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Sensors, Volume 16, Issue 7 (July 2016)

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Open AccessArticle Reduced Graphene Oxide/Au Nanocomposite for NO2 Sensing at Low Operating Temperature
Sensors 2016, 16(7), 1152; https://doi.org/10.3390/s16071152
Received: 30 June 2016 / Revised: 20 July 2016 / Accepted: 21 July 2016 / Published: 22 July 2016
Cited by 7 | PDF Full-text (5084 KB) | HTML Full-text | XML Full-text
Abstract
A reduced grapheme oxide (rGO)/Au hybrid nanocomposite has been synthesized by hydrothermal treatment using graphite and HAuCl4 as the precursors. Characterization, including X-ray diffraction (XRD), Raman spectra, X-ray photoelecton spectroscopy (XPS) and transmission electron microscopy (TEM), indicates the formation of rGO/Au. A
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A reduced grapheme oxide (rGO)/Au hybrid nanocomposite has been synthesized by hydrothermal treatment using graphite and HAuCl4 as the precursors. Characterization, including X-ray diffraction (XRD), Raman spectra, X-ray photoelecton spectroscopy (XPS) and transmission electron microscopy (TEM), indicates the formation of rGO/Au. A gas sensor fabricated with rGO/Au nanocomposite was applied for NO2 detection at 50 °C. Compared with pure rGO, rGO/Au nanocomposite exhibits higher sensitivity, a more rapid response–recovery process and excellent reproducibility. Full article
(This article belongs to the Special Issue Gas Nanosensors)
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Open AccessArticle Modeling and Assessment of GPS/BDS Combined Precise Point Positioning
Sensors 2016, 16(7), 1151; https://doi.org/10.3390/s16071151
Received: 31 May 2016 / Revised: 12 July 2016 / Accepted: 15 July 2016 / Published: 22 July 2016
Cited by 4 | PDF Full-text (3341 KB) | HTML Full-text | XML Full-text
Abstract
Precise Point Positioning (PPP) technique enables stand-alone receivers to obtain cm-level positioning accuracy. Observations from multi-GNSS systems can augment users with improved positioning accuracy, reliability and availability. In this paper, we present and evaluate the GPS/BDS combined PPP models, including the traditional model
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Precise Point Positioning (PPP) technique enables stand-alone receivers to obtain cm-level positioning accuracy. Observations from multi-GNSS systems can augment users with improved positioning accuracy, reliability and availability. In this paper, we present and evaluate the GPS/BDS combined PPP models, including the traditional model and a simplified model, where the inter-system bias (ISB) is treated in different way. To evaluate the performance of combined GPS/BDS PPP, kinematic and static PPP positions are compared to the IGS daily estimates, where 1 month GPS/BDS data of 11 IGS Multi-GNSS Experiment (MGEX) stations are used. The results indicate apparent improvement of GPS/BDS combined PPP solutions in both static and kinematic cases, where much smaller standard deviations are presented in the magnitude distribution of coordinates RMS statistics. Comparisons between the traditional and simplified combined PPP models show no difference in coordinate estimations, and the inter system biases between the GPS/BDS system are assimilated into receiver clock, ambiguities and pseudo-range residuals accordingly. Full article
(This article belongs to the Section Remote Sensors)
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Open AccessArticle A High-Gain Passive UHF-RFID Tag with Increased Read Range
Sensors 2016, 16(7), 1150; https://doi.org/10.3390/s16071150
Received: 14 June 2016 / Revised: 19 July 2016 / Accepted: 19 July 2016 / Published: 22 July 2016
Cited by 1 | PDF Full-text (1632 KB) | HTML Full-text | XML Full-text
Abstract
In this work, a passive ultra-high frequency radio-frequency identification UHF-RFID tag based on a 1.25 wavelengths thin dipole antenna is presented for the first time. The length of the antenna is properly chosen in order to maximize the tag read range, while maintaining
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In this work, a passive ultra-high frequency radio-frequency identification UHF-RFID tag based on a 1.25 wavelengths thin dipole antenna is presented for the first time. The length of the antenna is properly chosen in order to maximize the tag read range, while maintaining a reasonable tag size and radiation pattern. The antenna is matched to the RFID chip by means of a very simple matching network based on a shunt inductance. A tag prototype, based on the Alien Higgs-3 chip, is designed and fabricated. The overall dimensions are 400 mm × 14.6 mm, but the tag width for most of its length is delimited by the wire diameter (0.8 mm). The measured read range exhibits a maximum value of 17.5 m at the 902–928 MHz frequency band. This represents an important improvement over state-of-the-art passive UHF-RFID tags. Full article
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Open AccessArticle Piezoresistive Membrane Surface Stress Sensors for Characterization of Breath Samples of Head and Neck Cancer Patients
Sensors 2016, 16(7), 1149; https://doi.org/10.3390/s16071149
Received: 29 February 2016 / Revised: 9 July 2016 / Accepted: 14 July 2016 / Published: 22 July 2016
Cited by 4 | PDF Full-text (7734 KB) | HTML Full-text | XML Full-text
Abstract
For many diseases, where a particular organ is affected, chemical by-products can be found in the patient’s exhaled breath. Breath analysis is often done using gas chromatography and mass spectrometry, but interpretation of results is difficult and time-consuming. We performed characterization of patients’
