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A long-standing vision of indoor localization is to eliminate infrastructure and deployment costs. Recent innovations make it possible to enable device-to-device (D2D) localization while requiring multiple antennas for the systems. We ask the following question: can we localize the more generally-used single-antenna devices (e.g., IoT) using another single-antenna device (e.g., smartphone or smartwatch) in a smart environment where low-cost backscatter tags are widely deployed on walls or smart objects. In this paper, we present TagLoc, a light-weight system that enables device-to-device localization without relying on large antenna arrays. Our observation is that the reflected signals from the ambient smart environment can be exploited to eliminate the requirement of bulky antenna arrays that are unachievable for the simple-designed IoT devices. Specifically, TagLoc creates multiple direction signatures using backscatter arrays in smart environments. Then, the receiver can accurately estimate the direction signatures from the transmitter to the arrays and then localize the target by cooperating all tag arrays. We prototype TagLoc using two single-antenna Intel NUCs with off-the-shelf Intel 5300 WiFi cards and customized backscatter tags. The results show TagLoc can achieve robust performance in a real indoor environment with a median localization error of 0.82m.

This work investigated the transient characteristics of tissue attenuation coefficient before, during and after HIFU treatment at different total acoustic powers (TAP) in ex vivo porcine muscle tissues. Dynamic changes of attenuation coefficient parameters were correlated with conventional B-mode ultrasound images over the whole HIFU treatment process. Two-dimensional pulse-echo radiofrequency (RF) data were acquired to estimate the changes of least squares attenuation coefficient slope (Δβ) and attenuation coefficient intercept (Δα0) averaged in the region of interest, and to construct Δβ, Δα0, and B-mode images simultaneously. During HIFU treatment, bubble activities were visible as strong hyperechoic regions in the B-mode images, causing fluctuations in Δβ and Δα0 estimations during treatment. Δβ and Δα0 increased with the appearance of bubble clouds in the B-mode images to values in the range of 1.5-2.5 [dB/(MHz.cm)] and 4-5 [dB/cm], respectively. After the treatment, Δβ and Δα0 gradually decreased, accompanied by fadeout of hyperechoic spot in the B-mode images, until they were stable at ranges of 0.75-1 [dB/(MHz.cm)] and 1-1.5 [dB/cm], respectively. In conclusion, Δβ and Δα0 images outperformed B-mode images in detecting HIFU thermal lesions by having significantly higher contrast to speckle ratios at all investigated TAP values.

With phase-sensitive optical time-domain reflectometry (Φ-OTDR), an optic fiber can be used as a distributed vibration sensor to perceive the external disturbance along the fiber through the phase variation of the Rayleigh backscatter light. However, due to the inevitable interference fading phenomenon, the signal-to-noise ratio (SNR) of Rayleigh backscatter light at certain points is insufficient, thus affecting the fidelity of vibration sensing. In this paper, we propose the spectrum extraction and the rotated-vector-sum (SERVS) method to suppress the interference fading in the pulse-intensity-coding Φ-OTDR, which applies Golay complementary sequence through acousto-optic modulator (AOM). Benefited from the easier implementation, the experimental results demonstrate that the percentage of fading points can be reduced from 2.98% to 0.33% significantly and the standard deviation of differential phase is also decreased from 0.6556 rad to 0.2901 rad. Also the minimum level of averaged power spectral density (PSD) of the differential phase at whole locations along the fiber is reduced about 6 dB/Hz effectively. For the demodulated disturbance signal, no influence on the SNR is observed thus it maintains a SNR improvement of 8.6 dB compared to the traditional single pulse Φ-OTDR system, achieving a noise floor of 2.38 pϵ/√Hz.

Summarization: This work offers a novel, backscatter radio-based, blind beamforming technique that assists the reception of signals in multipath conditions. The technique is based on simple, assistive backscattering tags, implemented without any means of signal amplification. These tags can blindly (i.e., without feedback) modify the phase of the associated wireless channels, leading to constructive addition of the multipath components (i.e., alignment). Such alignment events offer distributed beamforming gain. Analysis is performed and an expression for the probability of alignment is offered, along with an expression for the achievable gain, corroborated by simulations and experimental results. It is shown that increased number of assistive tags offers higher beamforming gain, at the expense of increased delay. The effectiveness of the proposed beamforming technique is highlighted with experiments and measurements on the radio frequency identification (RFID) Gen2 standard. Commercial RFIDs that initially could not be interrogated due to insufficient impinged power, were successfully interrogated hundreds of times/minute with the assistance of the beamforming tags. It was experimentally shown that the proposed beamforming tags can offer power gains in the range of 0.4 – 3.7 dB. While the technique was tested on commercial RFIDs, it is not limited to a specific communication standard. Presented on: IEEE Journal of Radio Frequency Identification

This letter considers a Radio Frequency (RF) powered Internet of Things (IoT) network that exploits ambient backscatter communications to maximize the minimum number of samples of targets. We propose a Maximum Backscatter Opportunity Search (MBOS) heuristic algorithm to construct set covers to ensure complete targets coverage. Our results demonstrate that the performance of MBOS is within 91% of the optimal number of samples and it is 25% higher as compared to not using backscattering.

