementary position technology. The target
is to develop a wearable location system that can position itself within a complex
construction environment automatically with the aid of an accurate building model.
The wearable location system should work on a tablet computer which is running
an augmented reality (AR) solution and is capable of track and visualize 3D-CAD
models in real environment. The wearable location system is needed to support the
system in initialization of the accurate camera pose calculation and automatically
ïŹnding the right location in the 3D-CAD model. One type of sensor which does seem
applicable to people tracking is inertial measurement unit (IMU). The IMU sensors
in aerospace applications, based on laser based gyroscopes, are big but provide a
very accurate position estimation with a limited drift. Small and light units such
as those based on Micro-Electro-Mechanical (MEMS) sensors are becoming very
popular, but they have a signiïŹcant bias and therefore suïŹer from large drifts and
require method for calibration like map matching. The system requires very little
ïŹxed infrastructure, the monetary cost is proportional to the number of users, rather
than to the coverage area as is the case for traditional absolute indoor location
systems.Siirretty Doriast
A Review of Radio Frequency Based Localization for Aerial and Ground Robots with 5G Future Perspectives
Efficient localization plays a vital role in many modern applications of
Unmanned Ground Vehicles (UGV) and Unmanned aerial vehicles (UAVs), which would
contribute to improved control, safety, power economy, etc. The ubiquitous 5G
NR (New Radio) cellular network will provide new opportunities for enhancing
localization of UAVs and UGVs. In this paper, we review the radio frequency
(RF) based approaches for localization. We review the RF features that can be
utilized for localization and investigate the current methods suitable for
Unmanned vehicles under two general categories: range-based and fingerprinting.
The existing state-of-the-art literature on RF-based localization for both UAVs
and UGVs is examined, and the envisioned 5G NR for localization enhancement,
and the future research direction are explored
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