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Positioning Techniques in Indoor Environments Based on Stochastic Modeling of UWB Round Trip Time Measurements

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posted on 20.07.2021, 19:53 by Paolo Carbone

In this paper, a technique for modeling propagation of Ultra Wide Band (UWB) signals in indoor or outdoor environments is proposed, supporting the design of a positioning systems based on Round Trip Time (RTT) measurements and on a particle filter. By assuming that nonlinear pulses are transmitted in an Additive White Gaussian Noise Channel, and detected using a threshold based receiver, it is shown that RTT measurements may be affected by a non-Gaussian noise. RTT noise properties are analyzed, and the effects of non-Gaussian noise on the performance of a RTT based positioning system are investigated. To this aim, a classical Least Square, an extended Kalman Filter and a Particle Filter are compared when used to detect a slowly moving target in presence of the modeled noise. It is shown that, in a realistic indoor environment, the Particle Filter solution may be a competitive solution, at a price of increased computational complexity. Experimental verifications validate the presented approach.

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Email Address of Submitting Author

paolo.carbone@unipg.it

Submitting Author's Institution

University of Perugia, Eng. Dept.

Submitting Author's Country

Italy

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