1,699 research outputs found
Massive MIMO-based Localization and Mapping Exploiting Phase Information of Multipath Components
In this paper, we present a robust multipath-based localization and mapping
framework that exploits the phases of specular multipath components (MPCs)
using a massive multiple-input multiple-output (MIMO) array at the base
station. Utilizing the phase information related to the propagation distances
of the MPCs enables the possibility of localization with extraordinary accuracy
even with limited bandwidth. The specular MPC parameters along with the
parameters of the noise and the dense multipath component (DMC) are tracked
using an extended Kalman filter (EKF), which enables to preserve the
distance-related phase changes of the MPC complex amplitudes. The DMC comprises
all non-resolvable MPCs, which occur due to finite measurement aperture. The
estimation of the DMC parameters enhances the estimation quality of the
specular MPCs and therefore also the quality of localization and mapping. The
estimated MPC propagation distances are subsequently used as input to a
distance-based localization and mapping algorithm. This algorithm does not need
prior knowledge about the surrounding environment and base station position.
The performance is demonstrated with real radio-channel measurements using an
antenna array with 128 ports at the base station side and a standard cellular
signal bandwidth of 40 MHz. The results show that high accuracy localization is
possible even with such a low bandwidth.Comment: 14 pages (two columns), 13 figures. This work has been submitted to
the IEEE Transaction on Wireless Communications for possible publication.
Copyright may be transferred without notice, after which this version may no
longer be accessibl
Practical Accuracy Limits of Radiation-Aware Magneto-Inductive 3D Localization
The key motivation for the low-frequency magnetic localization approach is
that magnetic near-fields are well predictable by a free-space model, which
should enable accurate localization. Yet, limited accuracy has been reported
for practical systems and it is unclear whether the inaccuracies are caused by
field distortion due to nearby conductors, unconsidered radiative propagation,
or measurement noise. Hence, we investigate the practical performance limits by
means of a calibrated magnetoinductive system which localizes an active
single-coil agent with arbitrary orientation, using 4 mW transmit power at 500
kHz. The system uses eight single-coil anchors around a 3m x 3m area in an
office room. We base the location estimation on a complex baseband model which
comprises both reactive and radiative propagation. The link coefficients, which
serve as input data for location estimation, are measured with a multiport
network analyzer while the agent is moved with a positioner device. This
establishes a reliable ground truth for calibration and evaluation. The system
achieves a median position error of 3.2 cm and a 90th percentile of 8.3 cm.
After investigating the model error we conjecture that field distortion due to
conducting building structures is the main cause of the performance bottleneck.
The results are complemented with predictions on the achievable accuracy in
more suitable circumstances using the Cram\'er-Rao lower bound.Comment: To appear at the IEEE ICC 2019 Workshops. This work has been
submitted to the IEEE for possible publication. Copyright may be transferred
without notice, after which this version may no longer be accessibl
Locating the information: applications, technologies and future aspects
In today’s world, the demand for information is growing rapidly with respect to the human curiosity to explore the inside and the outside of our planet. In a simple analogy, the human body has thousands of sensors called receptor neurons to obtain information such as temperature or pressure from the environment. Similarly, recent developments in electronics and wireless communications lead engineers to the design of small-sized, low-power, low-cost sensor nodes which have the ability to communicate with each other over short distances and collect the information that is gathered
Detection of UWB ranging measurement quality for collaborative indoor positioning
Wireless communication signals have become popular alternatives for indoor positioning and navigation due to lack of navigation satellite signals in such environments. The signal characteristics determine the method used for positioning as well as the positioning accuracy. Ultra-wideband (UWB) signals, with a typical bandwidth of over 1 GHz, overcome multipath problems in complicated environments. Hence, potentially achieves centimetre-level ranging accuracy in open areas. However, signals can be disrupted when placed in environments with obstructions and cause large ranging errors. This paper proposes a ranging measurement quality indicator (RQI) which detects the UWB measurement quality based on the received signal strength pattern. With a detection validity of more than 83%, the RQI is then implemented in a ranging-based collaborative positioning system. The relative constraint of the collaborative network is adjusted adaptively according to the detected RQI. The proposed detection and positioning algorithm improves positioning accuracy by 80% compared to non-adaptive collaborative positioning
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