GNSS spoofing detection for single antenna receivers via CNR variation monitoring

In this paper,a method for spoofing detection based on the variation of the signal’s carrier-to-noise ratio(CNR)is proposed.This method leverages the directionality of the antenna to induce varying gain changes in the signals across different incident directions,resulting in distinct CNR variations for each signal.A model is developed to calculate the variation value of the signal CNR based on the antenna gain pattern.This model enables the differentiation of the variation values of the CNR for authentic satellite signals and spoofing signals,thereby facilitating spoofing detection.The proposed method is capable of detecting spoofing signals with power and CNR similar to those of authentic satellite signals.The accuracy of the signal CNR variation value calculation model and the effectiveness of the spoofing detection method are verified through a series of experiments.In addition,the proposed spoofing detection method works not only for a single spoofing source but also for distributed spoofing sources.

Non-invasive estimation of the powder size distribution from a single speckle image

Non-invasive characterization of powders may take one of two approaches:imaging and counting individual particles;or relying on scattered light to estimate the particle size distribution(PSD)of the ensemble.The former approach runs into practical difficulties,as the system must conform to the working distance and other restrictions of the imaging optics.The latter approach requires an inverse map from the speckle autocorrelation to the particle sizes.The principle relies on the pupil function determining the basic sidelobe shape,whereas the particle size spread modulates the sidelobe intensity.We recently showed that it is feasible to invert the speckle autocorrelation and obtain the PSD using a neural network,trained efficiently through a physics-informed semi-generative approach.In this work,we eliminate one of the most time-consuming steps of our previous method by engineering the pupil function.By judiciously blocking portions of the pupil,we sacrifice some photons but in return we achieve much enhanced sidelobes and,hence,higher sensitivity to the change of the size distribution.The result is a 60×reduction in total acquisition and processing time,or 0.25 seconds per frame in our implementation.Almost real-time operation in our system is not only more appealing toward rapid industrial adoption,it also paves the way for quantitative characterization of complex spatial or temporal dynamics in drying,blending,and other chemical and pharmaceutical manufacturing processes.

Multiplexed stimulated emission depletion nanoscopy(mSTED)for 5-color live-cell long-term imaging of organelle interactome

Stimulated emission depletion microscopy(STED)holds great potential in biological science applications,especially in studying nanoscale subcellular structures.However,multi-color STED imaging in live-cell remains challenging due to the limited excitation wavelengths and large amount of laser radiation.Here,we develop a multiplexed live-cell STED method to observe more structures simultaneously with limited photo-bleaching and photo-cytotoxicity.By separating live-cell fluorescent probes with similar spectral properties using phasor analysis,our method enables five-color live-cell STED imaging and reveals long-term interactions between different subcellular structures.The results here provide an avenue for understanding the complex and delicate interactome of subcellular structures in live-cell.

A Comprehensive Method for Evaluating Precision of Transfer Alignment on a Moving Base

In this study, we propose the use of the Degree of Alignment(DOA) in engineering applications for evaluating the precision of and identifying the transfer alignment on a moving base. First, we derive the statistical formula on the basis of estimations. Next, we design a scheme for evaluating the transfer alignment on a moving base, for which the attitude error cannot be directly measured. Then, we build a mathematic estimation model and discuss Fixed Point Smoothing(FPS), Returns to Scale(RTS), Inverted Sequence Recursive Estimation(ISRE), and Kalman filter estimation methods, which can be used when evaluating alignment accuracy. Our theoretical calculations and simulated analyses show that the DOA reflects not only the alignment time and accuracy but also differences in the maneuver schemes, and is suitable for use as an integrated evaluation index. Furthermore, all four of these algorithms can be used to identify the transfer alignment and evaluate its accuracy. We recommend RTS in particular for engineering applications. Generalized DOAs should be calculated according to the tactical requirements.

Study of high-precision earth sensor with triple-FOV

Earth sensors are widely used in spacecraft for attitude determination. They need to have a very large field of view(FOV)( > 120°) and relatively low accuracy while being used in the aircrafts around orbit. A triple-FOV infrared earth sensor is proposed in this paper. It uses three pieces of standard infrared detectors with a wavelength range of 14;16μm,to sense the horizontal circle by detecting the infrared light emitted from the earth. From which,the geocentric vector can be obtained. A mathematic model is established and a validation model is set up to provide input parameters for the mathematic model. The simulation results of the two models show that the output of the mathematic model coincides with the known parameters. Based on the above analysis,a prototype has been built and tested. The test results show that the angle measurement error is about 0. 002° and hence such a triple-FOV earth sensor is capable to provide high-precision position information for autonomous navigation.