For studying the flow of glaciers and their response to climate change it is important to detect glacier surges. Here, we compute within Google Earth Engine the normalized differences between winter maxima of Sentinel-1 C-band radar backscatter image stacks over subsequent years. We arrive at a global map of annual backscatter changes, which are for glaciers in most cases related to changed crevassing associated with surge-type activity. For our demonstration period 2018–2019 we detected 69 surging glaciers, with many of them not classified so far as surge type. Comparison with glacier surface velocities shows that we reliably find known surge activities. Our method can support operational monitoring of glacier surges, and some other special events such as large rock and snow avalanches.

Ambient backscatter communication (AmBC) leverages the existing ambient radio frequency (RF) environment to implement communication with battery-free devices. The key challenge in the development of AmBC is the very weak RF signals backscattered by the AmBC Tag. To overcome this challenge, we propose the use of orthogonal space-time block codes (OSTBC) by incorporating multiple antennas at the Tag as well as at the Reader. Our approach considers both coherent and non-coherent OSTBC so that systems with and without channel state information can be considered. To allow the application of OSTBC, we develop an approximate linearized and normalized multiple-input multiple-output (MIMO) channel model for the AmBC system. This MIMO channel model is shown to be accurate for a wide range of useful operating conditions. Two coherent detectors and a non-coherent detector are also provided based on the proposed AmBC channel model. Simulation results show that enhanced bit error rate performance can be achieved, demonstrating the benefit of using multiple antennas at the Tag as well as the Reader., 13 pages, 10 figures

Background To assess alterations in backscatter from the corneal epithelium, anterior stroma and lens surface in eyes with subclinical, mild and moderate keratoconus (KC). Methods In this single-centre, cross-sectional study involving 24 eyes with subclinical KC, 107 eyes with manifest KC (mild = 40 and moderate = 67 eyes) and 90 controls, line densitometry was performed with Pentacam (Oculus Optikgerate GmbH, Wetzlar, Germany) to obtain simultaneous backscatter values for the corneal epithelium, anterior stroma and anterior lens surface. Backscatter values and Pentacam parameters were used in subsequent statistical analyses. Results Eyes with subclinical, mild and moderate KC had similar epithelial and stromal backscatter (P > 0.05) that was significantly increased compared with the controls (P < 0.05). Although anterior lens surface backscatter did not differ between the control and KC groups (P > 0.05), it was significantly higher in the mild and moderate KC groups than in the subclinical KC group (P < 0.05). In the KC group (n = 131) epithelial backscatter was strongly correlated with stromal backscatter (r = 0.911, P < 0.0001). Conclusions Increased epithelial backscatter and a strong correlation with anterior stromal backscatter in the KC groups were consistent with the epithelium-stroma interaction involved in KC pathogenesis. Single-point backscatter analysis can be used with point clouds to construct epithelial and stromal backscatter maps in Pentacam to aid the detection of KC as a novel feature.

Simple, low-power, reliable backscatter communication systems must overcome the severe, double-fading nature of the backscatter channel. In this article, we show experimentally that when a conventional transponder is replaced by a retrodirective transponder in backscatter systems, those deep fading nulls are reduced by as much as two orders-of-magnitude. We consider three multipath scenarios all of which show a pronounced link-reliability improvement with a retrodirective transponder compared to its standard non-retrodirective counterpart. The measurements also reveal that by comparing the best case scenario of the two transponder designs under 0.001 outage probability, the retrodirective transponder requires only a 13-dB fade margin while the conventional tag requires a 34-dB fade margin—a significant improvement that would be a key enabler for next-generation backscatter systems.

The resonant fiber optic gyro (RFOG) based on reciprocal modulation-demodulation technique is introduced and the influence of high modulation frequency on resonance and demodulation output is analyzed. The expression of backscattering output in resonant cavity is deduced and the experimental device is built to measure the backscattering coefficient. The demodulation model considering backscattering noise is established under reciprocal sinusoidal modulation, and the optimal modulation parameters are obtained by simulation. Finally, the RFOG system is set up. The results show that the detection sensitivity is improved by 19% with the optimal modulation parameters and the system bias stability improves from 0.067°/s to 0.023°/s.

INTRODUCTION: Quantitative ultrasound parameters based on form factor models were investigated as potential biomarkers of cell death in breast tumor (MDA-231) xenografts treated with chemotherapy. METHODS: Ultrasound backscatter radiofrequency data were acquired from MDA-231 breast cancer tumor–bearing mice (n = 20) before and after the administration of chemotherapy drugs at two ultrasound frequencies: 7 MHz and 20 MHz. Radiofrequency spectral analysis involved estimating the backscatter coefficient from regions of interest in the center of the tumor, to which form factor models were fitted, resulting in estimates of average scatterer diameter and average acoustic concentration (AAC). RESULTS: The ∆AAC parameter extracted from the spherical Gaussian model was found to be the most effective cell death biomarker (at the lower frequency range, r2 = 0.40). At both frequencies, AAC in the treated tumors increased significantly (P = .026 and .035 at low and high frequencies, respectively) 24 hours after treatment compared with control tumors. Furthermore, stepwise multiple linear regression analysis of the low-frequency data revealed that a multiparameter quantitative ultrasound model was strongly correlated to cell death determined histologically posttreatment (r2 = 0.74). CONCLUSION: The Gaussian form factor model–based scattering parameters can potentially be used to track the extent of cell death at clinically relevant frequencies (7 MHz). The 20-MHz results agreed with previous findings in which parameters related to the backscatter intensity (i.e., AAC) increased with cell death. The findings suggested that, in addition to the backscatter coefficient parameter ∆AAC, biological features including tumor heterogeneity and initial tumor volume were important factors in the prediction of cell death response.