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For many diseases, where a particular organ is affected, chemical by-products can be found in the patient’s exhaled breath. Breath analysis is often done using gas chromatography and mass spectrometry, but interpretation of results is difficult and time-consuming. We performed characterization of patients’ exhaled breath samples by an electronic nose technique based on an array of nanomechanical membrane sensors. Each membrane is coated with a different thin polymer layer. By pumping the exhaled breath into a measurement chamber, volatile organic compounds present in patients’ breath diffuse into the polymer layers and deform the membranes by changes in surface stress. The bending of the membranes is measured piezoresistively and the signals are converted into voltages. The sensor deflection pattern allows one to characterize the condition of the patient. In a clinical pilot study, we investigated breath samples from head and neck cancer patients and healthy control persons. Evaluation using principal component analysis (PCA) allowed a clear distinction between the two groups. As head and neck cancer can be completely removed by surgery, the breath of cured patients was investigated after surgery again and the results were similar to those of the healthy control group, indicating that surgery was successful. Full article
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Open AccessArticle An Improved Otsu Threshold Segmentation Method for Underwater Simultaneous Localization and Mapping-Based Navigation
Sensors 2016, 16(7), 1148; https://doi.org/10.3390/s16071148
Received: 25 April 2016 / Revised: 7 July 2016 / Accepted: 19 July 2016 / Published: 22 July 2016
Cited by 7 | PDF Full-text (4456 KB) | HTML Full-text | XML Full-text
Abstract
The main focus of this paper is on extracting features with SOund Navigation And Ranging (SONAR) sensing for further underwater landmark-based Simultaneous Localization and Mapping (SLAM). According to the characteristics of sonar images, in this paper, an improved Otsu threshold segmentation method (TSM)
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The main focus of this paper is on extracting features with SOund Navigation And Ranging (SONAR) sensing for further underwater landmark-based Simultaneous Localization and Mapping (SLAM). According to the characteristics of sonar images, in this paper, an improved Otsu threshold segmentation method (TSM) has been developed for feature detection. In combination with a contour detection algorithm, the foreground objects, although presenting different feature shapes, are separated much faster and more precisely than by other segmentation methods. Tests have been made with side-scan sonar (SSS) and forward-looking sonar (FLS) images in comparison with other four TSMs, namely the traditional Otsu method, the local TSM, the iterative TSM and the maximum entropy TSM. For all the sonar images presented in this work, the computational time of the improved Otsu TSM is much lower than that of the maximum entropy TSM, which achieves the highest segmentation precision among the four above mentioned TSMs. As a result of the segmentations, the centroids of the main extracted regions have been computed to represent point landmarks which can be used for navigation, e.g., with the help of an Augmented Extended Kalman Filter (AEKF)-based SLAM algorithm. The AEKF-SLAM approach is a recursive and iterative estimation-update process, which besides a prediction and an update stage (as in classical Extended Kalman Filter (EKF)), includes an augmentation stage. During navigation, the robot localizes the centroids of different segments of features in sonar images, which are detected by our improved Otsu TSM, as point landmarks. Using them with the AEKF achieves more accurate and robust estimations of the robot pose and the landmark positions, than with those detected by the maximum entropy TSM. Together with the landmarks identified by the proposed segmentation algorithm, the AEKF-SLAM has achieved reliable detection of cycles in the map and consistent map update on loop closure, which is shown in simulated experiments. Full article
(This article belongs to the Special Issue Vision-Based Sensors in Field Robotics)
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Open AccessArticle Design and Field Experimentation of a Cooperative ITS Architecture Based on Distributed RSUs
Sensors 2016, 16(7), 1147; https://doi.org/10.3390/s16071147
Received: 29 April 2016 / Revised: 18 July 2016 / Accepted: 19 July 2016 / Published: 22 July 2016
Cited by 1 | PDF Full-text (2278 KB) | HTML Full-text | XML Full-text | Correction
Abstract
This paper describes a new cooperative Intelligent Transportation System architecture that aims to enable collaborative sensing services. The main goal of this architecture is to improve transportation efficiency and performance. The system, which has been proven within the participation in the ICSI (Intelligent
