24,099 research outputs found
Self-localization in Ad Hoc Indoor Acoustic Networks
The increasing use of mobile technology in everyday life has aroused interest into developing new ways of utilizing the data collected by devices such as mobile phones and wearable devices. Acoustic sensors can be used to localize sound sources if the positions of spatially separate sensors are known or can be determined. However, the process of determining the 3D coordinates by manual measurements is tedious especially with increasing number of sensors. Therefore, the localization process has to be automated. Satellite based positioning is imprecise for many applications and requires line-of-sight to the sky. This thesis studies localization methods for wireless acoustic sensor networks and the process is called self-localization.This thesis focuses on self-localization from sound, and therefore the term acoustic is used. Furthermore, the development of the methods aims at utilizing ad hoc sensor networks, which means that the sensors are not necessarily installed in the premises like meeting rooms and other purpose-built spaces, which often have dedicated audio hardware for spatial audio applications. Instead of relying on such spaces and equipment, mobile devices are used, which are combined to form sensor networks.For instance, a few mobile phones laid on a table can be used to create a sensor network built for an event and it is inherently dismantled once the event is over, which explains the use of the term ad hoc. Once positions of the devices are estimated, the network can be used for spatial applications such as sound source localization and audio enhancement via spatial filtering. The main purpose of this thesis is to present the methods for self-localization of such an ad hoc acoustic sensor network. Using off-the-shelf ad hoc devices to establish sensor networks enables implementation of many spatial algorithms basically in any environment.Several acoustic self-localization methods have been introduced over the years. However, they often rely on specialized hardware and calibration signals. This thesis presents methods that are passive and utilize environmental sounds such as speech from which, by using time delay estimation, the spatial information of the sensor network can be determined. Many previous self-localization methods assume that audio captured by the sensors is synchronized. This assumption cannot be made in an ad hoc sensor network, since the different sensors are unaware of each other without specific signaling that is not available without special arrangement.The methods developed in this thesis are evaluated with simulations and real data recordings. Scenarios in which the targets of positioning are stationary and in motion are studied. The real world recordings are made in closed spaces such as meeting rooms. The targets are approximately 1 – 5 meters apart. The positioning accuracy is approximately five centimeters in a stationary scenario, and ten centimeters in a moving-target scenario on average. The most important result of this thesis is presenting the first self-localization method that uses environmental sounds and off-the-shelf unsynchronized devices, and allows the targets of self-localization to move
Jumps: Enhancing hop-count positioning in sensor networks using multiple coordinates
Positioning systems in self-organizing networks generally rely on
measurements such as delay and received signal strength, which may be difficult
to obtain and often require dedicated equipment. An alternative to such
approaches is to use simple connectivity information, that is, the presence or
absence of a link between any pair of nodes, and to extend it to hop-counts, in
order to obtain an approximate coordinate system. Such an approximation is
sufficient for a large number of applications, such as routing. In this paper,
we propose Jumps, a positioning system for those self-organizing networks in
which other types of (exact) positioning systems cannot be used or are deemed
to be too costly. Jumps builds a multiple coordinate system based solely on
nodes neighborhood knowledge. Jumps is interesting in the context of wireless
sensor networks, as it neither requires additional embedded equipment nor
relies on any nodes capabilities. While other approaches use only three
hop-count measurements to infer the position of a node, Jumps uses an arbitrary
number. We observe that an increase in the number of measurements leads to an
improvement in the localization process, without requiring a high dense
environment. We show through simulations that Jumps, when compared with
existing approaches, reduces the number of nodes sharing the same coordinates,
which paves the way for functions such as position-based routing
Robotic Wireless Sensor Networks
In this chapter, we present a literature survey of an emerging, cutting-edge,
and multi-disciplinary field of research at the intersection of Robotics and
Wireless Sensor Networks (WSN) which we refer to as Robotic Wireless Sensor
Networks (RWSN). We define a RWSN as an autonomous networked multi-robot system
that aims to achieve certain sensing goals while meeting and maintaining
certain communication performance requirements, through cooperative control,
learning and adaptation. While both of the component areas, i.e., Robotics and
WSN, are very well-known and well-explored, there exist a whole set of new
opportunities and research directions at the intersection of these two fields
which are relatively or even completely unexplored. One such example would be
the use of a set of robotic routers to set up a temporary communication path
between a sender and a receiver that uses the controlled mobility to the
advantage of packet routing. We find that there exist only a limited number of
articles to be directly categorized as RWSN related works whereas there exist a
range of articles in the robotics and the WSN literature that are also relevant
to this new field of research. To connect the dots, we first identify the core
problems and research trends related to RWSN such as connectivity,
localization, routing, and robust flow of information. Next, we classify the
existing research on RWSN as well as the relevant state-of-the-arts from
robotics and WSN community according to the problems and trends identified in
the first step. Lastly, we analyze what is missing in the existing literature,
and identify topics that require more research attention in the future
LIS: Localization based on an intelligent distributed fuzzy system applied to a WSN
The localization of the sensor nodes is a fundamental problem in wireless sensor networks.
