Previous Issue

E-Mail Alert

Add your e-mail address to receive forthcoming issues of this journal:

Journal Browser

Journal Browser

Table of Contents

Sensors, Volume 19, Issue 2 (January-2 2019)

  • Issues are regarded as officially published after their release is announced to the table of contents alert mailing list.
  • You may sign up for e-mail alerts to receive table of contents of newly released issues.
  • PDF is the official format for papers published in both, html and pdf forms. To view the papers in pdf format, click on the "PDF Full-text" link, and use the free Adobe Readerexternal link to open them.
Cover Story (view full-size image) Thrusters play an important role in the motion control of amphibious spherical robots. A thrust [...] Read more.
View options order results:
result details:
Displaying articles 1-140
Export citation of selected articles as:
Open AccessArticle Acoustic Stimulation by Shunt-Diode Pre-Linearizer using Very High Frequency Piezoelectric Transducer for Cancer Therapeutics
Sensors 2019, 19(2), 357; https://doi.org/10.3390/s19020357 (registering DOI)
Received: 26 November 2018 / Revised: 4 January 2019 / Accepted: 14 January 2019 / Published: 16 January 2019
PDF Full-text (1410 KB)
Abstract
In this paper, we proposed cancer cell acoustic stimulation by shunt-diode pre-linearizer scheme using a very high frequency (≥100 MHz) piezoelectric transducer. To verify the concept of our proposed scheme, we performed pulse-echo detection, and accessed therapeutic effects of human cervical cancer cells
[...] Read more.
In this paper, we proposed cancer cell acoustic stimulation by shunt-diode pre-linearizer scheme using a very high frequency (≥100 MHz) piezoelectric transducer. To verify the concept of our proposed scheme, we performed pulse-echo detection, and accessed therapeutic effects of human cervical cancer cells exposed to acoustic stimulation experiments using 100 MHz focused piezoelectric transducer triggered by PA with and without the proposed shunt-diode pre-linearizer scheme. In the pulse-echo detection responses, the peak-to-peak voltage of the echo signal when using the PA with shunt-diode pre-linearizer (49.79 mV) was higher than that when using the PA alone (29.87 mV). In the experimental results, the cell densities of cancer cells on Day 4 when using no acoustic stimulation (control group), the very high-frequency piezoelectric transducer triggered by PA only and PA combined with proposed pre-linearizer schemes (1 V and 5 V DC bias voltages) showed 100%, 92.8 ± 4.2%, 84.2 ± 4.6%, and 78 ± 2.9%, respectively. Therefore, we confirmed that the shunt-diode pre-linearizer could improve the performances of the pulse signals of the PA, thus, enabling better therapeutic stimulation performances for cancer cell suppression. Full article
Open AccessArticle Distributed Fiber Optics Sensing and Coda Wave Interferometry Techniques for Damage Monitoring in Concrete Structures
Sensors 2019, 19(2), 356; https://doi.org/10.3390/s19020356 (registering DOI)
Received: 17 December 2018 / Revised: 10 January 2019 / Accepted: 11 January 2019 / Published: 16 January 2019
PDF Full-text (8761 KB)
Abstract
The assessment of Coda Wave Interferometry (CWI) and Distributed Fiber Optics Sensing (DFOS) techniques for the detection of damages in a laboratory size reinforced concrete beam is presented in this paper. The sensitivity of these two novel techniques to micro cracks is discussed
[...] Read more.
The assessment of Coda Wave Interferometry (CWI) and Distributed Fiber Optics Sensing (DFOS) techniques for the detection of damages in a laboratory size reinforced concrete beam is presented in this paper. The sensitivity of these two novel techniques to micro cracks is discussed and compared to standard traditional sensors. Moreover, the capacity of a DFOS technique to localize cracks and quantify crack openings is also assessed. The results show that the implementation of CWI and DFOS techniques allow the detection of early subtle changes in reinforced concrete structures until crack formation. With their ability to quantify the crack opening, following early detection and localization, DFOS techniques can achieve more effective monitoring of reinforced concrete structures. Contrary to discrete sensors, CWI and DFOS techniques cover larger areas and thus provide more efficient infrastructures asset management and maintenance operations throughout the lifetime of the structure. Full article
(This article belongs to the Section Physical Sensors)
Open AccessArticle Metasurfaces for Advanced Sensing and Diagnostics
Sensors 2019, 19(2), 355; https://doi.org/10.3390/s19020355 (registering DOI)
Received: 30 November 2018 / Revised: 24 December 2018 / Accepted: 9 January 2019 / Published: 16 January 2019
PDF Full-text (676 KB)
Abstract
Interest in sensors and their applications is rapidly evolving, mainly driven by the huge demand of technologies whose ultimate purpose is to improve and enhance health and safety. Different electromagnetic technologies have been recently used and achieved good performances. Despite the plethora of
[...] Read more.
Interest in sensors and their applications is rapidly evolving, mainly driven by the huge demand of technologies whose ultimate purpose is to improve and enhance health and safety. Different electromagnetic technologies have been recently used and achieved good performances. Despite the plethora of literature, limitations are still present: limited response control, narrow bandwidth, and large dimensions. MetaSurfaces, artificial 2D materials with peculiar electromagnetic properties, can help to overcome such issues. In this paper, a generic tool to model, design, and manufacture MetaSurface sensors is developed. First, their properties are evaluated in terms of impedance and constitutive parameters. Then, they are linked to the structure physical dimensions. Finally, the proposed method is applied to realize devices for advanced sensing and medical diagnostic applications: glucose measurements, cancer stage detection, water content recognition, and blood oxygen level analysis. The proposed method paves a new way to realize sensors and control their properties at will. Most importantly, it has great potential to be used for many other practical applications, beyond sensing and diagnostics. Full article
(This article belongs to the Special Issue Biomedical Infrared Imaging: From Sensors to Applications)
Open AccessArticle Blind Estimation of the PN Sequence of A DSSS Signal Using A Modified Online Unsupervised Learning Machine
Sensors 2019, 19(2), 354; https://doi.org/10.3390/s19020354 (registering DOI)
Received: 26 November 2018 / Revised: 3 January 2019 / Accepted: 11 January 2019 / Published: 16 January 2019
PDF Full-text (433 KB)
Abstract
Direct sequence spread spectrum (DSSS) signals are now widely used in air and underwater acoustic communications. A receiver which does not know the pseudo-random (PN) sequence cannot demodulate the DSSS signal. In this paper, firstly, the principle of principal component analysis (PCA) for
[...] Read more.
Direct sequence spread spectrum (DSSS) signals are now widely used in air and underwater acoustic communications. A receiver which does not know the pseudo-random (PN) sequence cannot demodulate the DSSS signal. In this paper, firstly, the principle of principal component analysis (PCA) for PN sequence estimation of the DSSS signal is analyzed, then a modified online unsupervised learning machine (LEAP) is introduced for PCA. Compared with the original LEAP, the modified LEAP has the following improvements: (1) By normalizing the system state transition matrices, the modified LEAP can obtain better robustness when the training errors occur; (2) with using variable learning steps instead of a fixed one, the modified LEAP not only converges faster but also has excellent estimation performance. When the modified LEAP is converging, we can utilize the network connection weights which are the eigenvectors of the autocorrelation matrix of the DSSS signal to estimate the PN sequence. Due to the phase ambiguity of the eigenvectors, a novel approach which is based on the properties of the PN sequence is proposed here to exclude the wrong estimated PN sequences. Simulation results showed that the methods mentioned above can estimate the PN sequence rapidly and robustly, even when the DSSS signal is far below the noise level. Full article
Open AccessArticle Smart Meeting Room Usage Information and Prediction by Modelling Occupancy Profiles
Sensors 2019, 19(2), 353; https://doi.org/10.3390/s19020353 (registering DOI)
Received: 14 December 2018 / Revised: 10 January 2019 / Accepted: 15 January 2019 / Published: 16 January 2019
PDF Full-text (1257 KB)
Abstract
The monitoring of small houses and rooms has become possible due to the advances in IoT sensors, actuators and low power communication protocols in the last few years. As buildings are one of the biggest energy consuming entities, monitoring them has great interest
[...] Read more.
The monitoring of small houses and rooms has become possible due to the advances in IoT sensors, actuators and low power communication protocols in the last few years. As buildings are one of the biggest energy consuming entities, monitoring them has great interest for trying to avoid non-necessary energy waste. Moreover, human behaviour has been reported as being the main discrepancy source between energy usage simulations and real usage, so the ability to monitor and predict actions as opening windows, using rooms, etc. is gaining attention to develop stronger models which may lead to reduce the overall energy consumption of buildings, considering buildings thermal inertia and additional capabilities. In this paper, a case study is described in which four meeting rooms have been monitored to obtain information about the usage of the rooms and later use it to predict their future usage. The results show the possibility to deploy a simple and non-intrusive sensing system whose output could be used to develop advanced control strategies. Full article
Open AccessArticle Modeling of Rate-Independent and Symmetric Hysteresis Based on Madelung’s Rules
Sensors 2019, 19(2), 352; https://doi.org/10.3390/s19020352 (registering DOI)
Received: 16 December 2018 / Revised: 13 January 2019 / Accepted: 15 January 2019 / Published: 16 January 2019
PDF Full-text (3838 KB) | HTML Full-text | XML Full-text
Abstract
Hysteresis is a kind of nonlinearity with memory, which is usually unwanted in practice. Many phenomenological models have been proposed to describe the observed hysteresis. For instance, the Prandtl-Ishlinskii (PI) model, which consists of several backlash operators, is the most widely used. On
[...] Read more.
Hysteresis is a kind of nonlinearity with memory, which is usually unwanted in practice. Many phenomenological models have been proposed to describe the observed hysteresis. For instance, the Prandtl-Ishlinskii (PI) model, which consists of several backlash operators, is the most widely used. On the other hand, the well-known Madelung’s rules are always used to validate hysteresis models. It is worth pointing out that the PI model obeys Madelung’s rules. In this paper, instead of considering these rules as criteria, we propose a modeling method for symmetric hysteresis by directly constructing the trajectory based on Madelung’s rules. In the proposed method, turning points are recorded and wiped out according to the input value. After the implementation of the recording and wiping-out mechanisms, the curve which the current trajectory moves along can be determined and then the trajectory can be described. Furthermore, the relationship between the proposed method and the PI model is also investigated. The effectiveness of the presented method is validated by simulation and experimental results. Full article
(This article belongs to the Section Physical Sensors)
Figures

