Underwater four-quadrant dual-beam circumferential scanning laser fuze using nonlinear adaptive backscatter filter based on pauseable SAF-LMS algorithm

The phenomenon of a target echo peak overlapping with the backscattered echo peak significantly undermines the detection range and precision of underwater laser fuzes.To overcome this issue,we propose a four-quadrant dual-beam circumferential scanning laser fuze to distinguish various interference signals and provide more real-time data for the backscatter filtering algorithm.This enhances the algorithm loading capability of the fuze.In order to address the problem of insufficient filtering capacity in existing linear backscatter filtering algorithms,we develop a nonlinear backscattering adaptive filter based on the spline adaptive filter least mean square(SAF-LMS)algorithm.We also designed an algorithm pause module to retain the original trend of the target echo peak,improving the time discrimination accuracy and anti-interference capability of the fuze.Finally,experiments are conducted with varying signal-to-noise ratios of the original underwater target echo signals.The experimental results show that the average signal-to-noise ratio before and after filtering can be improved by more than31 d B,with an increase of up to 76%in extreme detection distance.

Stackelberg Game for Wireless Powered and Backscattering Enabled Sensor Networks

This paper investigates a wireless powered and backscattering enabled sensor network based on the non-linear energy harvesting model, where the power beacon(PB) delivers energy signals to wireless sensors to enable their passive backscattering and active transmission to the access point(AP). We propose an efficient time scheduling scheme for network performance enhancement, based on which each sensor can always harvest energy from the PB over the entire block except its time slots allocated for passive and active information delivery. Considering the PB and wireless sensors are from two selfish service providers, we use the Stackelberg game to model the energy interaction among them. To address the non-convexity of the leader-level problem, we propose to decompose the original problem into two subproblems and solve them iteratively in an alternating manner. Specifically, the successive convex approximation, semi-definite relaxation(SDR) and variable substitution techniques are applied to find a nearoptimal solution. To evaluate the performance loss caused by the interaction between two providers, we further investigate the social welfare maximization problem. Numerical results demonstrate that compared to the benchmark schemes, the proposed scheme can achieve up to 35.4% and 38.7% utility gain for the leader and the follower, respectively.

Joint Optimization of Resource Allocation and Trajectory Based on User Trajectory for UAV-Assisted Backscatter Communication System

The Backscatter communication has gained widespread attention from academia and industry in recent years. In this paper, A method of resource allocation and trajectory optimization is proposed for UAV-assisted backscatter communication based on user trajectory. This paper will establish an optimization problem of jointly optimizing the UAV trajectories, UAV transmission power and BD scheduling based on the large-scale channel state signals estimated in advance of the known user trajectories, taking into account the constraints of BD data and working energy consumption, to maximize the energy efficiency of the system. The problem is a non-convex optimization problem in fractional form, and there is nonlinear coupling between optimization variables.An iterative algorithm is proposed based on Dinkelbach algorithm, block coordinate descent method and continuous convex optimization technology. First, the objective function is converted into a non-fractional programming problem based on Dinkelbach method,and then the block coordinate descent method is used to decompose the original complex problem into three independent sub-problems. Finally, the successive convex approximation method is used to solve the trajectory optimization sub-problem. The simulation results show that the proposed scheme and algorithm have obvious energy efficiency gains compared with the comparison scheme.

LoRa Backscatter Network Efficient Data Transmission Using RF Source Range Control

Networks based on backscatter communication provide wireless data transmission in the absence of a power source.A backscatter device receives a radio frequency(RF)source and creates a backscattered signal that delivers data;this enables new services in battery-less domains with massive Internet-of-Things(IoT)devices.Connectivity is highly energy-efficient in the context of massive IoT applications.Outdoors,long-range(LoRa)backscattering facilitates large IoT services.A backscatter network guarantees timeslot-and contention-based transmission.Timeslot-based transmission ensures data transmission,but is not scalable to different numbers of transmission devices.If contention-based transmission is used,collisions are unavoidable.To reduce collisions and increase transmission efficiency,the number of devices transmitting data must be controlled.To control device activation,the RF source range can be modulated by adjusting the RF source power during LoRa backscatter.This reduces the number of transmitting devices,and thus collisions and retransmission,thereby improving transmission efficiency.We performed extensive simulations to evaluate the performance of our method.

