Special Issue "Localization in Wireless Sensor Networks"

A special issue of Journal of Sensor and Actuator Networks (ISSN 2224-2708).

Deadline for manuscript submissions: closed (31 October 2019).

Special Issue Editors

Dr. Marko Beko
Website
Guest Editor
Universidade Lusofona, Lisboa, Portugal
Interests: wireless communications and networking; signal processing; machine learning; sensor networks; cognitive radio; source localization; PAPR reduction; MIMO communications
Prof. Slavisa Tomic
Website
Guest Editor
Universidade Lusófona de Humanidades e Tecnologias, Portugal
Interests: target localization; non-convex optimization
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Special Issue Information

Dear Colleagues,

Recent and continuing growth of mobile computing and user-centric applications has led to a need for accurate and low-cost localization and tracking systems. Global Navigation Satellite Systems, and in particular, Global Positioning System (GPS), have become part of our everyday lives and are widely used for outdoor navigation and localization. However, most people spend a large amount of their time in indoor environments (home, office, school, etc.), where GPS has very limited or no functionality. Therefore, researchers have been exploring use of alternative sources of information for indoor localization. With an objective of maintaining low implementation costs, making use of existing technologies, such as terrestrial radio frequency (RF) sources, when providing a solution to the localization problem is strongly encouraged. Amongst others, these include Wi-Fi, Bluetooth and ultra-wide band (UWB) signals, but researchers also use infrared signals, images, acoustic, light, and magnetic fields to name a few. Nevertheless, the requirement for wide deployment of infrastructure has made these systems cost-ineffective for some time. Only recently, advances in RF and micro-electromechanical system integrated circuit design enabled the wide availability of low-cost sensors and permitted the use of large-scale networks with hundreds or even thousands of sensors, sensing at high spatial and temporal densities. Because of the immense network proportions, human moderation is almost impossible. In order to achieve autonomous network configuration and establish the quality of the network coverage and/or spatial/geographical relationship for signal analysis and data mining, automatic estimation of sensors’ physical locations is of crucial importance. Moreover, localization using existing technologies is a key enabling technology for many applications that can improve safety and efficiency in everyday life (such as ambient assisted living (assistance for elderly or people with disabilities, smart parking, monitoring of storage conditions and goods), navigation (aid for visually impaired, guiding costumers through shopping malls, airports, etc.), workforce management (finding nearby doctors or police officers), context-dependent information sharing, etc.), and is being actively pursued by technological giants, such as Google, Apple, Microsoft and Huawei, as well as research groups in some of the leading universities worldwide. Nonetheless, current systems found in the literature provide unsatisfactory accuracies or require specific and expensive equipment that needs to be installed and maintained. Thus, the search for a robust and accurate localization system still remains open.

This Special Issue is focused on real-time target localization and tracking techniques in wireless sensor networks. Research articles, review articles as well as short communications are invited.

Topics of Interest

Suitable topics include, but are not limited to:

  • Single target tracking
  • Multiple target tracking
  • Continuous target tracking
  • Prediction-based target tracking
  • Range estimation
  • Range free localization
  • Range based localization
  • Acoustic localization
  • Visible light localization
  • Hybrid localization
  • Collaborative localization and mapping
  • Network localization
  • Distributed localization
  • Indoor localization
  • Underwater localization
  • Ad hoc or opportunistic localization
  • Relay network localization
  • Multi-static sonar localization and tracking
  • Energy-efficient localization and tracking
  • Novel applications of localization and tracking
  • Survey of localization and tracking technologies

Dr. Marko Beko
Dr. Slavisa Tomic
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Sensor and Actuator Networks is an international peer-reviewed open access quarterly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Published Papers (7 papers)

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Editorial

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Open AccessEditorial
Special Issue: Localization in Wireless Sensor Networks
J. Sens. Actuator Netw. 2020, 9(1), 14; https://doi.org/10.3390/jsan9010014 - 27 Feb 2020
Abstract
Recent and continuous development of mobile computing and user-centric applications has led to a requirement for accurate and low-cost localization and tracking systems [...] Full article
(This article belongs to the Special Issue Localization in Wireless Sensor Networks)