Figure 1

Open AccessArticle Embracing the Future Internet of Things
Sensors 2019, 19(2), 351; https://doi.org/10.3390/s19020351 (registering DOI)
Received: 15 December 2018 / Revised: 10 January 2019 / Accepted: 11 January 2019 / Published: 16 January 2019
PDF Full-text (3205 KB) | Supplementary Files
Abstract
All of the objects in the real world are envisioned to be connected and/or represented, through an infrastructure layer, in the virtual world of the Internet, becoming Things with status information. Services are then using the available data from this Internet-of-Things (IoT) for
[...] Read more.
All of the objects in the real world are envisioned to be connected and/or represented, through an infrastructure layer, in the virtual world of the Internet, becoming Things with status information. Services are then using the available data from this Internet-of-Things (IoT) for various social and economical benefits which explain its extreme broad usage in very heterogeneous fields. Domain administrations of diverse areas of application developed and deployed their own IoT systems and services following disparate standards and architecture approaches that created a fragmentation of things, infrastructures and services in vertical IoT silos. Coordination and cooperation among IoT systems are the keys to build “smarter” IoT services boosting the benefits magnitude. This article analyses the technical trends of the future IoT world based on the current limitations of the IoT systems and the capability requirements. We propose a hyper-connected IoT framework in which “things” are connected to multiple interdependent services and describe how this framework enables the development of future applications. Moreover, we discuss the major limitations in today’s IoT and highlight the required capabilities in the future. We illustrate this global vision with the help of two concrete instances of the hyper-connected IoT in smart cities and autonomous driving scenarios. Finally, we analyse the trends in the number of connected “things” and point out open issues and future challenges. The proposed hyper-connected IoT framework is meant to scale the benefits of IoT from local to global. Full article
Open AccessArticle Real-Time Underwater Image Recognition with FPGA Embedded System for Convolutional Neural Network
Sensors 2019, 19(2), 350; https://doi.org/10.3390/s19020350 (registering DOI)
Received: 28 November 2018 / Revised: 10 January 2019 / Accepted: 11 January 2019 / Published: 16 January 2019
PDF Full-text (1923 KB) | HTML Full-text | XML Full-text
Abstract
The underwater environment is still unknown for humans, so the high definition camera is an important tool for data acquisition at short distances underwater. Due to insufficient power, the image data collected by underwater submersible devices cannot be analyzed in real time. Based
[...] Read more.
The underwater environment is still unknown for humans, so the high definition camera is an important tool for data acquisition at short distances underwater. Due to insufficient power, the image data collected by underwater submersible devices cannot be analyzed in real time. Based on the characteristics of Field-Programmable Gate Array (FPGA), low power consumption, strong computing capability, and high flexibility, we design an embedded FPGA image recognition system on Convolutional Neural Network (CNN). By using two technologies of FPGA, parallelism and pipeline, the parallelization of multi-depth convolution operations is realized. In the experimental phase, we collect and segment the images from underwater video recorded by the submersible. Next, we join the tags with the images to build the training set. The test results show that the proposed FPGA system achieves the same accuracy as the workstation, and we get a frame rate at 25 FPS with the resolution of 1920 × 1080. This meets our needs for underwater identification tasks. Full article
(This article belongs to the Special Issue Smart Ocean: Emerging Research Advances, Prospects and Challenges)
Figures

