23-04-2014, 02:58 PM
A Data Fusion Technique for Wireless Ranging Performance Improvement
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Abstract
The increasing diffusion of mobile and portable de-
vices provided with wireless connectivity makes the problem of
distance measurement based on radio-frequency technologies in-
creasingly important for the development of next-generation no-
madic applications. In this paper, the performance limitations of
two classic wireless ranging techniques based on received signal
strength (RSS) and two-way time-of-flight (ToF) measurements,
respectively, are analyzed and compared in detail. On the basis of
this study, a data fusion algorithm is proposed to combine both
techniques in order to improve ranging accuracy. The algorithm
has been implemented and tested on the field using a dedicated
embedded prototype made with commercial off-the-shelf compo-
nents. Several experimental results prove that the combination
of both techniques can significantly reduce measurement uncer-
tainty. The results obtained with the developed prototype are not
accurate enough for fine-grained position tracking in Ambient
Assisted Living applications. However, the platform can be suc-
cessfully used for reliable indoor zoning, e.g., for omnidirectional
and adjustable hazard proximity detection. Most importantly, the
proposed solution is absolutely general, and it is quite simple
and light from the computational point of view. Accuracy could
be further improved by using a more isotropic antenna and by
integrating the ToF measurement technique at the lowest possible
level on the same radio chip used for communication. Usually, this
feature is not available in typical low-cost short-range wireless
modules, e.g., for wireless sensor networks. Thus, the results of
this research suggest that combining RSS with ToF measurements
could be a viable solution for chip manufacturers interested in
adding ranging capabilities to their radio modules.
I NTRODUCTION
IN THE last years, wireless measurement techniques for
indoor object positioning have become increasingly inter-
esting in various applicative fields such as home automation,
security, and Ambient Assisted Living (AAL). Unfortunately,
most of the existing solutions suffer from limitations imposed
by the line-of-sight (LOS) constraints, as they usually properly
work only in a specified direction. As a consequence,
DATA F USION A LGORITHM FOR
D ISTANCE E STIMATION
In order to perform object tracking, the distance between two
nodes should be continuously measured over time. Assuming
that one node is fixed, whereas the other is moving, the distance
can be measured by either node (e.g., the moving device) as
soon as it receives the response or acknowledgment message
sent by its partner. Thus, every distance value estimated through
either (1) or (3) is intrinsically event driven. If the commu-
nication between nodes periodically occurs, the time interval
Tc between two consecutive messages received by the node
measuring the distance can be regarded as the sampling period
of the ranging system. In theory, Tc can be arbitrarily set by the
user. The lower bound to Tc is given by the sum of the minimum
RTT value including the time spent to process any sent or
received packet and the computing time due to the distance
estimation algorithm. Of course, Tc is generally subject to some
fluctuations (e.g., due to timestamping jitter, channel access, or
processing latency variations). However, if Tc is set much larger
than these fluctuations, their effect on the performance of the
digital ranging system is negligible, as shown in Section V-B.
CONCLUSION
This paper deals with a data fusion algorithm merging RSS
and ToF measurement results in order to improve wireless
ranging accuracy. Both approaches have been analyzed in detail
in order to evaluate the main uncertainty contributions affecting
either measurement procedure. The proposed algorithm has a
general validity (i.e., independent of the chosen implemen-
tation), and it relies on two MA filters to reduce the input
wideband noise, a heuristic criterion able to easily remove
possible large position-dependent offsets, and two KFs that use
RSS- and ToF-based measurement results in a complementary
manner. Due to its moderate complexity, the algorithm could
be integrated in future transceiver chips to support possible
positioning services (e.g., for wireless sensor networks). At
the moment, the algorithm has been implemented and tested
on the field using a dedicated embedded system made up of
commercial off-the-shelf (COTS) components. The estimated
accuracy is generally about 1 m, but it can be so small as
50–60 cm around a given reference distance. Accordingly,
such a distance can be also set as a threshold for adjustable
and omnidirectional proximity detection. Unfortunately, the
accuracy of the developed prototype is limited by the features
of some hardware components, particularly the antenna that
is not so isotropic as specified in the data sheet.