Ultra-wideband Sensor Research Articles

Non-Wearable UWB Sensor for Human Identification in Smart Home

Human identification is one of the main challenges for health monitoring systems in smart home. The majority of existing systems employ either wearable tags or video cameras to identify multiple residents in home environment. However, due to the inflexibility and inconvenience of wearable devices, and potential intrusiveness of video cameras, the adoption rate of these approaches remains low. In this paper, we propose a novel non-wearable identification system to recognize multiple residents in a home environment, through ambient non-intrusive ultra-wide band (UWB) sensors. For each room, over the entrance, we propose to install a UWB sensor to monitor and identify individuals who enter or exit the room. As each individual has different body figure and walking gait, they are “seen” differently by UWB sensor. Through the proposed Region of Interest (ROI) extraction approach, our system generates a unique UWB signature for each individual which will be used for their identification. We evaluated our system in a controlled laboratory environment with eight individuals including six males and two females. Our UWB-based approach achieved 88% accuracy in identifying individuals among eight subjects, while a similar ultrasound-based technique [1] achieved only a 54% accuracy rate.

GEOREFERENCING IN GNSS-CHALLENGED ENVIRONMENT: INTEGRATING UWB AND IMU TECHNOLOGIES

Abstract. Acquiring geospatial data in GNSS compromised environments remains a problem in mapping and positioning in general. Urban canyons, heavily vegetated areas, indoor environments represent different levels of GNSS signal availability from weak to no signal reception. Even outdoors, with multiple GNSS systems, with an ever-increasing number of satellites, there are many situations with limited or no access to GNSS signals. Independent navigation sensors, such as IMU can provide high-data rate information but their initial accuracy degrades quickly, as the measurement data drift over time unless positioning fixes are provided from another source. At The Ohio State University’s Satellite Positioning and Inertial Navigation (SPIN) Laboratory, as one feasible solution, Ultra- Wideband (UWB) radio units are used to aid positioning and navigating in GNSS compromised environments, including indoor and outdoor scenarios. Here we report about experiences obtained with georeferencing a pushcart based sensor system under canopied areas. The positioning system is based on UWB and IMU sensor integration, and provides sensor platform orientation for an electromagnetic inference (EMI) sensor. Performance evaluation results are provided for various test scenarios, confirming acceptable results for applications where high accuracy is not required.

Multiple moving person tracking by UWB sensors: the effect of mutual shielding persons and methods reducing its impacts

Ultra-wideband (UWB) radars are sensors allowing to track people in critical environments and situations. The results reached by single UWB sensors for such applications have shown that they are able to detect and track a person very well in a single person scenario. However, in multiple moving person scenarios, the ability of a single UWB sensor to detect several persons is usually significantly reduced. This is caused by a mutual shielding among people. In this paper, we will deal with the mutual shielding effect and its impacts, as well as with the methods of improving multiple moving person tracking by UWB radars. Firstly, we will provide a comprehensive description of the mutual shielding effect. Then, based on its analyses, we will state three complementary approaches created by the authors of this paper to reduce its impacts. They include an enhancement of the low-level echo of the targets, radar antenna array positioning at a convenient height, UWB sensor network application and, finally, their mutual combinations. The properties of those approaches will be demonstrated by two experimental measurements aimed at through wall tracking of two and three people, respectively. The results obtained in the experiments will illustrate the mutual shielding effect and the potential of the methods we have proposed to reduce its impacts.