This research explores the possibility of monitoring apoptosis and classifying clusters of apoptotic cells based on the changes in ultrasound backscatter signals from the tissues. The backscatter from normal and apoptotic cells, using a high frequency ultrasound instrument are modeled through an autoregressive (AR) modeling technique. The proper model order is calculated by tracking the error criteria in the reconstruction of the original signal. The AR model coefficients, which are assumed to contain the main statistical features of the signal, are passed as the input to linear and nonlinear machine classifiers (Fisher linear discriminant, conditional Gaussian classifier, Naive Bayes classifier and neural networks with nonlinear activation functions). In addition, an adaptive signal segmentation method (least squares lattice filter) is used to differentiate the data from layers of different cell types into stationary parts ready for modeling and classification.

Phase-sensitive optical time-domain reflectometry $\Phi $ -OTDR) is a powerful sensing device that enables fully distributed optical fiber vibration detection with fast response and high sensitivity. Based on the introduction of its principles, Rayleigh backscatter, sensing mechanism, the characteristics of the $\Phi $ -OTDR system are analyzed in detail. Some gaps in the $\Phi $ -OTDR technology are outlined, and its development trends are highlighted. The application of its current technology is illustrated in different fields such as the perimeter security monitoring system, submarine cable surveillance, and so on. In the experiments analysis, it was pointed out that the device is very sensitive, which is subject to a high rate of false alarms; it also has unresolved types of disturbances. For these purposes, this paper first summarizes the development status of the $\Phi $ -OTDR-based fully distributed optical fiber sensing device. Then, it analyzes and proposes the use of a Printed Circuit Board (PCB) winding flyback converter with shielding, to solve the problem of sensitivity. The shielding method has been proven to significantly reduce high frequency noise up to 30 MHz. This will enable relevant industries and future researchers to know the current state of the $\Phi $ -OTDR device.

This paper presents the results of theoretical and experimental studies of electromagnetic waves backscattering by partially non-reciprocal media. It is proposed to implement a controlled reflector...

This paper is a comprehensive experimental report on the neutron radiation effects of distributed optical fiber sensors with enhanced Rayleigh scattering profiles in an in-pile environment. Femtosecond laser direct writing was used to inscribe Type-II modifications in standard telecom fibers and radiation-hardened fibers with fluorine-doped cores. Rayleigh backscattering signals were enhanced for continuous 1.5 m. In-pile lead-out sensors tests were carried out at the MIT Research Reactor for two months, which was operated at a nominal power of 5.7 MW with fast neutron (>0.1 MeV) flux of 1.29 × 1014 n/cm2/s and an in-core temperature of up to 560 °C. Using the Optical Frequency Domain Reflectometry technique, the backscattering profiles of fiber sensors were interrogated with a 3-cm spatial resolution to monitor the temperature profile of the reactor. Results show that laser inscribed Type-II modifications in the form of nanogratings are highly stable against extreme temperature and ionizing radiation. Both standard telecom fibers and radiation-hardened fibers with laser-enhanced Rayleigh profiles can continuously perform distributed temperature measurements over the entire duration of the in-pile testing. Temperature coefficients of sensors and spectral shift quality were studied as functions of total radiation fluence. To the best of our knowledge, we present for the first time, the temperature profile of an operating nuclear reactor core with 3-cm spatial resolution, enabled by distributed fiber sensors with laser-enhanced Rayleigh scattering profiles. The high spatial resolution measurements can provide valuable data for the design and validation of digital twin and virtual reality of nuclear energy systems.

Integrating backscatter communication (BackCom) into wireless powered communication networks (WPCNs) makes it possible to transmit information and harvest energy simultaneously, which is regarded as a promising method to enhance the throughput. A very important issue is how to allocate the charging time and transmitting time to efficiently utilize the energy in hybrid access point (HAP) so as to improve the network performance. This paper adopts convex optimization to handle the time allocation for both WPCNs and BackCom users. A two‐stage efficient algorithm is proposed to solve the problem of sum‐throughput maximization (STM) subject to the basic throughput requirements of BackCom users, where the Lagrange duality method is applied at the first‐stage, while golden section and bisection method are jointly used at the second‐stage. In order to solve the throughput unfairness among nodes in the STM problem, the common‐throughput maximization (CTM; i.e. the worst node's throughput) problem is further considered. This problem is decomposed into a master problem and a sub‐problem, which are solved in a progressive manner. Simulation results show that the proposed methods obtain substantial improvement compared to the benchmark scheme.

Results of the numerical study of a possibility of compensating for aero-optical aberration distortions of the beam wavefront using the aperture sensing technique based on atmospheric backscatter signals are described. It is shown that the technique makes it possible to partially compensate for aero-optical aberrations. The cross section beam size becomes several times smaller than that of a beam without the wavefront adaptive control, and the intensity distribution becomes more symmetric about the optical axis.

