4 research outputs found
Space-Time Hierarchical-Graph Based Cooperative Localization in Wireless Sensor Networks
It has been shown that cooperative localization is capable of improving both
the positioning accuracy and coverage in scenarios where the global positioning
system (GPS) has a poor performance. However, due to its potentially excessive
computational complexity, at the time of writing the application of cooperative
localization remains limited in practice. In this paper, we address the
efficient cooperative positioning problem in wireless sensor networks. A
space-time hierarchical-graph based scheme exhibiting fast convergence is
proposed for localizing the agent nodes. In contrast to conventional methods,
agent nodes are divided into different layers with the aid of the space-time
hierarchical-model and their positions are estimated gradually. In particular,
an information propagation rule is conceived upon considering the quality of
positional information. According to the rule, the information always
propagates from the upper layers to a certain lower layer and the message
passing process is further optimized at each layer. Hence, the potential error
propagation can be mitigated. Additionally, both position estimation and
position broadcasting are carried out by the sensor nodes. Furthermore, a
sensor activation mechanism is conceived, which is capable of significantly
reducing both the energy consumption and the network traffic overhead incurred
by the localization process. The analytical and numerical results provided
demonstrate the superiority of our space-time hierarchical-graph based
cooperative localization scheme over the benchmarking schemes considered.Comment: 14 pages, 15 figures, 4 tables, accepted to appear on IEEE
Transactions on Signal Processing, Sept. 201
Wireless Localization Systems: Statistical Modeling and Algorithm Design
Wireless localization systems are essential for emerging applications that rely on
context-awareness, especially in civil, logistic, and security sectors. Accurate localization in indoor environments is still a challenge and triggers a fervent research
activity worldwide. The performance of such systems relies on the quality of range
measurements gathered by processing wireless signals within the sensors composing
the localization system. Such range estimates serve as observations for the target
position inference. The quality of range estimates depends on the network intrinsic
properties and signal processing techniques. Therefore, the system design and analysis call for the statistical modeling of range information and the algorithm design
for ranging, localization and tracking. The main objectives of this thesis are: (i) the
derivation of statistical models and (ii) the design of algorithms for different wire-
less localization systems, with particular regard to passive and semi-passive systems
(i.e., active radar systems, passive radar systems, and radio frequency identification
systems). Statistical models for the range information are derived, low-complexity
algorithms with soft-decision and hard-decision are proposed, and several wideband
localization systems have been analyzed. The research activity has been conducted
also within the framework of different projects in collaboration with companies and
other universities, and within a one-year-long research period at Massachusetts Institute of Technology, Cambridge, MA, USA. The analysis of system performance,
the derived models, and the proposed algorithms are validated considering different case studies in realistic scenarios and also using the results obtained under the
aforementioned projects