Figure 1

Open AccessArticle A Novel Method for Extrinsic Calibration of Multiple RGB-D Cameras Using Descriptor-Based Patterns
Sensors 2019, 19(2), 349; https://doi.org/10.3390/s19020349 (registering DOI)
Received: 2 December 2018 / Revised: 21 December 2018 / Accepted: 14 January 2019 / Published: 16 January 2019
PDF Full-text (8043 KB) | HTML Full-text | XML Full-text
Abstract
This paper presents a novel method to estimate the relative poses between RGB-D cameras with minimal overlapping fields of view. This calibration problem is relevant to applications such as indoor 3D mapping and robot navigation that can benefit from a wider field of
[...] Read more.
This paper presents a novel method to estimate the relative poses between RGB-D cameras with minimal overlapping fields of view. This calibration problem is relevant to applications such as indoor 3D mapping and robot navigation that can benefit from a wider field of view using multiple RGB-D cameras. The proposed approach relies on descriptor-based patterns to provide well-matched 2D keypoints in the case of a minimal overlapping field of view between cameras. Integrating the matched 2D keypoints with corresponding depth values, a set of 3D matched keypoints are constructed to calibrate multiple RGB-D cameras. Experiments validated the accuracy and efficiency of the proposed calibration approach. Full article
(This article belongs to the Special Issue Depth Sensors and 3D Vision)
Figures

Figure 1

Open AccessArticle A Method for Analyzing the Impact of Intra-System and Inter-System Interference on DME Based on Queueing Theory
Sensors 2019, 19(2), 348; https://doi.org/10.3390/s19020348 (registering DOI)
Received: 26 November 2018 / Revised: 1 January 2019 / Accepted: 14 January 2019 / Published: 16 January 2019
PDF Full-text (816 KB) | HTML Full-text | XML Full-text
Abstract
In order to use Distance Measuring Equipment (DME) properly, the impact of intra-system and inter-system electromagnetic interference must be analyzed firstly. However, the error of interference analysis using present methods based on pulse overlap is large when there are more aircraft. The aim
[...] Read more.
In order to use Distance Measuring Equipment (DME) properly, the impact of intra-system and inter-system electromagnetic interference must be analyzed firstly. However, the error of interference analysis using present methods based on pulse overlap is large when there are more aircraft. The aim of this article is to study a method of analyzing interference on DME whether the number of aircraft is small or not. According to the flow chart of DME signal, we studied the limitations of present methods; then constructed a model of analyzing the collision between duration of desired signal and dead time of receiver based on M/M/1/0 queueing system. Combing this model with other methods, we present a analytic model of analyzing intra-system and inter-system interference on DME. Using this analytic model, we analyzed reply efficiency (RE) and capacity of DME under intra-system and Joint Tactical Information Distribution System (JTIDS) interference. The result shows that the calculation for the probability of overlap between DME dead time and subsequent signals using queueing model agrees well with simulation. Consequently, the analytic model is more accurate than using a single method to analyze interference on DME. Full article
Figures

Figure 1

Open AccessArticle Low-Cost and Data Anonymised City Traffic Flow Data Collection to Support Intelligent Traffic System
Sensors 2019, 19(2), 347; https://doi.org/10.3390/s19020347 (registering DOI)
Received: 14 December 2018 / Revised: 10 January 2019 / Accepted: 13 January 2019 / Published: 16 January 2019
PDF Full-text (2195 KB)
Abstract
There are many methods of collecting traffic flow data, especially using smart phone apps. However, few current solutions balance the need for collecting full route data whilst respecting privacy and remaining low-cost. This project looks into the creation of a wireless sensor network
[...] Read more.
There are many methods of collecting traffic flow data, especially using smart phone apps. However, few current solutions balance the need for collecting full route data whilst respecting privacy and remaining low-cost. This project looks into the creation of a wireless sensor network (WSN) that can balance these requirements in an attempt to negate some of the concerns that come with this type of technology. Our proposed system only collects location data within a defined city area. This data is collected with a randomized identifier, which limits repeated identification of the source vehicle and its occupants. Data collected is shared between vehicle and roadside base stations when the two are in range. To deal with the fluid nature of this scenario, a purposely designed Media Access Control (MAC) protocol was designed and implemented using the beacon-slotted ALOHA (Advocates of Linux Open-source Hawaii Association) mechanism. Full article
(This article belongs to the Special Issue Internet of Things and Machine-to-Machine Communication)
Open AccessArticle Aspect Entropy Extraction Using Circular SAR Data and Scattering Anisotropy Analysis
Sensors 2019, 19(2), 346; https://doi.org/10.3390/s19020346
Received: 27 November 2018 / Revised: 13 January 2019 / Accepted: 15 January 2019 / Published: 16 January 2019
PDF Full-text (5582 KB) | HTML Full-text | XML Full-text
Abstract
In conventional synthetic aperture radar (SAR) working modes, targets are assumed isotropic because the viewing angle is small. However, most man-made targets are anisotropic. Therefore, anisotropy should be considered when the viewing angle is large. From another perspective, anisotropy is also a useful
[...] Read more.
In conventional synthetic aperture radar (SAR) working modes, targets are assumed isotropic because the viewing angle is small. However, most man-made targets are anisotropic. Therefore, anisotropy should be considered when the viewing angle is large. From another perspective, anisotropy is also a useful feature. Circular SAR (CSAR) can detect the scattering variation under different azimuthal look angles by a 360-degree observation. Different targets usually have varying degrees of anisotropy, which aids in target discrimination. However, there is no effective method to quantify the degree of anisotropy. In this paper, aspect entropy is presented as a descriptor of the scattering anisotropy. The range of aspect entropy is from 0 to 1, which corresponds to anisotropic to isotropic. First, the method proposed extracts aspect entropy at the pixel level. Since the aspect entropy of pixels can discriminate isotropic and anisotropic scattering, the method prescreens the target from the isotropic clutters. Next, the method extracts aspect entropy at the target level. The aspect entropy of targets can discriminate between different types of targets. Then, the effect of noise on aspect entropy extraction is analyzed and a denoising method is proposed. The Gotcha public release dataset, an X-band circular SAR data, is used to validate the method and the discrimination capability of aspect entropy. Full article
(This article belongs to the Special Issue Synthetic Aperture Radar (SAR) Techniques and Applications)
Figures