A review of liquid crystal spatial light modulators:devices and applications

Spatial light modulators,as dynamic flat-panel optical devices,have witnessed rapid development over the past two decades,concomitant with the advancements in micro-and opto-electronic integration technology.In particular,liquid-crystal spatial light modulator(LC-SLM)technologies have been regarded as versatile tools for generating arbitrary optical fields and tailoring all degrees of freedom beyond just phase and amplitude.These devices have gained significant interest in the nascent field of structured light in space and time,facilitated by their ease of use and real-time light manipulation,fueling both fundamental research and practical applications.Here we provide an overview of the key working principles of LC-SLMs and review the significant progress made to date in their deployment for various applications,covering topics as diverse as beam shaping and steering,holography,optical trapping and tweezers,measurement,wavefront coding,optical vortex,and quantum optics.Finally,we conclude with an outlook on the potential opportunities and technical challenges in this rapidly developing field.

Precision Controlling of Frequency Difference for Elastic-Stress Birefringence He-Ne Dual-Frequency Lasers

Birefringence-Zeeman dual frequency lasers are capable of producing frequency difference from several kilohertz to hundreds of megahertz, but the precision of giving and stabilizing of the beat frequency still needs improvement to the range of ±200 kHz. We design a new elastic force-exerting device comprised of the bottom part, two arms and two pieces of force-exerting sheets. The frequency difference smoothly tuning is realized with this device in a large range of 2 MHz to 20 MHz. Power-balance frequency stabilization system is used to investigate characters of the temperature, frequency difference and laser power. The precision of the frequency difference has reach up to ±100 kHz after system temperature balance. Analyses of the laser frequency difference and power character are carried out.

Measurement of T wave in magnetocardiography using tunnel magnetoresistance sensor

Several critical clinical applications of magnetocardiography(MCG)involve its T wave.The T wave’s accuracy directly affects the diagnostic accuracy of MCG for ischemic heart disease and arrhythmogenic.Tunnel magnetoresistance(TMR)attracts attention as a new MCG measurement technique.However,the T waves measured by TMR are often drowned in noise.The accuracy of T waves needs to be discussed to determine the clinical value of MCG measured by TMR.This study uses an improved empirical mode decomposition(EMD)algorithm and averaging to eliminate the noise in the MCG measured by TMR.The MCG signals measured by TMR are compared with MCG measured by the optically pumped magnetometer(OPM)to judge its accuracy.Using the MCG measured by OPM as a reference,the relative errors in time and amplitude of the T wave measured by TMR are 3.4%and 1.8%,respectively.This is the first demonstration that TMR can accurately measure the time and amplitude of MCG T waves.The ability to provide reliable T wave data illustrates the significant clinical application value of TMR in MCG measurement.

Analyzing the Effect of the Intra-Pixel Position of Small PSFs for Optimizing the PL of Optical Subpixel Localization

Subpixel localization techniques for estimating the positions of point-like images captured by pixelated image sensors have been widely used in diverse optical measurement fields.With unavoidable imaging noise,there is a precision limit(PL)when estimating the target positions on image sensors,which depends on the detected photon count,noise,point spread function(PSF)radius,and PSF’s intra-pixel position.Previous studies have clearly reported the effects of the first three parameters on the PL but have neglected the intra-pixel position information.Here,we develop a localization PL analysis framework for revealing the effect of the intra-pixel position of small PSFs.To accurately estimate the PL in practical applications,we provide effective PSF(e PSF)modeling approaches and apply the Cramér–Rao lower bound.Based on the characteristics of small PSFs,we first derive simplified equations for finding the best PL and the best intra-pixel region for an arbitrary small PSF;we then verify these equations on real PSFs.Next,we use the typical Gaussian PSF to perform a further analysis and find that the final optimum of the PL is achieved at the pixel boundaries when the Gaussian radius is as small as possible,indicating that the optimum is ultimately limited by light diffraction.Finally,we apply the maximum likelihood method.Its combination with e PSF modeling allows us to successfully reach the PL in experiments,making the above theoretical analysis effective.This work provides a new perspective on combining image sensor position control with PSF engineering to make full use of information theory,thereby paving the way for thoroughly understanding and achieving the final optimum of the PL in optical localization.