Performance Analysis of Three Spectrum Sensing Detection Techniques with Ambient Backscatter Communication in Cognitive Radio Networks

In wireless communications, the Ambient Backscatter Communication (AmBC) technique is a promisingapproach, detecting user presence accurately at low power levels. At low power or a low Signal-to-Noise Ratio(SNR), there is no dedicated power for the users. Instead, they can transmit information by reflecting the ambientRadio Frequency (RF) signals in the spectrum. Therefore, it is essential to detect user presence in the spectrum forthe transmission of data without loss or without collision at a specific time. In this paper, the authors proposed anovel Spectrum Sensing (SS) detection technique in the Cognitive Radio (CR) spectrum, by developing the AmBC.Novel Matched Filter Detection with Inverse covariance (MFDI), Cyclostationary Feature Detection with Inversecovariance (CFDI) and Hybrid Filter Detection with Inverse covariance (HFDI) approaches are used with AmBCto detect the presence of users at low power levels. The performance of the three detection techniques is measuredusing the parameters of Probability of Detection (PD), Probability of False Alarms (Pfa), Probability of MissedDetection (Pmd), sensing time and throughput at low power or low SNR. The results show that there is a significantimprovement via the HFDI technique for all the parameters.

Joint optimization for secure ambient backscatter communication in NOMA-enabled IoT networks

Non-Orthogonal Multiple Access(NOMA)has emerged as a novel air interface technology for massive connectivity in Sixth-Generation(6G)era.The recent integration of NOMA in Backscatter Communication(BC)has triggered significant research interest due to its applications in low-powered Internet of Things(IoT)networks.However,the link security aspect of these networks has not been well investigated.This article provides a new optimization framework for improving the physical layer security of the NOMA ambient BC system.Our system model takes into account the simultaneous operation of NOMA IoT users and the Backscatter Node(BN)in the presence of multiple EavesDroppers(EDs).The EDs in the surrounding area can overhear the communication of Base Station(BS)and BN due to the wireless broadcast transmission.Thus,the chief aim is to enhance link security by optimizing the BN reflection coefficient and BS transmit power.To gauge the performance of the proposed scheme,we also present the suboptimal NOMA and conventional orthogonal multiple access as benchmark schemes.Monte Carlo simulation results demonstrate the superiority of the NOMA BC scheme over the pure NOMA scheme without the BC and conventional orthogonal multiple access schemes in terms of system secrecy rate.

An Ultrasonic Backscatter Instrument for Cancellous Bone Evaluation in Neonates

Ultrasonic backscatter technique has shown promise as a noninvasive cancellous bone assessment tool. A novel ultrasonic backscatter bone diagnostic （UBBD） instrument and an in vivo application for neonatal bone evaluation are introduced in this study. The UBBD provides several advantages, including noninvasiveness, non- ionizing radiation, portability, and simplicity. In this study, the backscatter signal could be measured within 5 s using the UBBD. Ultrasonic backscatter measurements were performed on 467 neonates （268 males and 199 females） at the left calcaneus. The backscatter signal was measured at a central frequency of 3.5 MHz. The delay （-/-1） and duration （7-2） of the backscatter signal of interest （SOl） were varied, and the apparent integrated backscatter （AIB）, frequency slope of apparent backscatter （FSAB）, zero frequency intercept of apparent backscatter （FIAB）, and spectral centroid shift （SCS） were calculated. The results showed that the SOl selection had a direct influence on cancellous bone evaluation. The AIB and FIAB were positively correlated with the gestational age （｜R｜ up to 0.45, P 〈 0.001） when -/-1 was short （〈 8 μS）, while negative correlations （｜R｜ up to 0.56, P 〈 0.001） were commonly observed for T1 〉 10 IJS. Moderate positive correlations （IRI up to 0.45, P 〈 0.001） were observed for FSAB and SCS with gestational age when 71 was long （〉 10 μs）. The 7-2 mainly introduced fluctuations in the observed correlation coefficients. The moderate correlations observed with UBBD demonstrate the feasibility of using the backscatter signal to evaluate neonatal bone status. This study also proposes an explicit standard for in vivo SOl selection and neonatal cancellous bone assessment.