Figure 1

Open AccessArticle Skull’s Photoacoustic Attenuation and Dispersion Modeling with Deterministic Ray-Tracing: Towards Real-Time Aberration Correction
Sensors 2019, 19(2), 345; https://doi.org/10.3390/s19020345
Received: 7 December 2018 / Revised: 10 January 2019 / Accepted: 14 January 2019 / Published: 16 January 2019
PDF Full-text (1679 KB) | HTML Full-text | XML Full-text
Abstract
Although transcranial photoacoustic imaging has been previously investigated by several groups, there are many unknowns about the distorting effects of the skull due to the impedance mismatch between the skull and underlying layers. The current computational methods based on finite-element modeling are slow,
[...] Read more.
Although transcranial photoacoustic imaging has been previously investigated by several groups, there are many unknowns about the distorting effects of the skull due to the impedance mismatch between the skull and underlying layers. The current computational methods based on finite-element modeling are slow, especially in the cases where fine grids are defined for a large 3-D volume. We develop a very fast modeling/simulation framework based on deterministic ray-tracing. The framework considers a multilayer model of the medium, taking into account the frequency-dependent attenuation and dispersion effects that occur in wave reflection, refraction, and mode conversion at the skull surface. The speed of the proposed framework is evaluated. We validate the accuracy of the framework using numerical phantoms and compare its results to k-Wave simulation results. Analytical validation is also performed based on the longitudinal and shear wave transmission coefficients. We then simulated, using our method, the major skull-distorting effects including amplitude attenuation, time-domain signal broadening, and time shift, and confirmed the findings by comparing them to several ex vivo experimental results. It is expected that the proposed method speeds up modeling and quantification of skull tissue and allows the development of transcranial photoacoustic brain imaging. Full article
(This article belongs to the Special Issue Biomedical Imaging Using Photoacoustic Technology)
Figures

Figure 1

Open AccessArticle Virtual View Generation Based on 3D-Dense-Attentive GAN Networks
Sensors 2019, 19(2), 344; https://doi.org/10.3390/s19020344
Received: 27 November 2018 / Revised: 8 January 2019 / Accepted: 9 January 2019 / Published: 16 January 2019
PDF Full-text (22306 KB) | HTML Full-text | XML Full-text
Abstract
A binocular vision system is a common perception component of an intelligent vehicle. Benefiting from the biomimetic structure, the system is simple and effective. Which are extremely snesitive on external factors, especially missing vision signals. In this paper, a virtual view-generation algorithm based
[...] Read more.
A binocular vision system is a common perception component of an intelligent vehicle. Benefiting from the biomimetic structure, the system is simple and effective. Which are extremely snesitive on external factors, especially missing vision signals. In this paper, a virtual view-generation algorithm based on generative adversarial networks (GAN) is proposed to enhance the robustness of binocular vision systems. The proposed model consists of two parts: generative network and discriminator network. To improve the quality of a virtual view, a generative network structure based on 3D convolutional neural networks (3D-CNN) and attentive mechanisms is introduced to extract the time-series features from image sequences. To avoid gradient vanish during training, the dense block structure is utilized to improve the discriminator network. Meanwhile, three kinds of image features, including image edge, depth map and optical flow are extracted to constrain the supervised training of model. The final results on KITTI and Cityscapes datasets demonstrate that our algorithm outperforms conventional methods, and the missing vision signal can be replaced by a generated virtual view. Full article
(This article belongs to the Section Intelligent Sensors)
Figures

Figure 1

Open AccessArticle Algorithm Design for Edge Detection of High-Speed Moving Target Image under Noisy Environment
Sensors 2019, 19(2), 343; https://doi.org/10.3390/s19020343
Received: 20 November 2018 / Revised: 10 January 2019 / Accepted: 10 January 2019 / Published: 16 January 2019
PDF Full-text (20070 KB) | HTML Full-text | XML Full-text
Abstract
For some measurement and detection applications based on video (sequence images), if the exposure time of camera is not suitable with the motion speed of the photographed target, fuzzy edges will be produced in the image, and some poor lighting condition will aggravate
[...] Read more.
For some measurement and detection applications based on video (sequence images), if the exposure time of camera is not suitable with the motion speed of the photographed target, fuzzy edges will be produced in the image, and some poor lighting condition will aggravate this edge blur phenomena. Especially, the existence of noise in industrial field environment makes the extraction of fuzzy edges become a more difficult problem when analyzing the posture of a high-speed moving target. Because noise and edge are always both the kind of high-frequency information, it is difficult to make trade-offs only by frequency bands. In this paper, a noise-tolerant edge detection method based on the correlation relationship between layers of wavelet transform coefficients is proposed. The goal of the paper is not to recover a clean image from a noisy observation, but to make a trade-off judgment for noise and edge signal directly according to the characteristics of wavelet transform coefficients, to realize the extraction of edge information from a noisy image directly. According to the wavelet coefficients tree and the Lipschitz exponent property of noise, the idea of neural network activation function is adopted to design the activation judgment method of wavelet coefficients. Then the significant wavelet coefficients can be retained. At the same time, the non-significant coefficients were removed according to the method of judgment of isolated coefficients. On the other hand, based on the design of Daubechies orthogonal compactly-supported wavelet filter, rational coefficients wavelet filters can be designed by increasing free variables. By reducing the vanishing moments of wavelet filters, more high-frequency information can be retained in the wavelet transform fields, which is benefit to the application of edge detection. For a noisy image of high-speed moving targets with fuzzy edges, by using the length 8-4 rational coefficients biorthogonal wavelet filters and the algorithm proposed in this paper, edge information could be detected clearly. Results of multiple groups of comparative experiments have shown that the edge detection effect of the proposed algorithm in this paper has the obvious superiority. Full article
Figures