Real-Time and Noncontact Impulse Radio Radar System for $\mu \text{m}$ Movement Accuracy and Vital-Sign Monitoring Applications

In this paper, a real-time, contactless pulse-based ultra-wideband (UWB) radar sensor was used to precisely detect the movement of the robotic arm, heartbeats, and respiration activities. To increase the object tracking resolution, an algorithm using adaptive and digitalized post-calibration techniques were proposed and tested. Both the radiated and reflected analog pulses were converted to digital signals by a low-noise comparator and its buffer for the time interval and distance detection. Moreover, the dynamic and calibrated tracking mechanism was incorporated into the algorithm for improving tracking accuracy and to continuously localize an object’s vibration. The measured performance revealed that the proposed method successfully achieved $\mu \text{m}$ movement precision, thus providing its excellent tracking ability. We performed three different experimental tests to demonstrate the UWB radar’s viability. First, the radar was employed to detect the undesired structural vibration of a delta robotic arm, which was subjected to high acceleration and structural flexibility. The measured results indicated that the accuracy of $100~\mu \text{m}$ can be achieved at a 10 Hz vibration frequency. Next, the apnea alarm was tested, which included an embedded sensitive sensor in the smart mattress in order to execute long-term physiological monitoring. The apnea was mitigated by auto-adjusting the patient’s sleeping posture on the mattress when the UWB sensor detected the apnea condition. The final experiment using the radar sensor was to monitor human vital signs, such as heart and breathing rates, simultaneously. In comparison with a commercial electrocardiography instrument, this radar sensor measured 73.2 bpm with only 1.2% deviation. Our results shown that the contactless UWB sensor performs superbly and is well-suited for monitoring physiological parameters.

Towards robust and efficient device-free localization using UWB sensor network

Device-free localization (DFL) is the method of using distributed wireless sensors to localize the target without carrying any devices. Existing DFL methods leverage the variation of narrowband received signal strength (NRSS) which is vulnerable to multipath fading, and thus results in considerable performance degradation in indoor environments. Moreover, the inefficient sensor deployment of traditional DFL involves huge human efforts, which is not suitable for emergency scenarios. In this paper, we utilize sensors transmitting ultra-wideband (UWB) signals to solve both problems. We proposed two RSS variation estimation methods based on the channel impulse response (CIR) measurements provided by UWB sensors, which turn out to be more robust to multipath than NRSS due to the fine multipath resolution of UWB signals. We also employ a higher operating frequency to enhance the shadowing loss for mitigating the multipath effect. Additionally, satisfactory sensor self-localization is achieved under the cooperative localization framework owing to the accurate ranging capability of UWB sensors. We conducted experiments in three different environments to explore the feasibility of our method. The results show that the proposed method gains much better localization performance and requires less human efforts than narrowband DFL.

Classification Algorithms for Human and Dog Movement Based on Micro-Doppler Signals

We propose classification algorithms for human and dog movement. The proposed algorithms use micro-Doppler signals obtained from humans and dogs moving in four different directions. A two-stage classifier based on a support vector machine (SVM) is proposed, which uses a radial-based function (RBF) kernel and 16SUPth/SUP-order linear predictive code (LPC) coefficients as feature vectors. With the proposed algorithms, we obtain the best classification results when a first-level SVM classifies the type of movement, and then, a second-level SVM classifies the moving object. We obtain the correct classification probability 95.54% of the time, on average. Next, to deal with the difficult classification problem of human and dog running, we propose a twolayer convolutional neural network (CNN). The proposed CNN is composed of six (6x6) convolution filters at the first and second layers, with (5x5) max pooling for the first layer and (2x2) max pooling for the second layer. The proposed CNN-based classifier adopts an auto regressive spectrogram as the feature image obtained from the 16SUPth/SUP-order LPC vectors for a specific time duration. The proposed CNN exhibits 100% classification accuracy and outperforms the SVM-based classifier. These results show that the proposed classifiers can be used for human and dog classification systems and also for classification problems using data obtained from an ultrawideband (UWB) sensor.

Statistical Modeling of Indirect Paths for UWB Sensors in an Indoor Environment.

In this paper, we present a statistical model of an indirect path generated in an ultra-wideband (UWB) human tracking scenario. When performing moving target detection, an indirect path signal can generate ghost targets that may cause a false alarm. For this purpose, we performed radar measurements in an indoor environment and established a statistical model of an indirect path based on the measurement data. The proposed model takes the form of a modified Saleh–Valenzuela model, which is used in a UWB channel model. An application example of the proposed model for mitigating false alarms is also presented.