Rapid stabilization of stochastic quantum systems in a unified framework

Rapid stabilization of general stochastic quantum systems is investigated based on the rapid stability of stochastic differential equations.We introduce a Lyapunov-LaSalle-like theorem for a class of nonlinear stochastic systems first,based on which a unified framework of rapidly stabilizing stochastic quantum systems is proposed.According to the proposed unified framework,we design the switching state feedback controls to achieve the rapid stabilization of singlequbit systems,two-qubit systems,and N-qubit systems.From the unified framework,the state space is divided into two state subspaces,and the target state is located in one state subspace,while the other system equilibria are located in the other state subspace.Under the designed state feedback controls,the system state can only transit through the boundary between the two state subspaces no more than two times,and the target state is globally asymptotically stable in probability.In particular,the system state can converge exponentially in(all or part of)the state subspace where the target state is located.Moreover,the effectiveness and rapidity of the designed state feedback controls are shown in numerical simulations by stabilizing GHZ states for a three-qubit system.

Mastering air combat game with deep reinforcement learning

Reinforcement learning has been applied to air combat problems in recent years,and the idea of curriculum learning is often used for reinforcement learning,but traditional curriculum learning suffers from the problem of plasticity loss in neural networks.Plasticity loss is the difficulty of learning new knowledge after the network has converged.To this end,we propose a motivational curriculum learning distributed proximal policy optimization(MCLDPPO)algorithm,through which trained agents can significantly outperform the predictive game tree and mainstream reinforcement learning methods.The motivational curriculum learning is designed to help the agent gradually improve its combat ability by observing the agent's unsatisfactory performance and providing appropriate rewards as a guide.Furthermore,a complete tactical maneuver is encapsulated based on the existing air combat knowledge,and through the flexible use of these maneuvers,some tactics beyond human knowledge can be realized.In addition,we designed an interruption mechanism for the agent to increase the frequency of decisionmaking when the agent faces an emergency.When the number of threats received by the agent changes,the current action is interrupted in order to reacquire observations and make decisions again.Using the interruption mechanism can significantly improve the performance of the agent.To simulate actual air combat better,we use digital twin technology to simulate real air battles and propose a parallel battlefield mechanism that can run multiple simulation environments simultaneously,effectively improving data throughput.The experimental results demonstrate that the agent can fully utilize the situational information to make reasonable decisions and provide tactical adaptation in the air combat,verifying the effectiveness of the algorithmic framework proposed in this paper.

Proposal for a realtime Einstein-synchronization-defined satellite virtual clock

Realization of high performance satellite onboard clock is vital for various positioning, navigation, and timing applications. For further improvement of the synchronization-based satellite time and frequency references, we propose a geosynchronous(GEO) satellite virtual clock concept based on ground–satellite synchronization and present a beacon transponder structure for its implementation(scheduled for launch in 2025), which does not require atomic clocks to be mounted on the satellite. Its high performance relies only on minor modifications to the existing transponder structure of GEO satellites. We carefully model the carrier phase link and analyze the factors causing link asymmetry within the special relativity. Considering that performance of such synchronization-based satellite clocks is primarily limited by the link's random phase noise, which cannot be adequately modeled, we design a closed-loop experiment based on commercial GEO satellites for pre-evaluation. This experiment aims at extracting the zero-means random part of the ground-satellite Ku-band carrier phase via a feedback loop. Ultimately, we obtain a 1σ value of 0.633 ps(two-way link), following the Gaussian distribution. From this result, we conclude that the proposed real-time Einstein-synchronization-defined satellite virtual clock can achieve picosecond-level replication of onboard time and frequency.