Figure 1

Open AccessArticle Pose Estimation for Straight Wing Aircraft Based on Consistent Line Clustering and Planes Intersection
Sensors 2019, 19(2), 342; https://doi.org/10.3390/s19020342
Received: 27 December 2018 / Revised: 10 January 2019 / Accepted: 11 January 2019 / Published: 16 January 2019
PDF Full-text (5411 KB) | HTML Full-text | XML Full-text
Abstract
Aircraft pose estimation is a necessary technology in aerospace applications, and accurate pose parameters are the foundation for many aerospace tasks. In this paper, we propose a novel pose estimation method for straight wing aircraft without relying on 3D models or other datasets,
[...] Read more.
Aircraft pose estimation is a necessary technology in aerospace applications, and accurate pose parameters are the foundation for many aerospace tasks. In this paper, we propose a novel pose estimation method for straight wing aircraft without relying on 3D models or other datasets, and two widely separated cameras are used to acquire the pose information. Because of the large baseline and long-distance imaging, feature point matching is difficult and inaccurate in this configuration. In our method, line features are extracted to describe the structure of straight wing aircraft in images, and pose estimation is performed based on the common geometry constraints of straight wing aircraft. The spatial and length consistency of the line features is used to exclude irrelevant line segments belonging to the background or other parts of the aircraft, and density-based parallel line clustering is utilized to extract the aircraft’s main structure. After identifying the orientation of the fuselage and wings in images, planes intersection is used to estimate the 3D localization and attitude of the aircraft. Experimental results show that our method estimates the aircraft pose accurately and robustly. Full article
(This article belongs to the Special Issue Visual Sensors)
Figures

Figure 1

Open AccessArticle IB-MAC: Transmission Latency-Aware MAC for Electro-Magnetic Intra-Body Communications
Sensors 2019, 19(2), 341; https://doi.org/10.3390/s19020341
Received: 14 December 2018 / Revised: 11 January 2019 / Accepted: 12 January 2019 / Published: 16 January 2019
PDF Full-text (1634 KB) | HTML Full-text | XML Full-text
Abstract
Intra-body Communication (IBC) is a communication method using the human body as a communication medium, in which body-attached devices exchange electro-magnetic (EM) wave signals with each other. The fact that our human body consists of water and electrolytes allows such communication methods to
[...] Read more.
Intra-body Communication (IBC) is a communication method using the human body as a communication medium, in which body-attached devices exchange electro-magnetic (EM) wave signals with each other. The fact that our human body consists of water and electrolytes allows such communication methods to be possible. Such a communication technology can be used to design novel body area networks that are secure and resilient towards external radio interference. While being an attractive technology for enabling new applications for human body-centered ubiquitous applications, network protocols for IBC systems is yet under-explored. The IEEE 802.15.6 standards present physical and medium access control (MAC) layer protocols for IBC, but, due to many simplifications, we find that its MAC protocol is limited in providing an environment to enable high data rate applications. This work, based on empirical EM wave propagation measurements made for the human body communication channel, presents IB-MAC, a centralized Time-division multiple access (TDMA) protocol that takes in consideration the transmission latency the body channel induces. Our results, in which we use an event-based simulator to compare the performance of IB-MAC with two different IEEE 802.15.6 standard-compliant MAC protocols and a state-of-the art TDMA-based MAC protocol for IBC, suggest that IB-MAC is suitable for supporting high data rate applications with comparable radio duty cycle and latency performance. Full article
(This article belongs to the Special Issue Internet of Things and Ubiquitous Sensing)
Figures

Figure 1

Open AccessArticle Optimal Placement of Virtual Masses for Structural Damage Identification
Sensors 2019, 19(2), 340; https://doi.org/10.3390/s19020340
Received: 11 December 2018 / Revised: 13 January 2019 / Accepted: 15 January 2019 / Published: 16 January 2019
PDF Full-text (5004 KB) | HTML Full-text | XML Full-text
Abstract
Adding virtual masses to a structure is an efficient way to generate a large number of natural frequencies for damage identification. The influence of a virtual mass can be expressed by Virtual Distortion Method (VDM) using the response measured by a sensor at
[...] Read more.
Adding virtual masses to a structure is an efficient way to generate a large number of natural frequencies for damage identification. The influence of a virtual mass can be expressed by Virtual Distortion Method (VDM) using the response measured by a sensor at the involved point. The proper placement of the virtual masses can improve the accuracy of damage identification, therefore the problem of their optimal placement is studied in this paper. Firstly, the damage sensitivity matrix of the structure with added virtual masses is built. The Volumetric Maximum Criterion of the sensitivity matrix is established to ensure the mutual independence of measurement points for the optimization of mass placement. Secondly, a method of sensitivity analysis and error analysis is proposed to determine the values of the virtual masses, and then an improved version of the Particle Swarm Optimization (PSO) algorithm is proposed for placement optimization of the virtual masses. Finally, the optimized placement is used to identify the damage of structures. The effectiveness of the proposed method is verified by a numerical simulation of a simply supported beam structure and a truss structure. Full article
(This article belongs to the Special Issue Smart Sensors for Structural Health Monitoring)
Figures