The green communication and large-scale connection issues will be faced by the wireless communication networks with futuristic sixth generation (6G) technology. The radio-frequency (RF) and spectrum sources may be shared simultaneously to achieve optimal communication in these networks by means of backscatter devices (BD) that may function in constrained spectrums as well as the stringent energy scenarios of green Internet-of-things (IoT) by means of the proposed novel modified backscatter communication model (BCM). Unlicensed eavesdroppers may interfere with the BD due to its vulnerability caused by the wireless communication channels and their broadcasting nature. The intrusion of an unlicensed eavesdropper is detected in an efficient manner by means of the proposed BCM. The analytical derivations of intercept probability (IP) and outage probability (OP) are invoked to analyze the security and reliability of the proposed architecture. Under high main-to-eavesdropper ratio (MER) regime, the IP and under high signal-to-noise ratio (SNR) regime, the OP asymptotic behaviors are estimated additionally. Based on the results of performance evaluation, it is evident that there is a decrease in the security of BD with the increase in MER while there is a simultaneous increase in the legitimate user security. Various system parameters may be adjusted for optimizing the security and reliability performance trade-off. For diverse orders, the existence of error floors are indicated by the non-zero fixed constant of BD and the legitimate user’s OP when high SNR value is observed at the system.

Symbiotic radio (SR) backscatter is a possible low-power wireless communication technique for future Internet of Things devices. In this letter, a multiple-input-multiple-output (MIMO) SR backscatter system is proposed, where the secondary multi-antenna transmission from the backscatter device (BD) to the receiver is riding on the primary multi-antenna transmission from the transmitter to the receiver. We investigate the beamforming design optimization problem which maximizes the sum capacity of primary and secondary transmissions under the capacity constraint of secondary transmission. In the MIMO SR backscatter system, each antenna of the SR BD reflects its received ambient radio frequency signals from all the transmitting antennas of the transmitter, which causes that the globally optimal solution is difficult to obtain. Here, we derive an algorithm to obtain the capacity upper bound. Furthermore, considering both primary and secondary transmissions, we propose an exact penalty method based locally optimal solution. Simulation results display that the proposed exact penalty method based locally optimal solution achieves the sum capacity which is close to the upper bound.

The efficacy of the deployment of backscatter networks in sensor networks and the internet of things has been severely limited by the maximum read range of backscatter radio frequency identification (RFID) tags. The work presented here demonstrates a low-power two-way repeater architecture capable of increasing the read range and extending the coverage of tags to non-line-of-sight (NLOS) scenarios. This is achieved through the use of a two-way frequency divided tunnel diode-based reflection amplifier optimized for use in backscattering channels. The system reports a more than 2X increase in the read range of a semi-passive RFID tag at 17 dBm output power. The work presented here shows a system capable of giving a comparable performance with the state of the art while consuming up to 1000X less power in a simple single-component front end.

This work demonstrates the ability to extend the positioning range of low-powered RFID tags to distances usually not achievable with other wireless or conventional RFID technologies. The technique is performed through a Received Signal Phase (RSP)-based method on a 5.8 GHz backscatter tunneling tag, in multipath-rich indoor and outdoor environments, at distances up to 35 meters from the reader. Distance errors as low as 0.1% of the total reader-to-tag distance were observed with average errors of 0.8% and 0.6% for indoor and outdoor environments, respectively. Compared to Received Signal Strength (RSS)-based techniques, the average distance estimation accuracy is improved by a factor of 51 and 38 for indoor and outdoor environments, respectively. Moreover, an Effective Isotropic Radiated Power (EIRP) of only 10.5 dBm and a biasing power for the tunneling tag of only $21.3~\mu \text{W}$ at 80 mV promise a low-power, long-range sub-meter scale positioning technique with a projected maximum range over 1 km.

Accurate crop type mapping provides numerous benefits for a deeper understanding of food systems and yield prediction. Ever-increasing big data, easy access to high-resolution imagery, and cloud-based analytics platforms like Google Earth Engine have drastically improved the ability for scientists to advance data-driven agriculture with improved algorithms for crop type mapping using remote sensing, computer vision, and machine learning. Crop type mapping techniques mainly relied on standalone SAR and optical imagery, few studies investigated the potential of SAR-optical data fusion, coupled with virtual constellation, and 3-dimensional (3D) deep learning networks. To this extent, we use a deep learning approach that utilizes the denoised backscatter and texture information from multi-temporal Sentinel-1 SAR data and the spectral information from multi-temporal optical Sentinel-2 data for mapping ten different crop types, as well as water, soil and urban area. Multi-temporal Sentinel-1 data was fused with multi-temporal optical Sentinel-2 data in an effort to improve classification accuracies for crop types. We compared the results of the 3D U-Net to the state-of-the-art deep learning networks, including SegNet and 2D U-Net, as well as commonly used machine learning method such as Random Forest. The results showed (1) fusing multi-temporal SAR and optical data yields higher training overall accuracies (OA) (3D U-Net 0.992, 2D U-Net 0.943, SegNet 0.871) and testing OA (3D U-Net 0.941, 2D U-Net 0.847, SegNet 0.643) for crop type mapping compared to standalone multi-temporal SAR or optical data (2) optical data fused with denoised SAR data via a denoising convolution neural network (OA 0.912) performed better for crop type mapping compared to optical data fused with boxcar (OA 0.880), Lee (OA 0.881), and median (OA 0.887) filtered SAR data and (3) 3D convolutional neural networks perform better than 2D convolutional neural networks for crop type mapping (SAR OA 0.912, optical OA 0.937, fused OA 0.992).

