149 research outputs found
On the Performance Limits of Pilot-Based Estimation of Bandlimited Frequency-Selective Communication Channels
In this paper the problem of assessing bounds on the accuracy of pilot-based
estimation of a bandlimited frequency selective communication channel is
tackled. Mean square error is taken as a figure of merit in channel estimation
and a tapped-delay line model is adopted to represent a continuous time channel
via a finite number of unknown parameters. This allows to derive some
properties of optimal waveforms for channel sounding and closed form Cramer-Rao
bounds
Statistical Characterization and Mitigation of NLOS Errors in UWB Localization Systems
In this paper some new experimental results about the statistical
characterization of the non-line-of-sight (NLOS) bias affecting time-of-arrival
(TOA) estimation in ultrawideband (UWB) wireless localization systems are
illustrated. Then, these results are exploited to assess the performance of
various maximum-likelihood (ML) based algorithms for joint TOA localization and
NLOS bias mitigation. Our numerical results evidence that the accuracy of all
the considered algorithms is appreciably influenced by the LOS/NLOS conditions
of the propagation environment
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
Theoretical framework for In-Car Navigation based on Integrated GPS/IMU Technologies
In this report the problem of vehicular navigation based on the integration of the global positioning system and an inertial navigation system
is tackled. After analysing some fundamental technical issues about reference systems, vehicle modelling and sensors, a novel solution, combining extended Kalman filtering with particle filltering, is developed. This solution allows to embed highly non-linear constraints originating from
digital maps in the position estimation process and is expected to be implementable on commercial hardware platforms equipped with low cost
inertial sensorsJRC.G.6-Digital Citizen Securit
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