Figure 1

Open AccessArticle Noise Estimation for Image Sensor Based on Local Entropy and Median Absolute Deviation
Sensors 2019, 19(2), 339; https://doi.org/10.3390/s19020339
Received: 29 November 2018 / Revised: 20 December 2018 / Accepted: 28 December 2018 / Published: 16 January 2019
PDF Full-text (9686 KB) | HTML Full-text | XML Full-text
Abstract
Noise estimation for image sensor is a key technique in many image pre-processing applications such as blind de-noising. The existing noise estimation methods for additive white Gaussian noise (AWGN) and Poisson-Gaussian noise (PGN) may underestimate or overestimate the noise level in the situation
[...] Read more.
Noise estimation for image sensor is a key technique in many image pre-processing applications such as blind de-noising. The existing noise estimation methods for additive white Gaussian noise (AWGN) and Poisson-Gaussian noise (PGN) may underestimate or overestimate the noise level in the situation of a heavy textured scene image. To cope with this problem, a novel homogenous block-based noise estimation method is proposed to calculate these noises in this paper. Initially, the noisy image is transformed into the map of local gray statistic entropy (LGSE), and the weakly textured image blocks can be selected with several biggest LGSE values in a descending order. Then, the Haar wavelet-based local median absolute deviation (HLMAD) is presented to compute the local variance of these selected homogenous blocks. After that, the noise parameters can be estimated accurately by applying the maximum likelihood estimation (MLE) to analyze the local mean and variance of selected blocks. Extensive experiments on synthesized noised images are induced and the experimental results show that the proposed method could not only more accurately estimate the noise of various scene images with different noise levels than the compared state-of-the-art methods, but also promote the performance of the blind de-noising algorithm. Full article
(This article belongs to the Special Issue Image Sensors)
Figures

Figure 1

Open AccessArticle Indoor 3-D Localization Based on Received Signal Strength Difference and Factor Graph for Unknown Radio Transmitter
Sensors 2019, 19(2), 338; https://doi.org/10.3390/s19020338
Received: 8 December 2018 / Revised: 14 January 2019 / Accepted: 14 January 2019 / Published: 16 January 2019
PDF Full-text (1141 KB) | HTML Full-text | XML Full-text
Abstract
Accurate localization of the radio transmitter is an important work in radio management. Previous research is more focused on two-dimensional (2-D) scenarios, but the localization of an unknown radio transmitter under three-dimensional (3-D) scenarios has more practical significance. In this paper, we propose
[...] Read more.
Accurate localization of the radio transmitter is an important work in radio management. Previous research is more focused on two-dimensional (2-D) scenarios, but the localization of an unknown radio transmitter under three-dimensional (3-D) scenarios has more practical significance. In this paper, we propose a novel 3-D localization algorithm with received signal strength difference (RSSD) information and factor graph (FG), which is suitable for both line-of-sight (LOS) and non-line-of-sight (NLOS) condition. Considering the stochastic properties of measurement errors caused by the indoor environment, RSSD measurements are processed with mean and variance in the form of Gaussian distribution in the FG framework. A new 3-D RSSD-based FG model is constructed with the relationship between RSSD and location coordinates by local linearization technique. The soft-information computation and iterative process of the proposed model are derived by using the sum-product algorithm. In addition, the impacts of different grid distances and number of signal receivers on positioning accuracy are explored. Finally, the performance of our proposed approach is experimentally evaluated in a real scenario. The results show that the positioning performance of the proposed algorithm is not only superior to the k-nearest neighbors (kNN) algorithm and least square (LS) algorithm, but also it can achieve a mean localization error as low as 1.15 m. Our proposed scheme provides a good solution for the accurate detection of an unknown radio transmitter under indoor 3-D space and has a good application prospect. Full article
(This article belongs to the Special Issue Sensor Fusion and Novel Technologies in Positioning and Navigation)
Figures

Figure 1

Open AccessArticle Determination of the Location and Magnetic Moment of Ferromagnetic Objects Based on the Analysis of Magnetovision Measurements
Sensors 2019, 19(2), 337; https://doi.org/10.3390/s19020337
Received: 19 October 2018 / Revised: 11 January 2019 / Accepted: 13 January 2019 / Published: 16 January 2019
Viewed by 43 | PDF Full-text (3091 KB) | HTML Full-text | XML Full-text
Abstract
This article is concerned with the localization of ferromagnetic objects on the basis of magnetovision measurement analysis. In the presented case, the concept of localization is understood as the indication of the x, y, and z coordinates of the magnetic moment
[...] Read more.
This article is concerned with the localization of ferromagnetic objects on the basis of magnetovision measurement analysis. In the presented case, the concept of localization is understood as the indication of the x, y, and z coordinates of the magnetic moment of the sought object. Magnetovision measurement provides a much simpler, two-dimensional localization of magnetic anomalies compared to existing active and passive mobile devices, largely based on operator knowledge and experience. In addition, the analysis of the obtained magnetovision measurement, by fusing data with a mathematical model, enables a quantitative assessment of the position of an object in space and the determination of the value and spatial orientation of its magnetic moment vector. The detection and localization method was verified using the certified magnetic moment standard. An additional novelty is the inclusion of the influence of the constant gradient of the external field in the model, which corresponds to disturbing the measurement by the influence of large, but distant, objects. The proposed three-dimensional magnetovision measurement method and its analysis enable the determination of the x, y, and z coordinates; the angular position; and the magnetic moment values of unknown magnetic dipoles in real conditions (effects of disturbances generated by other distant objects and background noise), thus precisely detecting and locating the ferromagnetic object. Full article
(This article belongs to the Special Issue Magnetic Sensors)
Figures