A methodology for the assessment of cell concentration, in the range 5–100 cells/ $\mu \text{L}$ , suitable for in vivo analysis of serous body fluids is presented in this work. This methodology is based on the quantitative analysis of ultrasound images obtained from cell suspensions and considers applicability criteria, such as short analysis times, moderate frequency, and absolute concentration estimation, all necessary to deal with the variability of tissues among different patients. Numerical simulations provided the framework to analyze the impact of echo overlapping and the polydispersion of scatterer sizes on the cell concentration estimation. The cell concentration range that can be analyzed as a function of the transducer and emitted waveform used was also discussed. Experiments were conducted to evaluate the performance of the method using 7- $\mu \text{m}$ and 12- $\mu \text{m}$ polystyrene particles in water suspensions in the 5–100 particles/ $\mu \text{L}$ range. A single scanning focused transducer working at a central frequency of 20 MHz was used to obtain ultrasound images. The method proposed to estimate the concentration proved to be robust for different particle sizes and variations of gain acquisition settings. The effect of tissues placed in the ultrasound path between the probe and the sample was also investigated using 3-mm-thick tissue mimics. Under this situation, the algorithm was robust for the concentration analysis of 12 $\mu \text{m}$ particle suspensions, yet significant deviations were obtained for the smallest particles.

Osteoporosis is defined by a decrease in bone mass and a deterioration in bone microstructure. It is a major public health issue and a significant economic burden for both individuals and society. Thus, monitoring bone mass and structure is necessary to prevent bone fragility and osteoporosis. This study aimed to develop a prototype of quantitative ultrasound (QUS) and to evaluate the feasibility of backscatter mode for the bone assessment. Ultrasound (US) signals that propagate through the bone can be characterized by comparing the signal from both transmitter and receiver transducers. The US backscattered signal depends on the characteristic of both medium and transducer. In this study, we analyzed the attenuated signal based on the parameters: type of bone (compact and spongy), type of coupling medium (air, starch, and gel), the angle between transducers and bone (30o, 60o, and 90o), and transducer distance (0, 10, 5, 15, 20 and 25 cm). We use only 1 MHz transducer frequency. The prototype has been evaluated by Digital Oscilloscope and LabVIEW user interface to observe received signals. The results of this study showed that there was a difference in amplitude of the US signal from compact and spongy bones. The amplitude is directly proportional to acoustic impedance and inversely proportional to the distance between transducers. There is a negative correlation between bone microstructure to attenuation, and compact bones have a greater attenuation coefficient than spongy bones.

The coupling of Rayleigh backscatter induced phase noise in bi-directional, inline fiber interferometers compromises detection sensitivity for Fourier frequencies less than 1 Hz. Here we report experimental and theoretical work highlighting the coupling of backscatter phase noise, and its subsequent range-gating and suppression using digitally enhanced homodyne interferometry. Between two in-line fiber interferometers, each with a differential arm-length of 8 km, we demonstrate a relative stability of 10 Hz/ $\sqrt{\text{Hz}}$ at a Fourier frequency of 100 mHz.

We describe the observation of a previously unreported resonance phenomenon in UWB SAR imaging and its application in a novel scheme for the retrieval of thickness and dielectric properties of scene features. The resonance was observed in a 14–50 GHz laboratory study of very high resolution SAR imagery. It presented as a periodic fluctuation in the backscatter of a scene feature in response to changes in the radar measurement frequency. The complimentary static reflectivity measurements of a range of dielectric materials showed the phenomenon could be understood as a material behaving as a resonant microwave cavity. Modeling simulations were able to accurately reproduce the observed nulling characteristics for visually homogeneous materials (acrylic, MDF, and plasterboard) and which displayed a regular frequency spacing between nulls. Those with inhomogeneous structures (chipboard and plywood) showed much more irregular nulling patterns. The spacing of the backscatter nulls is set by the product of the permittivity and thickness of the material. By exploiting diversity in viewing geometry, the two terms can be separated and measured. The scheme offers a new opportunity in the SAR surveillance and monitoring of man-made structures.

Multichannel pulse-echo ultrasound using linear arrays and single-channel data acquisition systems opens new perspectives for the evaluation of cortical bone. In combination with spectral backscatter analysis, it can provide quantitative information about cortical microstructural properties. We present a numerical study, based on the finite-difference time-domain method, to estimate the backscatter cross section of randomly distributed circular pores in a bone matrix. A model that predicts the backscatter coefficient using arbitrary pore diameter distributions was derived. In an ex vivo study on 19 human tibia bones (six males, 13 females, 83.7 ± 8.4 years), multidirectional ultrasound backscatter measurements were performed using an ultrasound scanner equipped with a 6-MHz 128-element linear array with sweep motor control. A normalized depth-dependent spectral analysis was performed to derive backscatter and attenuation coefficients. Site-matched reference values of tissue acoustic impedance ${Z}$ , cortical thickness (Ct.Th), pore density (Ct.Po.Dn), porosity (Ct.Po), and characteristic parameters of the pore diameter (Ct.Po.Dm) distribution were obtained from 100-MHz scanning-acoustic microscopy images. Proximal femur areal bone mineral density (aBMD), stiffness ${S}$ , and ultimate force Fu from the same donors were available from a previous study. All pore structure and material properties could be predicted using linear combinations of backscatter parameters with a median to high accuracy (0.28 ≤ adjusted R2 ≤ 0.59). The combination of cortical thickness and backscatter parameter provided similar or better prediction accuracies than aBMD. For the first time, a method for the noninvasive assessment of the pore diameter distribution in cortical bone by ultrasound is proposed. The combined assessment of cortical thickness, sound velocity, and pore size distribution in a mobile, nonionizing measurement system could have a major impact on preventing osteoporotic fractures.