System for Bulk Dielectric Permittivity Estimation of Breast Tissues at Microwave Frequencies

This paper presents an apparatus capable of measuring the average dielectric properties of the human breast. It is composed of two arrays between which the breast is placed. Each array is fitted with five ultra-wideband (UWB) sensors operating from 1.5 to 10 GHz. Direct contact is made between the breast skin and the sensor arrays, avoiding any matching liquid. The transmission coefficients for all possible sensor pairs in the two arrays are measured in 15 s. The data are then transformed to the time domain, and a time delay spectroscopy technique is used to estimate permittivity. The system was tested using phantoms with known properties and showed accurate estimations. Tests on human subjects resulted in dielectric property estimates in line with published data, while variation between scans of the same volunteer is as small as 2%.

Vivaldi Antenna for UWB Sensor Networks

In this paper, the Vivaldi antenna designed for ultra-wideband (UWB) sensor networks by exponential curves is presented. Manufactured antennas are used for through-wall measurements. The article describes the design and optimization of the antenna, antenna measurements using the network vector analyser and pulse radar. Measured results are compared with simulated results. The antenna is also compared with commercially manufactured antennas used in the above mentioned applications. The designed Vivaldi antenna is printed on ARLON 600 substrate and operates in the frequency band from 0.810 GHz up to more than 12 GHz. Experimental results show good agreement with the simulated performance.DOI: http://dx.doi.org/10.5755/j01.eie.22.4.15915

A new approach to construction of extended kit for M-Sequence UWB sensor system based on LTCC

Purpose The purpose of this paper is to introduce modified in–phase and quadrature components (I–Q) demodulator based on low temperature co-fired ceramics (LTCC) dielectric substrate GreenTape 951PX for M-Sequence ultra-wide band (UWB) sensor system. Design/methodology/approach Microstrip low pass (LP) and band pass (BP) filters for UWB sensor systems with required properties (for both filters, minimum attenuation is −40dB in stopband, bandwidth of pass band is 6 to 8.5 GHz for BP filter and cutoff frequency is 2.5 GHz for LP filter) were designed, simulated, fabricated and measured using dielectric substrates Du Pont GreenTape 951 PX. The developed microstrip filters were integrated with all parts of I–Q demodulator on one multilayer structure based on LTCC substrate Du Pont GreenTape 951 PX. Findings Both type of microstrip filters integrated in the I– Q demodulator achieved better transmission characteristics in comparison with commercial available filters. It was shown that LTCC technology based on GreenTape 951PX proves good stability in gigahertz frequency and suitability for fabrication of I–Q demodulator with a multilayer approach. Originality/value The novelty of this work lies in substituting commercially available LP and BP filters used in I– Q demodulator by microstrip LP and BP filters with better performance and furthermore the I– Q demodulator is fabricated based on LTCC instead of previously used PCB.

A Bernoulli Filter for Extended Target Tracking Using Random Matrices in a UWB Sensor Network

In this paper, we propose a new tractable Bernoulli filter based on the random matrix framework to track an extended target in an ultra-wideband (UWB) sensor network. The resulting filter jointly tracks the kinematic and shape parameters of the target and is called the extended target Gaussian inverse Wishart Bernoulli (ET-GIW-Ber) filter. Closed form expressions for the ET-GIW-Ber filter recursions are presented. A clustering step is inserted into the measurement update stage in order to have a computationally tractable filter. In addition, a new method that is consistent with the applied clustering method is embedded into the filter recursions in order to adaptively estimate the time-varying number of measurements of the extended target. The simulation results demonstrate the robust and effective performance of the proposed filter. Furthermore, real data collected from a UWB sensor network are used to assess the performance of the proposed filter. It is shown that the proposed filter yields a very promising performance in estimation of the kinematic and shape parameters of the target.