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This paper describes a new cooperative Intelligent Transportation System architecture that aims to enable collaborative sensing services. The main goal of this architecture is to improve transportation efficiency and performance. The system, which has been proven within the participation in the ICSI (Intelligent Cooperative Sensing for Improved traffic efficiency) European project, encompasses the entire process of capture and management of available road data. For this purpose, it applies a combination of cooperative services and methods for data sensing, acquisition, processing and communication amongst road users, vehicles, infrastructures and related stakeholders. Additionally, the advantages of using the proposed system are exposed. The most important of these advantages is the use of a distributed architecture, moving the system intelligence from the control centre to the peripheral devices. The global architecture of the system is presented, as well as the software design and the interaction between its main components. Finally, functional and operational results observed through the experimentation are described. This experimentation has been carried out in two real scenarios, in Lisbon (Portugal) and Pisa (Italy). Full article
(This article belongs to the Special Issue Selected Papers from UCAmI, IWAAL and AmIHEALTH 2015)
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Open AccessArticle Vibration Sensitivity Reduction of Micromachined Tuning Fork Gyroscopes through Stiffness Match Method with Negative Electrostatic Spring Effect
Sensors 2016, 16(7), 1146; https://doi.org/10.3390/s16071146
Received: 15 June 2016 / Revised: 19 July 2016 / Accepted: 19 July 2016 / Published: 22 July 2016
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Abstract
In this paper, a stiffness match method is proposed to reduce the vibration sensitivity of micromachined tuning fork gyroscopes. Taking advantage of the coordinate transformation method, a theoretical model is established to analyze the anti-phase vibration output caused by the stiffness mismatch due
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In this paper, a stiffness match method is proposed to reduce the vibration sensitivity of micromachined tuning fork gyroscopes. Taking advantage of the coordinate transformation method, a theoretical model is established to analyze the anti-phase vibration output caused by the stiffness mismatch due to the fabrication imperfections. The analytical solutions demonstrate that the stiffness mismatch is proportional to the output induced by the external linear vibration from the sense direction in the anti-phase mode frequency. In order to verify the proposed stiffness match method, a tuning fork gyroscope (TFG) with the stiffness match electrodes is designed and implemented using the micromachining technology and the experimental study is carried out. The experimental tests illustrate that the vibration output can be reduced by 73.8% through the stiffness match method than the structure without the stiffness match. Therefore, the proposed stiffness match method is experimentally validated to be applicable to vibration sensitivity reduction in the Micro-Electro-Mechanical-Systems (MEMS) tuning fork gyroscopes without sacrificing the scale factor. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle Design of a Direction-of-Arrival Estimation Method Used for an Automatic Bearing Tracking System
Sensors 2016, 16(7), 1145; https://doi.org/10.3390/s16071145
Received: 1 June 2016 / Revised: 17 July 2016 / Accepted: 19 July 2016 / Published: 22 July 2016
Cited by 5 | PDF Full-text (13354 KB) | HTML Full-text | XML Full-text
Abstract
In this paper, we introduce a sub-band direction-of-arrival (DOA) estimation method suitable for employment within an automatic bearing tracking system. Inspired by the magnitude-squared coherence (MSC), we extend the MSC to the sub-band and propose the sub-band magnitude-squared coherence (SMSC) to measure the
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In this paper, we introduce a sub-band direction-of-arrival (DOA) estimation method suitable for employment within an automatic bearing tracking system. Inspired by the magnitude-squared coherence (MSC), we extend the MSC to the sub-band and propose the sub-band magnitude-squared coherence (SMSC) to measure the coherence between the frequency sub-bands of wideband signals. Then, we design a sub-band DOA estimation method which chooses a sub-band from the wideband signals by SMSC for the bearing tracking system. The simulations demonstrate that the sub-band method has a good tradeoff between the wideband methods and narrowband methods in terms of the estimation accuracy, spatial resolution, and computational cost. The proposed method was also tested in the field environment with the bearing tracking system, which also showed a good performance. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessReview Fiber Optic Sensors for Temperature Monitoring during Thermal Treatments: An Overview
Sensors 2016, 16(7), 1144; https://doi.org/10.3390/s16071144
Received: 8 June 2016 / Revised: 15 July 2016 / Accepted: 18 July 2016 / Published: 22 July 2016
Cited by 26 | PDF Full-text (1763 KB) | HTML Full-text | XML Full-text | Correction
Abstract
During recent decades, minimally invasive thermal treatments (i.e., Radiofrequency ablation, Laser ablation, Microwave ablation, High Intensity Focused Ultrasound ablation, and Cryo-ablation) have gained widespread recognition in the field of tumor removal. These techniques induce a localized temperature increase or decrease to remove the
