Wireless location estimation using generalized linear models

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2004-01-01
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Amran, Prihamdhani
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Electrical and Computer Engineering

The Department of Electrical and Computer Engineering (ECpE) contains two focuses. The focus on Electrical Engineering teaches students in the fields of control systems, electromagnetics and non-destructive evaluation, microelectronics, electric power & energy systems, and the like. The Computer Engineering focus teaches in the fields of software systems, embedded systems, networking, information security, computer architecture, etc.

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The Department of Electrical Engineering was formed in 1909 from the division of the Department of Physics and Electrical Engineering. In 1985 its name changed to Department of Electrical Engineering and Computer Engineering. In 1995 it became the Department of Electrical and Computer Engineering.

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1909-present

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  • Department of Electrical Engineering (1909-1985)
  • Department of Electrical Engineering and Computer Engineering (1985-1995)

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Location estimation is a very important task in wireless communication systems. Its goal is to determine the geographic position and, in some cases, velocity and direction of motion of wireless devices. The main challenge and critical requirement is to design an accurate and low-cost location system. This technology is utilized for global position system (GPS) and some localization applications in cellular and sensor networks. We propose maximum likelihood (ML) methods for location estimation using received-signal-strength (RSS) and time-of-arrival (TOA) measurements. In the RSS case, we utilize both spatial and temporal measurements where the multipath fading effects are modeled using a Nakagami-[gamma] fading model. We also proposed to model the TOA measurement errors using the gamma distribution characteristic. We also derive Cramér-Rao bound (CRB) for the estimated location under both measurement scenarios. Simulation results show that the proposed algorithms outperform the commonly-used least-squares methods.

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Thu Jan 01 00:00:00 UTC 2004