A low-cost UWB sensor node powered by a piezoelectric harvester or solar cells

We propose an autonomous battery-less wireless sensor node that combines on a single printed circuit board an ultra-wideband (UWB) transmitter and its printed antenna, together with a piezoelectric cantilever and a solar cell array to harvest vibrations and light energy, respectively. The co-design of the solar cell array with the printed UWB antenna allows a prototype size of only 85×35mm2, i.e., less than 65% of a credit card size. Low-cost is achieved by using inexpensive FR4 dual-layer substrate, standard-ceramic capacitors, and low-cost harvesters. The vibrational energy scavenger is fabricated at the wafer scale based on commercially available bulk polycrystalline Lead Zirconate Titanate (PZT), and the solar cells are fabricated by depositing amorphous-Si on 0.5mm thick glass substrate. The cold-startup time of the demonstrator is about 42min under indoor-ambient light conditions, and about 34min under 700mg vibrations at a frequency of 100Hz. Once started, the sensor requires only 12.6μW to allow a transmission rate of one temperature sensor readout every 34s, thanks to the UWB transmitter that consumes only 206 pJ per pulse and a custom protocol with a reduced overhead.

A novel automated phasor measurement system for validated and traceable EMC/EMI near-field analysis

Traceable high precision EMC/EMI measurements will simplify product specifications and reduce the liability of OEMs. A novel automated near-field testbed for system- to chip-level EMC/ EMI in the RF domain based on photonic phasor probes is presented. The scanning system combines a large scanning volume with micrometer resolution. An optical surface reconstruction system allows the surface structure of the device under test (DUT) to be measured with better than 20 μm uncertainty, allowing scans at a precisely known distance above arbitrary electronic components. Miniaturized active electro-optical time-domain ultra-wideband Eand H-field sensors for the frequency range from 0.01 to 6 GHz combined with a high speed vector signal analyzer are applied to measure the EM phasor field distribution with a dynamic range of >120 dB. The fully isolated probes eliminate perturbations of the EM fields generated by the DUT compared to electrically connected probes and offer up to 60 dB better sensitivity than passive 42 2016 IEEE Electromagnetic Compatibility Magazine - Volume 5 - Quarter 2 electro-optical probes. The testbed enables high precision broadband near-field 3D scans for EMC/EMI analysis to be performed and excellent inter-laboratory repeatability to be achieved. In the near future, it will be possible to reconstruct emission data from the near field to the far field.

Looking behind a corner using multipath-exploiting UWB radar

Localization of persons that are hidden behind a corner is important in various security situations when the first responders should not be exposed to any threat. This article demonstrates the feasibility of an ultrawideband multipath-exploitation radar for localization in such scenarios. The approach utilizes multibounce echoes of electromagnetic waves that are scattered by the closest person situated behind a corner. We assume that the person does not carry any tag and does not cooperate with the localization system. The multibounce echoes are reflected and diffracted by the surroundings and make the hidden person visible to an operator that is behind the corner. The location estimation relies only on single-channel time-of-arrival data. Measured data are first processed by a background subtraction algorithm, which reveals the multipath evoked by the person. The multipath echoes are detected by a parallel threshold-based detector. A simple global nearest-neighbor algorithm is used for tracking detected echoes and improving their range estimates. The obtained range estimates are assigned to different physical propagation paths of the electromagnetic waves. The location of the person is estimated by fusing the information of the antenna location with respect to its surroundings and the assigned range estimates. The proposed approach is experimentally verified in a scenario where data are measured in real time by an ultrawideband sensor. Experimental results demonstrate that, depending on the scenario geometry, a walking or calmly standing person can be localized up to several meters behind the corner.

Detection and Classification of Transformer Winding Mechanical Faults Using UWB Sensors and Bayesian Classifier

Abstract In this paper, the Bayesian classifier is used to detect and classify the radial deformation and axial displacement of transformer windings. The proposed method is tested on a model of transformer for different volumes of radial deformation and axial displacement. In this method, ultra-wideband (UWB) signal is sent to the simplified model of the transformer winding. The received signal from the winding model is recorded and used for training and testing of Bayesian classifier in different axial displacement and radial deformation states of the winding. It is shown that the proposed method has a good accuracy to detect and classify the axial displacement and radial deformation of the winding.