Study on 6-DOF active vibration-isolation system of the ultra-precision turning lathe based on GA-BP-PID control for dynamic loads

The vibration disturbance from an external environment affects the machining accuracy of ultra-precision machining equipment.Most active vibration-isolation systems(AVIS)have been developed based on static loads.When a vibration-isolation load changes dynamically during ultra-precision turning lathe machining,the system parameters change,and the efficiency of the active vibration-isolation system based on the traditional control strategy deteriorates.To solve this problem,this paper proposes a vibration-isolation control strategy based on a genetic algorithm-back propagation neural network-PID control(GA-BP-PID),which can automatically adjust the control parameters according to the machining conditions.Vibration-isolation simulations and experiments based on passive vibration isolation,a PID algorithm,and the GA-BP-PID algorithm under dynamic load machining conditions were conducted.The experimental results demonstrated that the active vibration-isolation control strategy designed in this study could effectively attenuate vibration disturbances in the external environment under dynamic load conditions.This design is reasonable and feasible.

A real-time performance improvement method for composite time scale

The composite time scale(CTS)provides a stable,accurate,and reliable time scale for modern society.The improvement of CTS’s real-time performance will improve its stability,which strengths related applications’performance.Aiming at this goal,a method achieved by determining the optimal calculation interval and accelerating adjustment stage is proposed in this paper.The determinants of the CTS’s calculation interval(characteristics of the clock ensemble,the measurement noise,the time and frequency synchronization system’s noise and the auxiliary output generator noise floor)are studied and the optimal calculation interval is obtained.We also investigate the effect of ensemble algorithm’s initial parameters on the CTS’s adjustment stage.A strategy to get the reasonable initial parameters of ensemble algorithm is designed.The results show that the adjustment stage can be finished rapidly or even can be shorten to zero with reasonable initial parameters.On this basis,we experimentally generate a distributed CTS with a calculation interval of 500 s and its stability outperforms those of the member clocks when the averaging time is longer than1700 s.The experimental result proves that the CTS’s real-time performance is significantly improved.

A dual adaptive unscented Kalman filter algorithm for SINS-based integrated navigation system

In this study, the problem of measuring noise pollution distribution by the intertial-based integrated navigation system is effectively suppressed. Based on nonlinear inertial navigation error modeling, a nested dual Kalman filter framework structure is developed. It consists of unscented Kalman filter (UKF)master filter and Kalman filter slave filter. This method uses nonlinear UKF for integrated navigation state estimation. At the same time, the exact noise measurement covariance is estimated by the Kalman filter dependency filter. The algorithm based on dual adaptive UKF (Dual-AUKF) has high accuracy and robustness, especially in the case of measurement information interference. Finally, vehicle-mounted and ship-mounted integrated navigation tests are conducted. Compared with traditional UKF and the Sage-Husa adaptive UKF (SH-AUKF), this method has comparable filtering accuracy and better filtering stability. The effectiveness of the proposed algorithm is verified.

A step to the decentralized real-time timekeeping network

The composite time scale(CTS) provides an accurate and stable time-frequency reference for modern science and technology. Conventional CTS always features a centralized network topology, which means that the CTS is accompanied by a local master clock. This largely restricts the stability and reliability of the CTS. We simulate the restriction and analyze the influence of the master clock on the CTS. It proves that the CTS's long-term stability is also positively related to that of the master clock, until the region dominated by the frequency drift of the H-maser(averaging time longer than ~10~5s).Aiming at this restriction, a real-time clock network is utilized. Based on the network, a real-time CTS referenced by a stable remote master clock is achieved. The experiment comparing two real-time CTSs referenced by a local and a remote master clock respectively reveals that under open-loop steering, the stability of the CTS is improved by referencing to a remote and more stable master clock instead of a local and less stable master clock. In this way, with the help of the proposed scheme, the CTS can be referenced to the most stable master clock within the network in real time, no matter whether it is local or remote, making democratic polycentric timekeeping possible.

Disparity estimation for multi-scale multi-sensor fusion

The perception module of advanced driver assistance systems plays a vital role.Perception schemes often use a single sensor for data processing and environmental perception or adopt the information processing results of various sensors for the fusion of the detection layer.This paper proposes a multi-scale and multi-sensor data fusion strategy in the front end of perception and accomplishes a multi-sensor function disparity map generation scheme.A binocular stereo vision sensor composed of two cameras and a light deterction and ranging(LiDAR)sensor is used to jointly perceive the environment,and a multi-scale fusion scheme is employed to improve the accuracy of the disparity map.This solution not only has the advantages of dense perception of binocular stereo vision sensors but also considers the perception accuracy of LiDAR sensors.Experiments demonstrate that the multi-scale multi-sensor scheme proposed in this paper significantly improves disparity map estimation.

