5 research outputs found
Non-line-of-sight identification and mitigation for indoor localization using ultra-wideband sensor networks
Thesis (PhD (Computer Engineering))--University of Pretoria, 2020.With the advent of Industry 4.0, indoor localization is central to many applications across multiple
domains. Although impulse-radio ultra-wideband (IR-UWB) enables high precision time-of-arrival
(TOA) based ranging and localization for wireless sensor networks, there are several challenges,
including multi-user interference and non-line-of-sight (NLOS) conditions. NLOS conditions occur
when the communication path between receiver and transmitter is obstructed, and these conditions
are frequent indoors due to walls and other obstructions. To maintain location accuracy and precision
similar to line-of-sight (LOS) conditions, identification and mitigation of these NLOS conditions is
crucial. For identification and mitigation methods to be implemented in sensor networks, they must be
of low complexity to minimize their influence on localization requirements.
This thesis investigates NLOS identification and mitigation for IEEE 802.15.4a IR-UWB sensor
networks. The objective of this thesis is to improve location accuracy in NLOS conditions for IR-UWB
sensor networks. A comprehensive review of the state-of-the-art in NLOS identification and mitigation
is conducted, and limitations of these methods with regards to the use of multiple channels, dependence
on training data, mobility and complexity (particularly for applications with time constraints) are highlighted. This thesis proposes identification and mitigation methods that address the limitations
found in state-of-the-art methods.
A distance residual-based method for NLOS identification is proposed. Compared to conventional
NLOS identification which relies on knowledge of LOS and NLOS channel statistics, or analysis of
the standard deviation of range measurements over time, this identification method does not rely on
these parameters.
A NLOS classification method that distinguishes between through-the-wall and around-the-corner
conditions using channel statistics extracted from channel impulse responses is proposed. Unlike most
methods in literature that focus on distinguishing between LOS and NLOS, this method classifies
NLOS conditions into through-the-wall and around-the-corner, therefore providing more context to
the location estimate, and consequently enabling mitigation methods to be used for specific types of
NLOS conditions.
A through-the-wall ranging error mitigation method that relies on floor plans is proposed. A novel model
for through-the-wall TOA ranging is proposed and experimentally evaluated. The conventional throughthe-
wall TOA ranging model in literature requires many parameters which cannot be calculated in
realistic scenarios. Compared to through-the-wall TOA ranging models found in literature, the proposed
model relies on information from floor plans to reduce the number of unknown parameters in the model.
The results show that NLOS errors caused by through-the-wall propagation are significantly mitigated
with the proposed method, resulting in location accuracy which approaches the LOS case.
A NLOS mitigation method which corrects location estimates affected by random ranging errors
is proposed. This method relies on geometric constraints based on the fact that biases introduced
by NLOS conditions in TOA range measurements are positive. The method is evaluated for cases
where NLOS ranges are identifiable and cases where they are not identifiable. For the latter case, the
results show that the proposed method significantly outperforms state-of-the-art optimization-based
mitigation methods in terms of execution time, while retaining similar performance in terms of location
accuracy.Electrical, Electronic and Computer EngineeringPhD (Computer Engineering)UnrestrictedFaculty of Engineering, Built Environment and Information TechnologySDG-09: Industry, innovation and infrastructureSDG-11:Sustainable cities and communitie
Radio Communications
In the last decades the restless evolution of information and communication technologies (ICT) brought to a deep transformation of our habits. The growth of the Internet and the advances in hardware and software implementations modified our way to communicate and to share information. In this book, an overview of the major issues faced today by researchers in the field of radio communications is given through 35 high quality chapters written by specialists working in universities and research centers all over the world. Various aspects will be deeply discussed: channel modeling, beamforming, multiple antennas, cooperative networks, opportunistic scheduling, advanced admission control, handover management, systems performance assessment, routing issues in mobility conditions, localization, web security. Advanced techniques for the radio resource management will be discussed both in single and multiple radio technologies; either in infrastructure, mesh or ad hoc networks
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Design and Implementation of Large-Scale Wireless Sensor Networks for Environmental Monitoring Applications
Environmental monitoring represents a major application domain for wireless sensor networks (WSN). However, despite significant advances in recent years, there are still many challenging issues to be addressed to exploit the full potential of the emerging WSN technology. In this dissertation, we introduce the design and implementation of low-power wireless sensor networks for long-term, autonomous, and near-real-time environmental monitoring applications. We have developed an out-of-box solution consisting of a suite of software, protocols and algorithms to provide reliable data collection with extremely low power consumption. Two wireless sensor networks based on the proposed solution have been deployed in remote field stations to monitor soil moisture along with other environmental parameters. As parts of the ever-growing environmental monitoring cyberinfrastructure, these networks have been integrated into the Texas Environmental Observatory system for long-term operation. Environmental measurement and network performance results are presented to demonstrate the capability, reliability and energy-efficiency of the network