Blind Selection of Representative Observations for Sensor Radar Networks

Sensor radar networks enable important new applications based on accurate localization. They rely on the quality of range measurements, which serve as observations for inferring a target location. In harsh propagation environments (e.g., indoors), such observations can be nonrepresentative of the target due to noise, multipath, clutter, and non-line-of-sight conditions leading to target misdetection, false-alarm events, and inaccurate localization. These conditions can be mitigated by selecting and processing a subset of representative observations. We introduce blind techniques for the selection of representative observations gathered by sensor radars operating in harsh environments. A methodology for the design and analysis of sensor radar networks is developed, taking into account the aforementioned impairments and observation selection. Results are obtained for noncoherent ultra-wideband sensor radars in a typical indoor environment (with obstructions, multipath, and clutter) to enable a clear understanding of how observation selection improves the localization accuracy.

Stationary planar-surface target detection in an unknown indoor environment

It is difficult to detect a stationary object in practice, especially in an unknown indoor environment, because (a) there is no distinct speed difference between the targets and the background; (b) responses of the targets are contaminated by dense unknown clutter; (c) a priori knowledge of the background is not always available for some scenarios. In this paper, a set of ultra-wideband sensors are used to detect a stationary target with a planar diffuse surface. It is shown that, the relative spectrum-shifts of the data after data-projection operation, are closely connected to the illumination-angle differences. Based on this, a detector is designed, and the location and the orientation of the target are determined. In order to mitigate the influence of clutters, a “time-shift & accumulation” scheme is designed to enhance the signal. As a consequence, the signal-to-interference-and-noise ratio is increased. In addition, results from measurement in a realistic indoor environment are provided.

CORRELATION BETWEEN SIMULATIONS AND REAL MEASUREMENTS OF MICROSTRIP FILTERS BASED ON LTCC IN HIGH FREQUENCY AREA

The aim of this paper lies in comparison of two CAD (Computer aided Design) software (Ansoft Designer from Ansys and HyperLynx 3D EM Designer from Mentor Graphics) and real measurements of designed and fabricated filters. Both software tools belong to the group of the most used tools for design and simulation of different structures. These structures are made by transmission lines of a few kinds (microstrip, stripline, slotline, etc.) and they substitute common elements in HF (High Frequency) area. This paper presents 3 various microstrip filters based on LTCC (Low Temperature Co-fired Ceramic) dielectric material GreenTape 951. Low pass (LP), band pass (BP) and band stop (BS) filters for UWB (Ultra Wide-Band) sensor systems were designed, simulated, fabricated and measured. Measured results and simulations (S21 – forward transmission coefficient) are plotted in joint graphs where divergences are observed and depicted.

지뢰탐지 실험플랫폼의 진동 특성 해석

In this paper, analysis of the vibration characteristic for the mine detectable test platform is described. The test platform system is the multi-sensor mine detectable vehicle. This multi-sensor mine detectable unit is more efficient detection performance than other conventional methods. The test platform system has five subsystems, the UWB(ultra wide band) sensor scanner, the MD(metal detector) sensor scanner, the ND(neutron detector) sensor scanner, and the detectable vehicle. We perform the vibration tests for the test platform and analyze the vibration characteristic, such as the max displacement, the max deformation and the max Von-Misses stress.

The Interference Impact of UWB Sensor on Mobile Station of 3G Mobile System

This paper presents the interference impact of Ultra Wide-Band (UWB) sensor using frequency of 3.5 GHz on 3G mobile system in Korea. The Minimum Coupling Loss (MCL) method and Spectrum Engineering Advanced Monte Carlo Analysis Tool (SEAMCAT) were used to evaluate the interference impacts of UWB sensor on 3G mobile system. The minimum allowable distance between UWB interferer and the victim receiver is required 0.09 m in indoor environment; in the case of multiple UWB interferers in outdoor environment, the maximum allowable UWB transmitting Power Spectral Density (PSD) should be-93.1 dBm/MHz below to guarantee co-existence with 3G mobile system.