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During recent decades, minimally invasive thermal treatments (i.e., Radiofrequency ablation, Laser ablation, Microwave ablation, High Intensity Focused Ultrasound ablation, and Cryo-ablation) have gained widespread recognition in the field of tumor removal. These techniques induce a localized temperature increase or decrease to remove the tumor while the surrounding healthy tissue remains intact. An accurate measurement of tissue temperature may be particularly beneficial to improve treatment outcomes, because it can be used as a clear end-point to achieve complete tumor ablation and minimize recurrence. Among the several thermometric techniques used in this field, fiber optic sensors (FOSs) have several attractive features: high flexibility and small size of both sensor and cabling, allowing insertion of FOSs within deep-seated tissue; metrological characteristics, such as accuracy (better than 1 °C), sensitivity (e.g., 10 pm·°C−1 for Fiber Bragg Gratings), and frequency response (hundreds of kHz), are adequate for this application; immunity to electromagnetic interference allows the use of FOSs during Magnetic Resonance- or Computed Tomography-guided thermal procedures. In this review the current status of the most used FOSs for temperature monitoring during thermal procedure (e.g., fiber Bragg Grating sensors; fluoroptic sensors) is presented, with emphasis placed on their working principles and metrological characteristics. The essential physics of the common ablation techniques are included to explain the advantages of using FOSs during these procedures. Full article
(This article belongs to the Special Issue Optical Fiber Sensors 2016)
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Open AccessLetter Localisation of Sensor Nodes with Hybrid Measurements in Wireless Sensor Networks
Sensors 2016, 16(7), 1143; https://doi.org/10.3390/s16071143
Received: 25 April 2016 / Revised: 29 June 2016 / Accepted: 13 July 2016 / Published: 22 July 2016
Cited by 7 | PDF Full-text (1679 KB) | HTML Full-text | XML Full-text
Abstract
Localisation in wireless networks faces challenges such as high levels of signal attenuation and unknown path-loss exponents, especially in urban environments. In response to these challenges, this paper proposes solutions to localisation problems in noisy environments. A new observation model for localisation of
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Localisation in wireless networks faces challenges such as high levels of signal attenuation and unknown path-loss exponents, especially in urban environments. In response to these challenges, this paper proposes solutions to localisation problems in noisy environments. A new observation model for localisation of static nodes is developed based on hybrid measurements, namely angle of arrival and received signal strength data. An approach for localisation of sensor nodes is proposed as a weighted linear least squares algorithm. The unknown path-loss exponent associated with the received signal strength is estimated jointly with the coordinates of the sensor nodes via the generalised pattern search method. The algorithm’s performance validation is conducted both theoretically and by simulation. A theoretical mean square error expression is derived, followed by the derivation of the linear Cramer-Rao bound which serves as a benchmark for the proposed location estimators. Accurate results are demonstrated with 25%–30% improvement in estimation accuracy with a weighted linear least squares algorithm as compared to linear least squares solution. Full article
(This article belongs to the Special Issue Scalable Localization in Wireless Sensor Networks)
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Open AccessArticle Passive Resistor Temperature Compensation for a High-Temperature Piezoresistive Pressure Sensor
Sensors 2016, 16(7), 1142; https://doi.org/10.3390/s16071142
Received: 17 June 2016 / Revised: 10 July 2016 / Accepted: 19 July 2016 / Published: 22 July 2016
Cited by 2 | PDF Full-text (3922 KB) | HTML Full-text | XML Full-text
Abstract
The main limitation of high-temperature piezoresistive pressure sensors is the variation of output voltage with operating temperature, which seriously reduces their measurement accuracy. This paper presents a passive resistor temperature compensation technique whose parameters are calculated using differential equations. Unlike traditional experiential arithmetic,
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The main limitation of high-temperature piezoresistive pressure sensors is the variation of output voltage with operating temperature, which seriously reduces their measurement accuracy. This paper presents a passive resistor temperature compensation technique whose parameters are calculated using differential equations. Unlike traditional experiential arithmetic, the differential equations are independent of the parameter deviation among the piezoresistors of the microelectromechanical pressure sensor and the residual stress caused by the fabrication process or a mismatch in the thermal expansion coefficients. The differential equations are solved using calibration data from uncompensated high-temperature piezoresistive pressure sensors. Tests conducted on the calibrated equipment at various temperatures and pressures show that the passive resistor temperature compensation produces a remarkable effect. Additionally, a high-temperature signal-conditioning circuit is used to improve the output sensitivity of the sensor, which can be reduced by the temperature compensation. Compared to traditional experiential arithmetic, the proposed passive resistor temperature compensation technique exhibits less temperature drift and is expected to be highly applicable for pressure measurements in harsh environments with large temperature variations. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle Developing Ubiquitous Sensor Network Platform Using Internet of Things: Application in Precision Agriculture