Accuracy Analysis of Stewart Platform Based on Interval Analysis Method

A Stewart platform is introduced in thc 500 m aperture spherical radio telescope（FAST） as an accuracy adjustable mechanism for teed receivers. Accuracy analysis is the basis of accuracy design. However, a rapid and effective accuracy analysis method for parallel manipulator is still needed. In order to enhance solution efficiency, an interval analysis method（lA method） is introduced to solve the terminal error bound of the Stewart platform with detailed solution path. Taking a terminal pose of the Stewart platform in FAST as an example, the terminal error is solved by the Monte Carlo method（MC method） by 4 980 s, the stochastic mathematical method（SM method） by 0.078 s, and the IA method by 2.203 s. Compared with MC method, the terminal error by SM method leads a 20% underestimate while the IA method can envelop the real error bound of the Stewart platform. This indicates that the IA method outperforms the other two methods by providing quick calculations and enveloping the real error bound of the Stewart platform. According to the given structural error of the dimension parameters of the Stewart platform, the IA method gives a maximum position error of 19.91 mm and maximum orientation error of 0.534°, which suggests that the IA method can be used for accuracy design of the Stewart platfbnn in FAST. The 1A method presented is a rapid and effective accuracy analysis method for Stewart platform.

Type Synthesis of 4-DOF Parallel Kinematic Mechanisms Based on Grassmann Line Geometry and Atlas Method

Many methods are proposed to deal with the type synthesis of parallel kinematic mechanisms（PKMs）, but most of them are less intuitive to some extent. Thus, to propose a concise and intuitive type synthesis method for engineering application is a very challenging issue, which should be further studied in the field. Grassmann line geometry, which can investigate the dimensions of spatial line-clusters in a concise way, is taken as the mathematic foundation. Atlas method is introduced to visually describe the degrees of freedom（DOFs） and constraints of a mechanism, and the dual rule is brought in to realize the mutual conversion of the freedom-space and constraint-space. Consequently, a systematic method based on Grassmann line geometry and Atlas method is generated and the entire type synthesis process is presented. Three type 4-DOF PKMs, i.e., 1T3R, 2T2R and 3T1R（T： translational DOF; R： rotational DOF）, are classified according to the different combinations of the translational DOFs and rotational DOFs. The type synthesis of 4-DOF PKMs is carried out and the possible configurations are thoroughly investigated. Some new PKMs with useful functions are generated during this procedure. The type synthesis method based on Grassmann line geometry and Atlas method is intuitive and concise, and can reduce the complexity of the PKMs＇ type synthesis. Moreover, this method can provide theoretical guidance for other PKMs＇ type synthesis and engineering application. A novel type synthesis method is proposed, which solves the existing methods＇ problems in terms of complicated, not intuitive and unsuitable for practical application.

Electrospinning of Flexible Poly(vinyl alcohol)/MXene Nanofiber-Based Humidity Sensor Self-Powered by Monolayer Molybdenum Diselenide Piezoelectric Nanogenerator

Two-dimensional material has been widely investigated for potential applications in sensor and flexible electronics.In this work,a self-powered flexible humidity sensing device based on poly(vinyl alcohol)/Ti_(3)C_(2)Tx(PVA/MXene)nanofibers film and monolayer molybdenum diselenide(MoSe2)piezoelectric nanogenerator(PENG)was reported for the first time.The monolayer MoSe_(2)-based PENG was fabricated by atmospheric pressure chemical vapor deposition techniques,which can generate a peak output of 35 mV and a power density of42 mW m^(-2).The flexible PENG integrated on polyethylene terephthalate(PET)substrate can harvest energy generated by different parts of human body and exhibit great application prospects in wearable devices.The electrospinned PVA/MXene nanofiber-based humidity sensor with flexible PET substrate under the driven of monolayer MoSe_(2) PENG,shows high response of~40,fast response/recovery time of 0.9/6.3 s,low hysteresis of 1.8%and excellent repeatability.The self-powered flexible humidity sensor yields the capability of detecting human skin moisture and ambient humidity.This work provides a pathway to explore the high-performance humidity sensor integrated with PENG for the self-powered flexible electronic devices.