Research

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Open AccessArticle
Characterization of the Log-Normal Model for Received Signal Strength Measurements in Real Wireless Sensor Networks
J. Sens. Actuator Netw. 2020, 9(1), 12; https://doi.org/10.3390/jsan9010012 - 09 Feb 2020
Cited by 1
Abstract
Using the classical received signal strength (RSS)-distance log-normal model in wireless sensor network (WSN) applications poses a series of characteristic challenges derived from (a) the model’s structural limitations when it comes to explaining real observations, (b) the inherent hardware (HW) variability typically encountered [...] Read more.
Using the classical received signal strength (RSS)-distance log-normal model in wireless sensor network (WSN) applications poses a series of characteristic challenges derived from (a) the model’s structural limitations when it comes to explaining real observations, (b) the inherent hardware (HW) variability typically encountered in the low-cost nodes of WSNs, and (c) the inhomogeneity of the deployment environment. The main goal of this article is to better characterize how these factors impact the model parameters, an issue that has received little attention in the literature. For that matter, I qualitatively elaborate on their effects and interplay, and present the results of two quantitative empirical studies showing how much the parameters can vary depending on (a) the nodes used in the model identification and their position in the environment, and (b) the antenna directionality. I further show that the path loss exponent and the reference power can be highly correlated. In view of all this, I argue that real WSN deployments are better represented by random model parameters jointly accounting for HW and local environmental characteristics, rather than by deterministic independent ones. I further argue that taking this variability into account results in more realistic models and plausible results derived from their usage. The article contains example values of the mean and standard deviation of the model parameters, and of the correlation between the path loss exponent and the reference power. These can be used as a guideline in other studies. Given the sensitivity of localization algorithms to the proper model selection and identification demonstrated in the literature, the structural limitations of the log-normal model, the variability of its parameters and their interrelation are all relevant aspects that practitioners need to be aware of when devising optimal localization algorithms for real WSNs that rely on this popular model. Full article
(This article belongs to the Special Issue Localization in Wireless Sensor Networks)
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Open AccessArticle
Performance Comparison of Closed-Form Least Squares Algorithms for Hyperbolic 3-D Positioning
J. Sens. Actuator Netw. 2020, 9(1), 2; https://doi.org/10.3390/jsan9010002 - 20 Dec 2019
Cited by 2
Abstract
An accurate 3-D wireless local positioning system (LPS) is a highly demanded tool for increasing safety in, e.g., emergency response and security operations. An LPS is an attractive approach that can meet stringent requirements and can achieve acceptable accuracies for a long time [...] Read more.
An accurate 3-D wireless local positioning system (LPS) is a highly demanded tool for increasing safety in, e.g., emergency response and security operations. An LPS is an attractive approach that can meet stringent requirements and can achieve acceptable accuracies for a long time during extended operations in global navigation satellite system (GNSS)-denied environments. In this work, three closed-form (CF) least squares (LS) algorithms were considered, where two of them were adapted to exploit the knowledge about nuisance parameters for accurate 3-D positioning based on time difference of arrival (TDoA) measurements. The algorithms utilize the single set (SS) of the TDoA measurements, an extended SS (ExSS) of the TDoA measurements, or the full set (FS) of the TDoA measurements, and were denoted, respectively, as the CFSSLS, CFExSSLS, and CFFSLS solutions. The performance of the algorithms was investigated with simulations and real-world measurements, where the wireless system transmitters were placed in a quasi-coplanar arrangement. At moderate to high signal-to-noise ratio (SNR) levels, the CFSSLS solution has the best performance, followed by the CFExSSLS solution and then by the CFFSLS solution. At low SNR levels, the CFFSLS algorithm outperformed the other two algorithms. Both the CFSSLS and CFFSLS solutions estimate nuisance parameters that are utilized in refining the vertical position estimate of the receiver. The CFFSLS solution delivers more accurate refined vertical position estimates since it utilizes more nuisance parameters, i.e., more information. The experimental results confirmed the simulation study in which the CFFSLS algorithm outperformed the other two algorithms, where the experimental environment was dominated by total non-line-of-sight (NLoS) conditions and low SNR levels at the receiver to be located. Therefore, it is recommended to use the FS TDoA measurements for 3-D positioning in bad signal conditions, such as high noise levels and NLoS propagation. Full article
(This article belongs to the Special Issue Localization in Wireless Sensor Networks)
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Open AccessArticle
Hybrid TOA/RSS Range-Based Localization with Self-Calibration in Asynchronous Wireless Networks
J. Sens. Actuator Netw. 2019, 8(2), 31; https://doi.org/10.3390/jsan8020031 - 24 May 2019
Cited by 2
Abstract
The paper addresses the problem of localization based on hybrid received signal strength (RSS) and time of arrival (TOA) measurements, in the presence of synchronization errors among all the nodes in a wireless network, and assuming all parameters are unknown. In most existing [...] Read more.
The paper addresses the problem of localization based on hybrid received signal strength (RSS) and time of arrival (TOA) measurements, in the presence of synchronization errors among all the nodes in a wireless network, and assuming all parameters are unknown. In most existing schemes, in fact, knowledge of the model parameters is postulated to reduce the high dimensionality of the cost functions involved in the position estimation process. However, such parameters depend on the operational wireless context, and change over time due to the presence of dynamic obstacles and other modification of the environment. Therefore, they should be adaptively estimated “on the field”, with a procedure that must be as simple as possible in order to suit multiple real-time re-calibrations, even in low-cost applications, without requiring human intervention. Unfortunately, the joint maximum likelihood (ML) position estimator for this problem does not admit a closed-form solution, and numerical optimization is practically unfeasible due to the large number of nuisance parameters. To circumvent such issues, a novel two-step algorithm with reduced complexity is proposed: A first calibration phase exploits nodes in known positions to estimate the unknown RSS and TOA model parameters; then, in a second localization step, an hybrid TOA/RSS range estimator is combined with an iterative least-squares procedure to finally estimate the unknown target position. The results show that the proposed hybrid TOA/RSS localization approach outperformed state-of-the-art competitors and, remarkably, achieved almost the same accuracy of the joint ML benchmark but with a significantly lower computational cost. Full article