Understanding the physical properties and scattering mechanisms contributes to synthetic aperture radar (SAR) image interpretation. For single-polarized SAR data, however, it is difficult to extract the physical scattering mechanisms due to lack of polarimetric information. Time–frequency analysis (TFA) on complex-valued SAR image provides extra information in frequency perspective beyond the “image” domain. Based on TFA theory, we propose to generate the subband scattering pattern for every object in complex-valued SAR image as the physical property representation, which reveals backscattering variations along slant-range and azimuth directions. In order to discover the inherent patterns and generate a scattering classification map from single-polarized SAR image, an unsupervised hierarchical deep embedding clustering (HDEC) algorithm based on TFA (HDEC-TFA) is proposed to learn the embedded features and cluster centers simultaneously and hierarchically. The polarimetric analysis result for quad-pol SAR images is applied as reference data of physical scattering mechanisms. In order to compare the scattering classification map obtained from single-polarized SAR data with the physical scattering mechanism result from full-polarized SAR, and to explore the relationship and similarity between them in a quantitative way, an information theory based evaluation method is proposed. We take Gaofen-3 quad-polarized SAR data for experiments, and the results and discussions demonstrate that the proposed method is able to learn valuable scattering properties from single-polarization complex-valued SAR data, and to extract some specific targets as well as polarimetric analysis. At last, we give a promising prospect to future applications.

Transplantation of severely steatotic donor livers is associated with early allograft dysfunction and poorer graft survival. Histology remains the gold standard diagnostic of donor steatosis despite the lack of consensus definition and its subjective nature. In this prospective observational study of liver transplant patients, we demonstrate the feasibility of using a handheld optical backscatter probe to assess the degree of hepatic steatosis and correlate the backscatter readings with clinical outcomes. The probe is placed on the surface of the liver and emits red and near infrared light from the tip of the device and measures the amount of backscatter of light from liver tissue via two photodiodes. Measurement of optical backscatter (Mantel-Cox P < 0.0001) and histopathological scoring of macrovesicular steatosis (Mantel-Cox P = 0.046) were predictive of 5-year graft survival. Recipients with early allograft dysfunction defined according to both Olthoff (P = 0.0067) and MEAF score (P = 0.0097) had significantly higher backscatter levels from the donor organ. Backscatter was predictive of graft loss (AUC 0.75, P = 0.0045). This study demonstrates the feasibility of real-time measurement of optical backscatter in donor livers. Early results indicate readings correlate with steatosis and may give insight to graft outcomes such as early allograft dysfunction and graft loss.

The intensity distribution of scattered radiation over the transmitting–receiving aperture of a turbulent lidar is experimentally studied. Sounding was performed along a horizontal path under moderate turbulence with a narrow laser beam located in the center of the receiving aperture of variable size. The relative contribution to the echo signal due to turbulence decreased as the receiving aperture increased. The BSE effect was found to be localized at the center of the receiving aperture: the peak of scattered radiation is located at the axis of the sounding beam, and its size is approximately equal to the beam size; at the periphery, the average intensity of scattered radiation slowly decreased to background values as the distance from the beam axis increased. The result can be used in practice for optimal choice of transceiver parameters when designing a turbulent lidar.

Introduction. The multipath resistance of GNSS antennas is largely determined by the gain slope of the amplitude radiation pattern at sliding angles (angles close to the horizon). The gain slope of the antenna radiation pattern is determined by the size of its ground plane. This article investigates the dependence between the gain slope and ground plane radius R of a quadrupole antenna.Aim. To analyse the impact of the radius of conventional and high-impedance ground planes on the backscatter radiation pattern of a quadrupole antenna at sliding angles.Materials and methods. Computer simulations were carried out in CAD CST Studio Suite using the methods of finite element analysis (FEM), finite difference time domain (FDTD) and template based post-processing.Results. Quadrupole antennas with a capacitive high-impedance ground plane and a conventional flat ground plane were simulated. The dependence of the average gain slope at sliding angles on the radius of the ground plane was determined at low fн and upper fв GNSS frequencies. The analysis of the down/up ratio, the rolloff gain and the multipath ratio for R= 1…20 of the wavelength of capacitive high-impedance and ground planes conventional flat was performed. It was established that higher gain slopes can be obtained using different types of ground planes; however, lower backscatter radiation values are achievable only using high-impedance structures. It was observed that the same slope of the radiation pattern (about 1 dB/°) for GNSS lower frequencies can be obtained at different R=12λ0, and, presumably, at 20λ0.Conclusion. A high-impedance ground plane with a diameter of 2R=12λ0 is preferable for a quadrupole antenna at low GNSS frequencies. A further increase in the ground plane size will insignificantly improve its characteristics.