There are a lot of different kinds of solutions in the literature. Some of them use external
devices like GPS, while others use special hardware or implicit parameters in wireless
communications.
In applications like wildlife localization in a natural environment, where the power available
and the weight are big restrictions, the use of hungry energy devices like GPS or hardware
that add extra weight like mobile directional antenna is not a good solution.
Due to these reasons it would be better to use the localization’s implicit characteristics in
communications, such as connectivity, number of hops or RSSI. The measurement related
to these parameters are currently integrated in most radio devices. These measurement
techniques are based on the beacons’ transmissions between the devices.
In the current study, a novel tracking distributed method, called LIS, for localization of
the sensor nodes using moving devices in a network of static nodes, which have no additional
hardware requirements is proposed.
The position is obtained with the combination of two algorithms; one based on a local
node using a fuzzy system to obtain a partial solution and the other based on a centralized
method which merges all the partial solutions. The centralized algorithm is based on the
calculation of the centroid of the partial solutions.
Advantages of using fuzzy system versus the classical Centroid Localization (CL)
algorithm without fuzzy preprocessing are compared with an ad hoc simulator made for
testing localization algorithms.
With this simulator, it is demonstrated that the proposed method obtains less localization
errors and better accuracy than the centroid algorithm.Junta de Andalucía P07-TIC-0247
Robust Localization from Incomplete Local Information
We consider the problem of localizing wireless devices in an ad-hoc network
embedded in a d-dimensional Euclidean space. Obtaining a good estimation of
where wireless devices are located is crucial in wireless network applications
including environment monitoring, geographic routing and topology control. When
the positions of the devices are unknown and only local distance information is
given, we need to infer the positions from these local distance measurements.
This problem is particularly challenging when we only have access to
measurements that have limited accuracy and are incomplete. We consider the
extreme case of this limitation on the available information, namely only the
connectivity information is available, i.e., we only know whether a pair of
nodes is within a fixed detection range of each other or not, and no
information is known about how far apart they are. Further, to account for
detection failures, we assume that even if a pair of devices is within the
detection range, it fails to detect the presence of one another with some
probability and this probability of failure depends on how far apart those
devices are. Given this limited information, we investigate the performance of
a centralized positioning algorithm MDS-MAP introduced by Shang et al., and a
distributed positioning algorithm, introduced by Savarese et al., called
HOP-TERRAIN. In particular, for a network consisting of n devices positioned
randomly, we provide a bound on the resulting error for both algorithms. We
show that the error is bounded, decreasing at a rate that is proportional to
R/Rc, where Rc is the critical detection range when the resulting random
network starts to be connected, and R is the detection range of each device.Comment: 40 pages, 13 figure
Sparse Localization with a Mobile Beacon Based on LU Decomposition in Wireless Sensor Networks
Node localization is the core in wireless sensor network. It can be solved by powerful beacons, which are equipped with global positioning system devices to know their location information. In this article, we present a novel sparse localization approach with a mobile beacon based on LU decomposition. Our scheme firstly translates node localization problem into a 1-sparse vector recovery problem by establishing sparse localization model. Then, LU decomposition pre-processing is adopted to solve the problem that measurement matrix does not meet the re¬stricted isometry property. Later, the 1-sparse vector can be exactly recovered by compressive sensing. Finally, as the 1-sparse vector is approximate sparse, weighted Cen¬troid scheme is introduced to accurately locate the node. Simulation and analysis show that our scheme has better localization performance and lower requirement for the mobile beacon than MAP+GC, MAP-M, and MAP-M&N schemes. In addition, the obstacles and DOI have little effect on the novel scheme, and it has great localization performance under low SNR, thus, the scheme proposed is robust
MiPOS - the Mote Indoor Positioning System
In the past few years, there have been huge research efforts into ubiquitous and context aware platforms that offer a user a custom level of service based on some known local parameters. The utility of such systems is greatly enhanced if a physical locational area can be determined. Recently, hybrid devices have been developed combining low power micro controllers with short range FM radio transceivers. Some location identification work has been carried out with these systems such as the Matrix Pencil approximation technique[8],however most of these all provide information for an ideal square area with no RF obstructions.Here we present MiPOS, a scalable locationing system based on the MICA mote[11] family of devices.The design goal of MiPOS is to provide a low-power, scalable, distributed locationing system suited to an indoor (office) environment.During the presentation of this paper we will highlight solutions in the areas of security, radio and network management and power awareness for a hybrid context aware wearable locationing device
- …