Figure 1

Open AccessArticle A Novel Infrared Temperature Measurement with Dual Mode Modulation of Thermopile Sensor
Sensors 2019, 19(2), 336; https://doi.org/10.3390/s19020336
Received: 30 November 2018 / Revised: 14 January 2019 / Accepted: 14 January 2019 / Published: 15 January 2019
Viewed by 121 | PDF Full-text (923 KB)
Abstract
Superior to the traditional infrared temperature sensing architecture including infrared sensor and thermistor, we propose a novel sensing approach based on a single thermopile sensor with dual modes modulation. A switching and sensing circuit is proposed and realized with a chopper amplifier AD8551
[...] Read more.
Superior to the traditional infrared temperature sensing architecture including infrared sensor and thermistor, we propose a novel sensing approach based on a single thermopile sensor with dual modes modulation. A switching and sensing circuit is proposed and realized with a chopper amplifier AD8551 and p-channel MOSFET (PMOS) for switching between detection of thermal radiation and the target and the ambient temperature for compensation. The error of target temperature after temperature compensation is estimated at less than 0.14 °C. Full article
(This article belongs to the Special Issue Selected Papers from IEEE ICKII 2018)
Open AccessArticle Joint Estimation of DOA and Frequency of Multiple Sources with Orthogonal Coprime Arrays
Sensors 2019, 19(2), 335; https://doi.org/10.3390/s19020335
Received: 22 November 2018 / Revised: 3 January 2019 / Accepted: 12 January 2019 / Published: 15 January 2019
Viewed by 98 | PDF Full-text (663 KB)
Abstract
A two-stage method is proposed to jointly estimate the direction-of-arrival (DOA) and carrier frequency (CF) of multiple sources, by using two orthogonal coprime arrays (CPAs). The DOAs of CF-known sources are estimated first by applying a spatial smoothing MUSIC algorithm. The contribution of
[...] Read more.
A two-stage method is proposed to jointly estimate the direction-of-arrival (DOA) and carrier frequency (CF) of multiple sources, by using two orthogonal coprime arrays (CPAs). The DOAs of CF-known sources are estimated first by applying a spatial smoothing MUSIC algorithm. The contribution of these source signals is then removed from the originally received signal by applying an orthogonal complement projector. Next, a joint-ESPRIT algorithm is applied to estimate the DOAs and CFs of the remaining CF-unknown sources. With two orthogonal CPA(5, 6), the RMSE of DOA and CF of applying the proposed method to 30 sources, 13 of which have unknown CF, is less than 1% at SNR > 5 dB. Full article
(This article belongs to the Section Physical Sensors)
Open AccessReview A Survey of Vehicle to Everything (V2X) Testing
Sensors 2019, 19(2), 334; https://doi.org/10.3390/s19020334
Received: 17 December 2018 / Revised: 1 January 2019 / Accepted: 11 January 2019 / Published: 15 January 2019
Viewed by 96 | PDF Full-text (2245 KB) | HTML Full-text | XML Full-text
Abstract
Vehicle to everything (V2X) is a new generation of information and communication technologies that connect vehicles to everything. It not only creates a more comfortable and safer transportation environment, but also has much significance for improving traffic efficiency, and reducing pollution and accident
[...] Read more.
Vehicle to everything (V2X) is a new generation of information and communication technologies that connect vehicles to everything. It not only creates a more comfortable and safer transportation environment, but also has much significance for improving traffic efficiency, and reducing pollution and accident rates. At present, the technology is still in the exploratory stage, and the problems of traffic safety and information security brought about by V2X applications have not yet been fully evaluated. Prior to marketization, we must ensure the reliability and maturity of the technology, which must be rigorously tested and verified. Therefore, testing is an important part of V2X technology. This article focuses on the V2X application requirements and its challenges, the need of testing. Then we also investigate and summarize the testing methods for V2X in the communication process and describe them in detail from the architectural perspective. In addition, we have proposed an end-to-end testing system combining virtual and real environments which can undertake the test task of the full protocol stack. Full article
(This article belongs to the Special Issue Internet of Vehicles)
Figures