Variations in Optical Scattering and Backscattering by Organic and Inorganic Particulates in Chinese Lakes of Taihu, Chaohu and Dianchi

This study presents an investigation of the scattering and backscattering properties of the particulates in three Chinese inland lakes(the Taihu Lake, the Chaohu Lake and the Dianchi Lake) based on in situ measurements taken at 119 sites. We modeled the particulate scattering spectra using a wavelength-dependent power-law function, finding that the power-law exponents in the Taihu Lake and the Chaohu Lake differ from those in the Dianchi Lake but are similar to the values in the U.S. coastal waters. In contrast to the open ocean, the backscattering properties in the three lakes can not be determined only from chlorophyll-a concentration. The backscattering ratio spectra exhibit a wavelength dependence feature in all three lakes, generally decreasing with the increasing wavelength. Analysis results of the correlations between the backscattering ratio and the individual water quality parameters clearly show that there are distinctive relations among the three lakes, attributed primarily to different compositions of optically active materials in the three lakes. Analysis of the mass-specific scattering and backscattering coefficients shows that the coefficients at wavelength 532 nm in the Taihu Lake and Chaohu Lake are similar, but they are apparently different from those in the Dianchi Lake. Lastly, Model I multiple linear regressions were adopted to partition the mass-specific cross-sections for scattering and backscattering into organic and inorganic cross-sections to further interpret the scattering and backscattering properties. The relative contribution of organic and inorganic particulates to scattering and backscattering is clearly different among the three lakes. The scattering and backscattering properties of the particulates in the three inland lakes vary significantly based on our collected data. The results indicated that the existing semi-analytical water quality retrieval models of the Taihu Lake can not be applied perfectly to the Chaohu Lake and the Dianchi Lake.

A Green Paradigm for Internet of Things: Ambient Backscatter Communications

Internet of Things (IoT) has attracted extensive interest from both academia and industries, and is recognized as an ultimate infrastructure to connect everything at anytime and anywhere. The implementation of IoT generally faces the challenges from energy constraint and implementation cost. In this paper, we will introduce a new green communication paradigm, the ambient backscatter (AmBC), that could utilize the environmental wireless signals for both powering a tiny-cost device and backscattering the information symbols. Specifically, we will present the basic principles of AmBC, analyze its features and advantages, suggest its open problems, and predict its potential applications for our future IoT.

Microwave backscattering from the sea surface with breaking waves

Based on the effective medium approximation theory of composites, the whitecap-covered sea surface is treated as a medium layer of dense seawater droplets and air. Two electromagnetic scattering models of randomly rough surface are applied to the investigation of microwave backscattering of breaking waves driven by strong wind. The shapes of seawater droplets are considered by calculating the effective dielectric constant of the whitecap layer. The responses of seawater droplets shapes, such as sphere and ellipsoid, to the backscattering coefficient are discussed. Numerical results of the models are in good agreement with the experimental measurements of horizontally and vertically polarized backscattering at microwave frequency 13.9GHz and different incidence angles.

基于Backscatter技术的假冒源地址攻击研究

假冒源地址攻击具有容易实施不易被追溯的特点,这种攻击行为在互联网上日益猖獗。网络安全正面临着前所未有的挑战,对假冒源地址攻击的研究是一项重要课题。文中概述假冒源地址攻击的主要特征;阐释Backscatter技术和ICMP协议的工作原理;从宏观和微观2个视角,研究CAIDA网络Telescopes工程所捕获PCAP流量的最新数据。借助于数据挖掘和统计分析技术,从PCAP流量数据中得到ICMP报文,并对所得报文跟踪分析了假冒源地址攻击信息。经过统计汇总,得出假冒源地址攻击所对应主要类型,并对集中度高的几种做了深入研究,通过对这些攻击类型的详细分析,探索了最新DoS/DDoS中假冒源地址攻击方式及其危害。最后总结全文并展望下一步研究工作。

Energy-Efficient UAV Trajectory Design for Backscatter Communication: A Deep Reinforcement Learning Approach

Recently,backscatter communication(BC)has been introduced as a green paradigm for Internet of Things(IoT).Meanwhile,unmanned aerial vehicles(UAVs)can serve as aerial base stations(BSs)to enhance the performance of BC system thanks to their high mobility and flexibility.In this paper,we investigate the problem of energy efficiency(EE)for an energy-limited backscatter communication(BC)network,where backscatter devices(BDs)on the ground harvest energy from the wireless signal of a flying rotary-wing quadrotor.Specifically,we first reformulate the EE optimization problem as a Markov decision process(MDP)and then propose a deep reinforcement learning(DRL)algorithm to design the UAV trajectory with the constraints of the BD scheduling,the power reflection coefficients,the transmission power,and the fairness among BDs.Simulation results show the proposed DRL algorithm achieves close-to-optimal performance and significant EE gains compared to the benchmark schemes.