(This article belongs to the Special Issue Localization in Wireless Sensor Networks)
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Open AccessArticle
Estimating Directional Data From Network Topology for Improving Tracking Performance
J. Sens. Actuator Netw. 2019, 8(2), 30; https://doi.org/10.3390/jsan8020030 - 20 May 2019
Cited by 4
Abstract
This work proposes a novel approach for tracking a moving target in non-line-of-sight (NLOS) environments based on range estimates extracted from received signal strength (RSS) and time of arrival (TOA) measurements. By exploiting the known architecture of reference points to act as an [...] Read more.
This work proposes a novel approach for tracking a moving target in non-line-of-sight (NLOS) environments based on range estimates extracted from received signal strength (RSS) and time of arrival (TOA) measurements. By exploiting the known architecture of reference points to act as an improper antenna array and the range estimates, angle of arrival (AOA) of the signal emitted by the target is first estimated at each reference point. We then show how to take advantage of these angle estimates to convert the problem into a more convenient, polar space, where a linearization of the measurement models is easily achieved. The derived linear model serves as the main building block on top of which prior knowledge acquired during the movement of the target is incorporated by adapting a Kalman filter (KF). The performance of the proposed approach was assessed through computer simulations, which confirmed its effectiveness in combating the negative effect of NLOS bias and superiority in comparison with its naive counterpart, which does not take prior knowledge into consideration. Full article
(This article belongs to the Special Issue Localization in Wireless Sensor Networks)
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Open AccessFeature PaperArticle
A Lightweight Localization Solution for Small, Low Resources WSNs
J. Sens. Actuator Netw. 2019, 8(2), 26; https://doi.org/10.3390/jsan8020026 - 05 May 2019
Cited by 2
Abstract
The increasing demand for location-dependent services in wireless sensor networks (WSNs) calls for solutions capable of handling the diversified demands and the unique challenges presented in WSNs. In most applications, nodes need to determine their locations in a reliable manner while operating under [...] Read more.
The increasing demand for location-dependent services in wireless sensor networks (WSNs) calls for solutions capable of handling the diversified demands and the unique challenges presented in WSNs. In most applications, nodes need to determine their locations in a reliable manner while operating under stringent constraints in computation, communication, and energy resources. This paper offers a novel solution to bridge the gap between the high accuracy demand and low resources available for range-based localization. We propose KickLoc, a fully distributed scheme, which considers the uncertainty of the distance measurements to minimize localization errors introduced from the range measurement, and leverages information from all neighboring nodes for better position estimations. Our work is evaluated via extensive simulations, with comparisons to other well-known localization schemes, and the Cramér-Rao lower bound (CRLB). In addition, we implement and evaluate the proposed system on sensor platforms with different range measurement mechanisms. The results show that this localization solution outperforms existing methods in various scenarios, while remains lightweight and suitable for small, low resources WSNs. Full article
(This article belongs to the Special Issue Localization in Wireless Sensor Networks)
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Open AccessArticle
Development and Experimental Evaluation of a Low-Cost Cooperative UAV Localization Network Prototype
J. Sens. Actuator Netw. 2018, 7(4), 42; https://doi.org/10.3390/jsan7040042 - 20 Sep 2018
Cited by 6
Abstract
Precise localization is one of the key requirements in the deployment of UAVs (Unmanned Aerial Vehicles) for any application including precision mapping, surveillance, assisted navigation, search and rescue. The need for precise positioning is even more relevant with the increasing automation in UAVs [...] Read more.
Precise localization is one of the key requirements in the deployment of UAVs (Unmanned Aerial Vehicles) for any application including precision mapping, surveillance, assisted navigation, search and rescue. The need for precise positioning is even more relevant with the increasing automation in UAVs and growing interest in commercial UAV applications such as transport and delivery. In the near future, the airspace is expected to be occupied with a large number of unmanned as well as manned aircraft, a majority of which are expected to be operating autonomously. This paper develops a new cooperative localization prototype that utilizes information sharing among UAVs and static anchor nodes for precise positioning of the UAVs. The UAVs are retrofitted with low-cost sensors including a camera, GPS receiver, UWB (Ultra Wide Band) radio and low-cost inertial sensors. The performance of the low-cost prototype is evaluated in real-world conditions in partially and obscured GNSS (Global Navigation Satellite Systems) environments. The performance is analyzed for both centralized and distributed cooperative network designs. It is demonstrated that the developed system is capable of achieving navigation grade (2–4 m) accuracy in partially GNSS denied environments, provided a consistent communication in the cooperative network is available. Furthermore, this paper provides experimental validation that information sharing is beneficial to improve positioning performance even in ideal GNSS environments. The experiments demonstrate that the major challenges for low-cost cooperative networks are consistent connectivity among UAV platforms and sensor synchronization. Full article
(This article belongs to the Special Issue Localization in Wireless Sensor Networks)
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