The vision of tracking small IoT devices runs into the reality of localization technologies---today it is difficult to continuously track objects through walls in homes and warehouses on a coin cell battery. Although Wi-Fi and ultra-wideband radios can provide tracking through walls, they do not last more than a month on small coin and button cell batteries because they consume tens of milliwatts of power. We present the first localization system that consumes microwatts of power at a mobile device and can be localized across multiple rooms in settings such as homes and hospitals. To this end, we introduce a multiband backscatter prototype that operates across 900 MHz, 2.4 GHz, and 5 GHz and can extract the backscatter phase information from signals that are below the noise floor. We build subcentimeter-sized prototypes that consume 93 μW and could last five to ten years on button cell batteries. We achieved ranges of up to 60 m away from the AP and accuracies of 2, 12, 50, and 145 cm at 1, 5, 30, and 60 m, respectively. To demonstrate the potential of our design, we deploy it in two real-world scenarios: five homes in a metropolitan area and the surgery wing of a hospital in patient pre-op and post-op rooms as well as storage facilities.

Backscatter communication which enables wireless-powered backscatter devices (BDs) to transmit information by reflecting incident signals, is an energy- and cost-efficient communication technology for Internet-of-Things. This paper considers an unmanned aerial vehicle (UAV)-assisted backscatter communication network (UBCN) consisting of multiple BDs and carrier emitters (CEs) on the ground as well as a UAV. A communicate-while-fly scheme is first designed, in which the BDs illuminated by their associated CEs transmit information to the flying UAV in a time-division-multiple-access manner. Considering the critical issue of the UAV's limited on-board energy and the CEs' transmission energy, we maximize the energy efficiency (EE) of the UBCN by jointly optimizing the UAV's trajectory, the BDs' scheduling, and the CEs' transmission power, subject to the BDs' throughput constraints and harvested energy constraints, as well as other practical constraints. Furthermore, we propose an iterative algorithm based on the block coordinated decent method to solve the formulated mixed-integer non-convex problem, in each iteration of which the variables are alternatively optimized by leveraging the cutting-plane technique, the Dinkelbach's method and the successive convex approximation technique. Also, the convergence and complexity of the proposed algorithm are analyzed. Finally, simulation results show that the proposed communicate-while-fly scheme achieves significant EE gains compared with the benchmark hover-and-fly scheme. Useful insights on the optimal trajectory design and resource allocation are also obtained., Comment: This paper has 31 pages and 10 figures. It is submitted for possible journal publications

With the commencement of the 5G of wireless networks, researchers around the globe have started paying their attention to the imminent challenges that may emerge in the beyond 5G (B5G) era. Various revolutionary technologies and innovative services are offered in 5G networks, which, along with many principal advantages, are anticipated to bring a boom in the number of connected wireless devices and the types of use-cases that may cause the scarcity of network resources. These challenges partly emerged with the advent of massive machine-type communications (mMTC) services, require extensive research innovations to sustain the evolution towards enhanced-mMTC (e-mMTC) with the scalable network cost in 6\textsuperscript{th} generation (6G) wireless networks. Towards delivering the anticipated massive connectivity requirements with optimal energy and spectral efficiency besides low hardware cost, this paper presents an enabling framework for 6G networks, which utilizes two emerging technologies, namely, non-coherent communications and backscatter communications (BsC). Recognizing the coherence between these technologies for their joint potential of delivering e-mMTC services in the B5G era, a comprehensive review of their state-of-the-art is conducted. The joint scope of non-coherent and BsC with other emerging 6G technologies is also identified, where the reviewed technologies include unmanned aerial vehicles (UAVs)-assisted communications, visible light communications (VLC), quantum-assisted communications, reconfigurable large intelligent surfaces (RLIS), non-orthogonal multiple access (NOMA), and machine learning-aided intelligent networks. Subsequently, the scope of these enabling technologies for different device types, service types, and optimization parameters is analyzed..., 6G Wireless Networks, Preprint, 34 pages, 11 Figures

In this paper, we introduce an ultra-high frequency radio frequency identification (UHF-RFID) mobile robot platform that is capable of performing fully autonomous inventory taking and stocktaking by providing three-dimensional (3D) product maps and thus making possible the concept of a smart warehouse. The proposed novel hardware architecture consists of an eight-channel UHF-RFID-listener for parallel signal phase recovery, including two different carrier leakage suppression circuits and a correlation decoder for each channel for the tag signal, which can handle a backscatter link frequency (BLF) deviation of up to ${\mathrm {22~\%}}$ to decode the tag data. The system also uses eight parallel channels for multiple-input multiple-output (MIMO) localization. For the system evaluation we labeled clothes stored in a warehouse with tags and generated their product map. The proposed localization algorithm is based on a synthetic aperture radar (SAR) MIMO approach that needs exact knowledge of the antenna positions and, therefore, of the driven trajectory. This position is provided by the robot, which takes advantage of a simultaneous localization and mapping (SLAM) algorithm, determining the position with ${\mathrm {1~cm}}$ accuracy while generating two-dimensional (2D) maps of the surroundings. We placed ten tags at known positions to assess the system’s performance and were able to locate these tags within a root mean square error (RMSE) of ${\mathrm {1.45~cm}}$ in 3D.

In this paper, we use the ultrasonic backscatter technique for measurement of the thickness of the hardened layer (case depth) on inductions-hardened VCN 100 steel plates. The experiment includes an immersion ultrasonic test where both the sample and the ultrasonic probe are immersed in a water tank. The measurement technique is based on the backscattering of ultrasonic waves from the transition zone which lies between the hardened layer and the soft inner core. The backscattered ultrasonic signals are measured and processed by a number of signal processing schemes to extract the thickness of the hardened layer. A scanning system measures the case depth on the surface of the plate samples and produces C-scan images showing the profile of the hardened layer. This technique could be used for nondestructive testing and quality control of hardened specimens.