Analysis of Orange Peel Defect in St14 Steel Sheet by Electron Backscattered Diffraction (EBSD)

In this paper, the orange peel defect in the surface range of the st14 steel sheet has been investigated using the electron backscattered diffraction (EBSD) technique. It has been found that the orange peel defect in the st14 steel sheet was resulted from the local coarse grains which were produced during hot-rolling due to the critical deformation in dual-phase zone. During deep drawing, the coarse grains with {100}<001> microtexture can slip on the {112}<111> slip system to form bulging and yields orange peel defects, while the coarse grains with {112}<110> orientation do not form the defect as the Schmid factor of {112}<111> slip system in it equals zero.

Ambient Backscatter Communications over NOMA Downlink Channels

In this paper,we investigate the performance of commensal ambient backscatter communications(AmBC)that ride on a non-ortho go nal multiple access(NOMA)downlink transmission,in which a backscatter device(BD)splits part of its received signals from the base station(BS)for energy harvesting,and backscatters the remaining received signals to transmit information to a cellular user.Specifically,under the power consumption constraint at BD and the peak transmit power constraint at BS,we derive the optimal reflection coefficient at BD,the optimal total transmit power at BS,and the optimal power allocation at BS for each transmission block to maximize the ergodic capacity of the ambient backscatter transmission on the premise of preserving the outage performance of the NOMA downlink transmission.Furthermore,we consider a scenario where the BS is restricted by a maximum allowed average transmit power and the reflection coefficient at BD is fixed due to BD’s low-complexity nature.An algorithm is developed to determine the optimal total transmit power and power allocation at BS for this scenario.Also,a low-complexity algorithm is proposed for this scenario to reduce the computational complexity and the signaling overheads.Finally,the performance of the derived solutions are studied and compared via numerical simulations.

An analysis of the radar backscatter from oil-covered sea surfaces using moment method and Monte-Carlo simulation: preliminary results

An analysis of the radar backscattering from the ocean surface covered by oil spill is presented using a mi- crowave scattering model and Monte-Carlo simulation. In the analysis, a one-dimensional rough sea sur- face is numerically generated with an ocean waveheight spectrum for a given wind velocity. A two-layered medium is then generated by adding a thin oil layer on the simulated rough sea surface. The electric fields backscattered from the sea surface with two-layered medium are computed with the method of moments （MoM）, and the backscattering coefficients are statistically obtained with N independent samples for each oil-spilled surface using the Monte-Carlo technique for various conditions of surface roughness, oil-layer thickness, frequency, polarization and incidence angle. The numerical simulation results are compared with theoretical models for clean sea surfaces and SAR images of an off-spilled sea surface caused by the Hebei （Hebei province, China） Spirit oil tanker in 2007. Further, conditions for better oil spill extraction are sought by the numerical simulation on the effects of wind speed and oil-layer thickness at different inci- dence angles on the backscattering coefficients.

Detection of Coaxial Backscattered Electrons in SEM

We present a coaxial detection of the backscattered electrons in SEM. The lens-aperture has been used to filter in energy and focus the backscattered electrons. This particular geometry allows us to eliminate the low energy backscattered electrons and collect the backscattered electrons, which are backscattered close to the incident beam orientation. The main advantage of this geometry is adapted to topographic contrast attenuation and atomic number contrast enhancement. Thus this new SEM is very suitable to analyze the material composition.

Spatial Modulation-Based Ambient Backscatter: Bringing Energy Self-Sustainability to Massive Internet of Everything in 6G

Ambient backscatter communications(AmBC)is a new ultra-low-power communication paradigm,which holds great promise for enabling energy self-sustainability(ESS)to massive data-intensive Internet of Everything(IoE)devices in 6G.Recent advances improve throughput and reliability by adopting multiple-antenna techniques in conventional backscatter communications(CoBC),but they cannot be directly applied to AmBC devices for high spectral and energy efficiency due to the unknown RF source and minimalist design in backscatter tag.To fill this gap,we propose SM-backscatter,an AmBC-compatible system that greatly improves spectral efficiency while maintaining ultra-low-power consumption.Specifically,the SM-backscatter consists of two novel components:i)a multiple-antenna backscatter tag that adopts spatial modulation(SM),and ii)a joint detection algorithm that detects both backscatter and source signals.To this end,we theoretically obtain an optimal detector and propose two suboptimal detectors with low complexity.Subsequently,we derive the BERs of both the backscatter and source signals to analyze the communication performance by introducing a two-step algorithm.Our simulation results verify the correctness of the theoretical analysis and indicate that our system can significantly outperform existing solutions.

