Tightly Coupled Positioning and Multipath Radio Channel Tracking
Mannesson, Anders LU ; Yaqoob, Muhammad Atif LU ; Bernhardsson, Bo LU
and Tufvesson, Fredrik
LU
(2016)
In IEEE Transactions on Aerospace and Electronic Systems
p.1522-1535
- Abstract
- Radio based localization is an active research topic with a wide range of applications. In this paper, we focus on localization of a radio receiver equipped with an inertial measurement unit. The localization is performed while simultaneously constructing a map of the small scale fading pattern in the local radio environment. The map in our case is a ray-trace-based multipath channel model. This solution is enabled by sensor fusion of information from the channel estimation data and the inertial sensors, and it does not assume any knowledge of, e.g., transmitter locations. The sensor data is fused in a recursive state space model that combines the kinematic motion model with the ray-based radio channel model, and the state vector is... (More)
- Radio based localization is an active research topic with a wide range of applications. In this paper, we focus on localization of a radio receiver equipped with an inertial measurement unit. The localization is performed while simultaneously constructing a map of the small scale fading pattern in the local radio environment. The map in our case is a ray-trace-based multipath channel model. This solution is enabled by sensor fusion of information from the channel estimation data and the inertial sensors, and it does not assume any knowledge of, e.g., transmitter locations. The sensor data is fused in a recursive state space model that combines the kinematic motion model with the ray-based radio channel model, and the state vector is estimated using a particle filter. The choice of the particle filter is justified by the multimodal characteristics of the posterior likelihood distributions that follows from the nonlinearities of the problem. The work is assuming a single receiver antenna but the approach can also be transferred to multiple antenna systems. We study the performance of the approach under realistic assumptions, based on the performance of today’s low-cost inertial sensors and radio systems, including accelerometer and gyroscope noise, and also radio receiver frequency error and noise. Simulations show a significant improvement in long-term positioning performance, evaluated against dead reckoning. The work is concluded with experiments which serve as a proof of concept for the proposed technique, using no extra equipment compared to what can be found in a modern cellular phone. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/8860468
- author
- Mannesson, Anders
LU
; Yaqoob, Muhammad Atif
LU
; Bernhardsson, Bo
LU
and Tufvesson, Fredrik
LU
- organization
- publishing date
- 2016
- type
- Contribution to journal
- publication status
- published
- subject
- in
- IEEE Transactions on Aerospace and Electronic Systems
- pages
- 1522 - 1535
- publisher
- IEEE - Institute of Electrical and Electronics Engineers Inc.
- external identifiers
-
- scopus:84997503388
- wos:000388648500005
- ISSN
- 0018-9251
- DOI
- 10.1109/TAES.2016.140653
- project
- Joint Positioning and Radio Channel Estimation
- language
- English
- LU publication?
- yes
- id
- f087a0ca-18d6-4265-a6b6-62f4b938a3a6 (old id 8860468)
- date added to LUP
- 2016-04-04 09:42:16
- date last changed
- 2022-04-23 21:54:51
@article{f087a0ca-18d6-4265-a6b6-62f4b938a3a6,
abstract = {{Radio based localization is an active research topic with a wide range of applications. In this paper, we focus on localization of a radio receiver equipped with an inertial measurement unit. The localization is performed while simultaneously constructing a map of the small scale fading pattern in the local radio environment. The map in our case is a ray-trace-based multipath channel model. This solution is enabled by sensor fusion of information from the channel estimation data and the inertial sensors, and it does not assume any knowledge of, e.g., transmitter locations. The sensor data is fused in a recursive state space model that combines the kinematic motion model with the ray-based radio channel model, and the state vector is estimated using a particle filter. The choice of the particle filter is justified by the multimodal characteristics of the posterior likelihood distributions that follows from the nonlinearities of the problem. The work is assuming a single receiver antenna but the approach can also be transferred to multiple antenna systems. We study the performance of the approach under realistic assumptions, based on the performance of today’s low-cost inertial sensors and radio systems, including accelerometer and gyroscope noise, and also radio receiver frequency error and noise. Simulations show a significant improvement in long-term positioning performance, evaluated against dead reckoning. The work is concluded with experiments which serve as a proof of concept for the proposed technique, using no extra equipment compared to what can be found in a modern cellular phone.}},
author = {{Mannesson, Anders and Yaqoob, Muhammad Atif and Bernhardsson, Bo and Tufvesson, Fredrik}},
issn = {{0018-9251}},
language = {{eng}},
pages = {{1522--1535}},
publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
series = {{IEEE Transactions on Aerospace and Electronic Systems}},
title = {{Tightly Coupled Positioning and Multipath Radio Channel Tracking}},
url = {{http://dx.doi.org/10.1109/TAES.2016.140653}},
doi = {{10.1109/TAES.2016.140653}},
year = {{2016}},
}