Sensors 2016, 16(7), 1141; https://doi.org/10.3390/s16071141
Received: 29 April 2016 / Revised: 17 July 2016 / Accepted: 18 July 2016 / Published: 22 July 2016
Cited by 7 | PDF Full-text (8791 KB) | HTML Full-text | XML Full-text
Abstract
The application of Information Technologies into Precision Agriculture methods has clear benefits. Precision Agriculture optimises production efficiency, increases quality, minimises environmental impact and reduces the use of resources (energy, water); however, there are different barriers that have delayed its wide development. Some of
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The application of Information Technologies into Precision Agriculture methods has clear benefits. Precision Agriculture optimises production efficiency, increases quality, minimises environmental impact and reduces the use of resources (energy, water); however, there are different barriers that have delayed its wide development. Some of these main barriers are expensive equipment, the difficulty to operate and maintain and the standard for sensor networks are still under development. Nowadays, new technological development in embedded devices (hardware and communication protocols), the evolution of Internet technologies (Internet of Things) and ubiquitous computing (Ubiquitous Sensor Networks) allow developing less expensive systems, easier to control, install and maintain, using standard protocols with low-power consumption. This work develops and test a low-cost sensor/actuator network platform, based in Internet of Things, integrating machine-to-machine and human-machine-interface protocols. Edge computing uses this multi-protocol approach to develop control processes on Precision Agriculture scenarios. A greenhouse with hydroponic crop production was developed and tested using Ubiquitous Sensor Network monitoring and edge control on Internet of Things paradigm. The experimental results showed that the Internet technologies and Smart Object Communication Patterns can be combined to encourage development of Precision Agriculture. They demonstrated added benefits (cost, energy, smart developing, acceptance by agricultural specialists) when a project is launched. Full article
(This article belongs to the Special Issue Selected Papers from UCAmI, IWAAL and AmIHEALTH 2015)
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Open AccessArticle Evaluation of Deployment Challenges of Wireless Sensor Networks at Signalized Intersections
Sensors 2016, 16(7), 1140; https://doi.org/10.3390/s16071140
Received: 31 March 2016 / Revised: 4 July 2016 / Accepted: 11 July 2016 / Published: 22 July 2016
Cited by 6 | PDF Full-text (29101 KB) | HTML Full-text | XML Full-text
Abstract
With the growing demand of Intelligent Transportation Systems (ITS) for safer and more efficient transportation, research on and development of such vehicular communication systems have increased considerably in the last years. The use of wireless networks in vehicular environments has grown exponentially. However,
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With the growing demand of Intelligent Transportation Systems (ITS) for safer and more efficient transportation, research on and development of such vehicular communication systems have increased considerably in the last years. The use of wireless networks in vehicular environments has grown exponentially. However, it is highly important to analyze radio propagation prior to the deployment of a wireless sensor network in such complex scenarios. In this work, the radio wave characterization for ISM 2.4 GHz and 5 GHz Wireless Sensor Networks (WSNs) deployed taking advantage of the existence of traffic light infrastructure has been assessed. By means of an in-house developed 3D ray launching algorithm, the impact of topology as well as urban morphology of the environment has been analyzed, emulating the realistic operation in the framework of the scenario. The complexity of the scenario, which is an intersection city area with traffic lights, vehicles, people, buildings, vegetation and urban environment, makes necessary the channel characterization with accurate models before the deployment of wireless networks. A measurement campaign has been conducted emulating the interaction of the system, in the vicinity of pedestrians as well as nearby vehicles. A real time interactive application has been developed and tested in order to visualize and monitor traffic as well as pedestrian user location and behavior. Results show that the use of deterministic tools in WSN deployment can aid in providing optimal layouts in terms of coverage, capacity and energy efficiency of the network. Full article
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Open AccessArticle A High Precision Terahertz Wave Image Reconstruction Algorithm
Sensors 2016, 16(7), 1139; https://doi.org/10.3390/s16071139
Received: 9 May 2016 / Revised: 20 June 2016 / Accepted: 29 June 2016 / Published: 22 July 2016
Cited by 1 | PDF Full-text (6516 KB) | HTML Full-text | XML Full-text
Abstract
With the development of terahertz (THz) technology, the applications of this spectrum have become increasingly wide-ranging, in areas such as non-destructive testing, security applications and medical scanning, in which one of the most important methods is imaging. Unlike remote sensing applications, THz imaging
[...] Read more.