Figure 1

Open AccessArticle Automatic Building Extraction from Google Earth Images under Complex Backgrounds Based on Deep Instance Segmentation Network
Sensors 2019, 19(2), 333; https://doi.org/10.3390/s19020333
Received: 11 December 2018 / Revised: 9 January 2019 / Accepted: 13 January 2019 / Published: 15 January 2019
Viewed by 118 | PDF Full-text (1763 KB)
Abstract
Building damage accounts for a high percentage of post-natural disaster assessment. Extracting buildings from optical remote sensing images is of great significance for natural disaster reduction and assessment. Traditional methods mainly are semi-automatic methods which require human-computer interaction or rely on purely human
[...] Read more.
Building damage accounts for a high percentage of post-natural disaster assessment. Extracting buildings from optical remote sensing images is of great significance for natural disaster reduction and assessment. Traditional methods mainly are semi-automatic methods which require human-computer interaction or rely on purely human interpretation. In this paper, inspired by the recently developed deep learning techniques, we propose an improved Mask Region Convolutional Neural Network (Mask R-CNN) method that can detect the rotated bounding boxes of buildings and segment them from very complex backgrounds, simultaneously. The proposed method has two major improvements, making it very suitable to perform building extraction task. Firstly, instead of predicting horizontal rectangle bounding boxes of objects like many other detectors do, we intend to obtain the minimum enclosing rectangles of buildings by adding a new term: the principal directions of the rectangles θ. Secondly, a new layer by integrating advantages of both atrous convolution and inception block is designed and inserted into the segmentation branch of the Mask R-CNN to make the branch to learn more representative features. We test the proposed method on a newly collected large Google Earth remote sensing dataset with diverse buildings and very complex backgrounds. Experiments demonstrate that it can obtain promising results. Full article
(This article belongs to the Special Issue Deep Learning Remote Sensing Data)
Open AccessReview Visualization of Urban Mobility Data from Intelligent Transportation Systems
Sensors 2019, 19(2), 332; https://doi.org/10.3390/s19020332
Received: 11 December 2018 / Revised: 2 January 2019 / Accepted: 10 January 2019 / Published: 15 January 2019
Viewed by 129 | PDF Full-text (38827 KB)
Abstract
Intelligent Transportation Systems are an important enabler for the smart cities paradigm. Currently, such systems generate massive amounts of granular data that can be analyzed to better understand people’s dynamics. To address the multivariate nature of spatiotemporal urban mobility data, researchers and practitioners
[...] Read more.
Intelligent Transportation Systems are an important enabler for the smart cities paradigm. Currently, such systems generate massive amounts of granular data that can be analyzed to better understand people’s dynamics. To address the multivariate nature of spatiotemporal urban mobility data, researchers and practitioners have developed an extensive body of research and interactive visualization tools. Data visualization provides multiple perspectives on data and supports the analytical tasks of domain experts. This article surveys related studies to analyze which topics of urban mobility were addressed and their related phenomena, and to identify the adopted visualization techniques and sensors data types. We highlight research opportunities based on our findings. Full article
(This article belongs to the Special Issue Smart Cities)
Open AccessArticle Corrosion Measurement of the Atmospheric Environment Using Galvanic Cell Sensors
Sensors 2019, 19(2), 331; https://doi.org/10.3390/s19020331
Received: 16 December 2018 / Revised: 5 January 2019 / Accepted: 11 January 2019 / Published: 15 January 2019
Viewed by 104 | PDF Full-text (1007 KB)
Abstract
An atmospheric corrosion monitor (ACM) is an instrument used to track the corrosion status of materials. In this paper, a galvanic cell sensor with a simple structure, flexible parameters, and low cost was proposed for constructing a novel ACM, which consisted of three
[...] Read more.
An atmospheric corrosion monitor (ACM) is an instrument used to track the corrosion status of materials. In this paper, a galvanic cell sensor with a simple structure, flexible parameters, and low cost was proposed for constructing a novel ACM, which consisted of three layers: the upper layer was gold, used as the cathode; the lower layer was corroded metal, used as the anode; and the middle layer was epoxy resin, used to separate the cathode and anode. Typically, the anode and epoxy resin were hollowed out, and the hollow parts were filled with electrolyte when it was wet to form a corrosive galvanic cell. Specifically, the corrosion rate was obtained by measuring the short circuit current of the cell. The sensor was made of a printed circuit board (PCB) or flexible printed circuit (FPC) and a metal coupon, which allowed for early control of the electrical parameters (including sensitivity and capacity) and could be combined with various metals. Additionally, the sensor feasibility was studied in water droplet experiments, during which the corrosive current changed with the electrolyte evaporation. The sensor practicability was also verified in a salt spray test, and the electric charge was compared using the thickness loss of bare coupons. A contrast test was also conducted for the corrosivity of different sensors made of aluminum, iron and copper. Full article
(This article belongs to the Special Issue Sensors for Emerging Environmental Markers and Contaminants)
Open AccessArticle Attitude Estimation of Underwater Vehicles Using Field Measurements and Bias Compensation
Sensors 2019, 19(2), 330; https://doi.org/10.3390/s19020330
Received: 1 December 2018 / Revised: 11 January 2019 / Accepted: 11 January 2019 / Published: 15 January 2019
Viewed by 127 | PDF Full-text (6214 KB)
Abstract
This paper proposes a method of estimating the attitude of an underwater vehicle. The proposed method uses two field measurements, namely, a gravitational field and a magnetic field represented in terms of vectors in three-dimensional space. In many existing methods that convert the
[...] Read more.
This paper proposes a method of estimating the attitude of an underwater vehicle. The proposed method uses two field measurements, namely, a gravitational field and a magnetic field represented in terms of vectors in three-dimensional space. In many existing methods that convert the measured field vectors into Euler angles, the yaw accuracy is affected by the uncertainty of the gravitational measurement and by the uncertainty of the magnetic field measurement. Additionally, previous methods have used the magnetic field measurement under the assumption that the magnetic field has only a horizontal component. The proposed method utilizes all field measurement components as they are, without converting them into Euler angles. The bias in the measured magnetic field vector is estimated and compensated to take full advantage of all measured field vector components. Because the proposed method deals with the measured field independently, uncertainties in the measured vectors affect the attitude estimation separately without adding up. The proposed method was tested by conducting navigation experiments with an unmanned underwater vehicle inside test tanks. The results were compared with those obtained by other methods, wherein the Euler angles converted from the measured field vectors were used as measurements. Full article
(This article belongs to the Section Physical Sensors)
Open AccessArticle Analysis and Design of SCMA-Based Hybrid Unicast-Multicast Relay-Assisted Networks
Sensors 2019, 19(2), 329; https://doi.org/10.3390/s19020329
Received: 3 December 2018 / Revised: 7 January 2019 / Accepted: 11 January 2019 / Published: 15 January 2019
Viewed by 98 | PDF Full-text (472 KB) | HTML Full-text | XML Full-text
Abstract
This paper studies a multi-user network model based on sparse code multiple access (SCMA), where both unicast and multicast services are considered. In the direct transmission scheme, the communication between the base station (BS) and the users is completed with one stage, in
[...] Read more.
This paper studies a multi-user network model based on sparse code multiple access (SCMA), where both unicast and multicast services are considered. In the direct transmission scheme, the communication between the base station (BS) and the users is completed with one stage, in which the relay is inexistent. In the two-stage cooperative transmission scheme, any number of relays are placed to improve the reliability of wireless communication system. The BS broadcasts the requested message to users and relays in the first stage, and the successful relays forward the message to unsuccessful users in the second stage. To characterize the performance of these two schemes, we derive the exact and approximate expressions of average outage probability. Furthermore, to take full advantage of the cooperative diversity, an optimal power allocation and relay location strategy in the high signal-to-noise ratio (SNR) regime is studied. The outage probability reaches the minimum value when the first stage occupies half of the total energy consumed. Simulation and analysis results are presented to demonstrate the performance of these two schemes. The results show that the two-stage cooperative scheme effectively reduce the average outage probability in SCMA network, especially in the high SNR region. Full article
(This article belongs to the Special Issue Green Wireless Networks in 5G-inspired Applications)
Figures

Figure 1

Open AccessArticle A Combined Quantitative Evaluation Model for the Capability of Hyperspectral Imagery for Mineral Mapping
Sensors 2019, 19(2), 328; https://doi.org/10.3390/s19020328
Received: 5 December 2018 / Revised: 11 January 2019 / Accepted: 11 January 2019 / Published: 15 January 2019
Viewed by 98 | PDF Full-text (747 KB)
Abstract
To analyze the influence factors of hyperspectral remote sensing data processing, and quantitatively evaluate the application capability of hyperspectral data, a combined evaluation model based on the physical process of imaging and statistical analysis was proposed. The normalized average distance between different classes
[...] Read more.
To analyze the influence factors of hyperspectral remote sensing data processing, and quantitatively evaluate the application capability of hyperspectral data, a combined evaluation model based on the physical process of imaging and statistical analysis was proposed. The normalized average distance between different classes of ground cover is selected as the evaluation index. The proposed model considers the influence factors of the full radiation transmission process and processing algorithms. First- and second-order statistical characteristics (mean and covariance) were applied to calculate the changes for the imaging process based on the radiation energy transfer. The statistical analysis was combined with the remote sensing process and the application performance, which consists of the imaging system parameters and imaging conditions, by building the imaging system and processing models. The season (solar zenith angle), sensor parameters (ground sampling distance, modulation transfer function, spectral resolution, spectral response function, and signal to noise ratio), and number of features were considered in order to analyze the influence factors of the application capability level. Simulated and real data collected by Hymap in the Dongtianshan area (Xinjiang Province, China), were used to estimate the proposed model’s performance in the application of mineral mapping. The predicted application capability of the proposed model is consistent with the theoretical analysis. Full article
(This article belongs to the Section Remote Sensors)
Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top