This paper addresses backscatter communications as a new paradigm for Internet of Things (IoT) sensor wireless solutions. The paper clearly presents the history background of the technology and then makes a summary of the more recent developments form several groups around the world, with emphasis in US and Europe groups. The analysis done in this paper will address circuit and physical layer approaches for such a solution and its real implementations, having in mind IoT sensors for long range high speed communications.

Optical frequency domain reflectometry (OFDR) measurements are performed by recording the interference pattern of light backscattered by density fluctuations or Bragg gratings along the length of an optical fiber. Changes in local temperature or strain in the fiber cause shifts in the backscattered light spectrum, which can be calibrated to the applied temperature or strain. Comparing the backscattered optical spectra from each reflection site with a reference (unstrained) spectrum allows for quantification of local spectral shifts. While mature OFDR-based technologies can provide high-precision spatially distributed measurements over kilometer lengths, the post-processing approaches used to recover spectral shifts from raw optical intensity data can limit the use of OFDR in harsh environments. This paper presents a novel approach to post-processing OFDR data which extends the usability of optical fibers exposed to harsh environments. This approach is the first to use the spectral shift quality, calculated for two OFDR measurements, to identify an appropriate reference scan from which the spectral shift can be determined. Three experimental data sets are used to test the algorithm: (1) an optical fiber heated to >950°C, (2) an aluminum-embedded optical fiber under strain from differential thermal expansion, and (3) an optical fiber exposed to a total neutron flux of $2\times 10^{13}$ n/cm2/s over 40 hours in a nuclear test reactor. Results show that using a metric of quality to select an appropriate reference measurement extends the functional range of OFDR strain and temperature sensors. Furthermore, this algorithm can be applied to existing OFDR data.

In this interdisciplinary work, a low-power varactor-tunable frequency selective surface is presented for use with a multiplexed remote sensor system. Combined with a low power sensor and control system, voltage biasing of the proposed frequency selective surface panel can be used to modulate the center frequency of a reflection peak, which in turn may be detected by remote interrogation through a radar system. The control board and frequency selective surface were found to draw only $200~\mu \text{A}$ of current during typical operation from two 3V CR2032 button batteries, enabling continuous operation for weeks at a time (even longer if operated in wake-up mode) when used in conjunction with a suitably low power sensor. Centered at 3 GHz, the backscatter peak can be modulated across a range of 200 MHz, and the combined system was shown to successfully differentiate between various concentrations of ammonia under test conditions.

In this paper, we analyze a backscatter network that implements simultaneous wireless information and power transfer. The backscatter devices (BDs) in the network work as relays that receive RF signals from the source, harvest the energy and use it to reflect the signal to the receiver. We assume a non-linear energy harvesting (EH) circuit that takes into account the sensitivity and non-linearity of the electronic components. We formulate an optimization problem to maximize the achievable rate at the receiver of this network. By considering both amplify-and-forward and decode-and-forward modes, we propose algorithms to jointly optimize the power-splitting ratio and the reflection coefficient of the BDs. Simulation results demonstrate the effectiveness of the proposed algorithms with respect to baseline relay networks. In particular, the impact of the number of BDs, source transmit power, and distance of the BDs from the source and destination on the average rate and energy efficiency of the network are illustrated.

Accurate tag quantity estimation is a prerequisite to maximize the throughput of radio frequency identification (RFID) systems. Previous estimators, mainly designed for single-antenna RFID systems, often suffer from performance degradation in low signal-to-noise-ratio (SNR) regimes, making them inappropriate for multi-antenna RFID systems where received tag signals are likely to overlap. In this regard, a high-dimensional tag quantity estimator is proposed in the multi-antenna context by exploiting the spatial diversity at receive antennas. We first show that the collided tag signals can be rearranged as high-dimensional vectors, whereby the tag quantity estimation problem can be modeled as a high-dimensional data clustering one. We next prove that when the SNR on each backscattering subchannel is greater than 3 dB, the distance incrementation between clusters offered by the modeling advantage benefits their separation. This finding encourages us to integrate the density-based spatial clustering of applications with noise (DBSCAN) algorithm with this high-dimensional space for tag quantity estimation, and its superiority over several existing approaches are supported by both synthetic and real-world case studies.

Indoor device-free object detection has many applications, such as assisted living, home security, and occupant-centered building utility control. To accommodate 3-D room layout variations and improve accuracy, multiple observation units with spatial diversity are often required, which will unavoidably cause a significant increase in the component and deployment cost if each unit needs wired power or battery. In this article, we present an indoor device-free object detection system implemented by a commercial radio frequency identification reader and many passive tags around the room. The passive tag as a dispersed observation point offers a cost-effective solution for the necessary spatial diversity. The tag backscattering phase is assembled to generate the reflectivity image inside the capture volume using Fourier-based reconstruction. A new calibration technique is proposed to compensate for multiplicative path losses and subtract the effect of background clutters, such as furniture. Noisy channels and channels with their line-of-sight blocked by the target are also filtered out during postprocessing to improve locating accuracy and mitigate ambiguity. A 1:6 room model was first used to study the effects of the indoor materials and room layout, where occupant recognition and centimeter-level locating were successfully demonstrated. Real-scale rooms were then tested, where decimeter-level 3-D location error was achieved for a single occupant, and useful information for occupant posture can also be evaluated.