With the development of terahertz (THz) technology, the applications of this spectrum have become increasingly wide-ranging, in areas such as non-destructive testing, security applications and medical scanning, in which one of the most important methods is imaging. Unlike remote sensing applications, THz imaging features sources of array elements that are almost always supposed to be spherical wave radiators, including single antennae. As such, well-developed methodologies such as Range-Doppler Algorithm (RDA) are not directly applicable in such near-range situations. The Back Projection Algorithm (BPA) can provide products of high precision at the the cost of a high computational burden, while the Range Migration Algorithm (RMA) sacrifices the quality of images for efficiency. The Phase-shift Migration Algorithm (PMA) is a good alternative, the features of which combine both of the classical algorithms mentioned above. In this research, it is used for mechanical scanning, and is extended to array imaging for the first time. In addition, the performances of PMA are studied in detail in contrast to BPA and RMA. It is demonstrated in our simulations and experiments described herein that the algorithm can reconstruct images with high precision. Full article
(This article belongs to the Special Issue Infrared and THz Sensing and Imaging)
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Open AccessArticle On Inertial Body Tracking in the Presence of Model Calibration Errors
Sensors 2016, 16(7), 1132; https://doi.org/10.3390/s16071132
Received: 29 April 2016 / Revised: 6 July 2016 / Accepted: 11 July 2016 / Published: 22 July 2016
Cited by 12 | PDF Full-text (3353 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
In inertial body tracking, the human body is commonly represented as a biomechanical model consisting of rigid segments with known lengths and connecting joints. The model state is then estimated via sensor fusion methods based on data from attached inertial measurement units (IMUs).
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In inertial body tracking, the human body is commonly represented as a biomechanical model consisting of rigid segments with known lengths and connecting joints. The model state is then estimated via sensor fusion methods based on data from attached inertial measurement units (IMUs). This requires the relative poses of the IMUs w.r.t. the segments—the IMU-to-segment calibrations, subsequently called I2S calibrations—to be known. Since calibration methods based on static poses, movements and manual measurements are still the most widely used, potentially large human-induced calibration errors have to be expected. This work compares three newly developed/adapted extended Kalman filter (EKF) and optimization-based sensor fusion methods with an existing EKF-based method w.r.t. their segment orientation estimation accuracy in the presence of model calibration errors with and without using magnetometer information. While the existing EKF-based method uses a segment-centered kinematic chain biomechanical model and a constant angular acceleration motion model, the newly developed/adapted methods are all based on a free segments model, where each segment is represented with six degrees of freedom in the global frame. Moreover, these methods differ in the assumed motion model (constant angular acceleration, constant angular velocity, inertial data as control input), the state representation (segment-centered, IMU-centered) and the estimation method (EKF, sliding window optimization). In addition to the free segments representation, the optimization-based method also represents each IMU with six degrees of freedom in the global frame. In the evaluation on simulated and real data from a three segment model (an arm), the optimization-based method showed the smallest mean errors, standard deviations and maximum errors throughout all tests. It also showed the lowest dependency on magnetometer information and motion agility. Moreover, it was insensitive w.r.t. I2S position and segment length errors in the tested ranges. Errors in the I2S orientations were, however, linearly propagated into the estimated segment orientations. In the absence of magnetic disturbances, severe model calibration errors and fast motion changes, the newly developed IMU centered EKF-based method yielded comparable results with lower computational complexity. Full article
(This article belongs to the Special Issue Inertial Sensors and Systems 2016)
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