Ultrasonic backscatter characterization of cancellous bone using a general Nakagami statistical model

The goal of this study is to analyze the statistics of the backscatter signal from bovine cancellous bone using a Nakagami model and to evaluate the feasibility of Nakagami-model parameters for cancellous bone characterization. Ultrasonic backscatter measurements were performed on 24 bovine cancellous bone specimens in vitro and the backscatter signals were compensated for the frequency-dependent attenuation prior to the envelope detection. The statistics of the backscatter envelope were modeled using the Nakagami distribution. Our results reveal that the backscatter envelope mainly followed pre-Rayleigh distributions, and the deviations of the backscatter envelope from Rayleigh distribution decreased with increasing bone density. The Nakagami shape parameter(i.e., m) was significantly correlated with bone densities(R = 0.78–0.81, p < 0.001) and trabecular microstructures(|R| = 0.46–0.78, p < 0.05). The scale parameter(i.e.,?) and signal-to-noise ratio(SNR) also yielded significant correlations with bone density and structural features. Multiple linear regressions showed that bone volume fraction(BV/TV) was the main predictor of the Nakagami parameters,and microstructure produced significantly independent contribution to the prediction of Nakagami distribution parameters,explaining an additional 10.2% of the variance at most. The in vitro study showed that statistical parameters derived with Nakagami model might be useful for cancellous bone characterization, and statistical analysis has potential for ultrasonic backscatter bone evaluation.

Crystallographic Characteristic of Intermetallic Compounds in Al-Si-Mg Casting Alloys Using Electron Backscatter Diffraction

The Al-Si-Mg alloy which can be strengthened by heat treatment is widely applied to the key components of aerospace and aeronautics. Iron-rich intermetallic compounds are well known to be strongly influential on mechanical properties in Al-Si-Mg alloys. But intermetallic compounds in cast Al-Si-Mg alloy intermetallics are often misidentified in previous metallurgical studies. It was described as many different compounds, such as AlFeSi, Al8Fe2Si, Al5（Fe, Mn）3Si2 and so on. For the purpose of solving this problem, the intermetallic compounds in cast Al-Si alloys containing 0.5% Mg were investigated in this study. The iron-rich compounds in Al-Si-Mg casting alloys were characterized by optical microscope（OM）, scanning electron microscope（SEM）, energy dispersive X-ray spectrometer（EDS）, electron backscatter diffraction（EBSD） and X-ray powder diffraction（XRD）. The electron backscatter diffraction patterns were used to assess the crystallographic characteristics of intermetallic compounds. The compound which contains Fe/Mg-rich particles with coarse morphologies was Al8FeMg3Si6 in the alloy by using EBSD. The compound belongs to hexagonal system, space group P6_2m, with the lattice parameter a=0.662 nm, c=0.792 nm. The β-phase is indexed as tetragonal Al3FeSi2, space group I4/mcm, a=0.607 nm and c=0.950 nm. The XRD data indicate that Al8FeMg3Si6 and Al3FeSi2 are present in the microstructure of Al-7Si-Mg alloy, which confirms the identification result of EBSD. The present study identified the iron-rich compound in Al-Si-Mg alloy, which provides a reliable method to identify the intermetallic compounds in short time in Al-Si-Mg alloy. Study results are helpful for identification of complex compounds in alloys.

Assessment of acoustic backscatter intensity surveying on deep-sea ferromanganese crust: Constraints from Weijia Guyot, western Pacific Ocean

Near-bottom observation data from the manned deep submersible Jiaolong with high-precision underwater positioning data from Weijia Guyot,Magellan Seamounts in the Western Pacific Ocean are reported.Three substrate types were identified:Sediment,ferromanganese crust,and ferromanganese crust with a thin cover of sediment.The ferromanganese crusts show clear zoning and their continuity is usually disturbed by sediments on areas of the mountainside with relatively gentle slope gradients.The identified substrate spatial distributions correspond to acoustic backscatter intensity data,with regions of high intensity always including crust development and regions of low intensity always having sediment.Therefore,acoustic backscatter intensity surveying appears useful in the delineation and evaluation of crust resources,although further more work is needed to develop a practicable methodology.