Low Complexity Location Fingerprinting with Generalized UWB Energy Detection Receivers
Christoph Steiner and Armin Wittneben
IEEE Transactions on Signal Processing, Volume 58, Issue 3, pp. 1756 - 1767, Mar. 2010.
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In this paper we propose and investigate location fingerprinting
with a low complexity generalized Ultra-Wideband energy detection
receiver. The energy samples at the output of the analog receiver
front-end serve as location fingerprints. We formulate the position
location problem as hypothesis testing problem and develop a
Bayesian framework treating the location fingerprints as random
vectors. In order to obtain an accurate stochastic description of
the energy samples, which is required by the Bayesian framework, we
provide two approaches. First, we derive a numerical algorithm to
calculate the exact probability density functions of the energy
samples, in case the Ultra-Wideband channel follows a Gaussian
process. These results are used for benchmarking and performance
prediction. Second, we propose closed form probability density
functions based on a model selection criterion and measured energy
samples. We show the accuracy and applicability of these closed form
probability density functions in terms of performance results of the
position location algorithm. The performance of the proposed
location fingerprinting algorithm is evaluated based on measured
Ultra-Wideband channels. The impact of important system parameters
on the performance is investigated as well.
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