Delay Error Research Articles

Performance Analysis of GPS/BDS Broadcast Ionospheric Models in Standard Point Positioning during 2021 Strong Geomagnetic Storms

The broadcast ionospheric model is one of the main methods for eliminating ionospheric delay errors for the Global Navigation Satellite Systems (GNSS) single-frequency users. GPS Klobuchar model (GPSK8) is the widely used broadcast ionospheric model for GPS, while BDS usually implements the BDS Klobuchar model (BDSK8) and BeiDou Global Broadcast Ionospheric Delay Correction Model (BDGIM). Geomagnetic storms may cause interference within the ionosphere and near-Earth space, compromising the accuracy of ionospheric models and adversely affecting the navigation satellite systems. This paper analyzes the static Standard Point Positioning (SPP) accuracy of GPS and BDS by implementing the broadcast ionospheric models and then investigates the impact of strong geomagnetic storms occurring in 2021 on positioning accuracy. The results show that the global 3D positioning accuracy (95%) of GPS + GPSK8, BDS + BDSK8, and BDS + BDGIM are 3.92 m, 4.63 m, and 3.50 m respectively. BDS has a better positioning accuracy in the northern hemisphere than that of the southern hemisphere, while the opposite is valid for GPS. In the mid-latitude region of the northern hemisphere, BDS + BDSK8 and BDS + BDGIM have similar positioning accuracy and are both better than GPS + GPSK8. The positioning accuracy after applying those three broadcast ionospheric models shows the superior performances of winter and summer over spring and autumn (based on the northern hemisphere seasons). With the exception of during winter, nighttime accuracy is better than that of daytime. The strong geomagnetic storm that occurred on the day of year (DOY) 132, 2021 has an impact on the positioning accuracy for only a small number of stations; however, the global average positioning accuracy is not significantly affected. The strong geomagnetic storms that occurred in DOY 307 and DOY 308 have a significant impact on the positioning accuracy of dozens of stations, and the global average positioning accuracy is affected to a certain extent, with some stations experiencing a serious loss of accuracy. Decreased degrees in positioning accuracy is proportional to the intensity of the geomagnetic storm. Of the 33 IGS Multi-GNSS Experiment (MGEX) stations worldwide, those located in the low and mid-latitudes are more significantly affected by the geomagnetic storms compared with higher latitudes. Evident fluctuations of the positioning errors existed during the strong geomagnetic storms, with an increase in extreme values, particularly in the up direction.

A Hybrid True-Time and Phase-Delayed Approach for Millimeter-Wave Beam Steering

In this research study, a novel hybrid approach to beam steering based on the combination of true time delay and phase shift to enable continuous beam steering with minimal beam squint in wideband mm-wave transceivers is investigated. With modern high-speed communication links in the mm-wave spectrum requiring ever higher bandwidths, and losses increasing with frequency, there is a need for steerable arrays in mobile applications. This steering capability is commonly realized by phase shifters, which enable continuous beam direction control, but produce significant beam squint at large bandwidths or steering directions. An alternative is to use a time-delayed control, which resolves the squint issue but covers only a limited number of beam directions, producing considerable loss and being large in size. This research work presents the first 2-bit time delay stage operating above 200 GHz. In addition, a novel approach is described to enable broadband continuous beam control with minimal beam squint; this is achieved by combining the time delay circuit with a 90° vector-sum phase shifter. To prove the concept, the circuit is realized in a 130-nm SiGe Bipolar Complementary Metal Oxide Semiconductor (CMOS) (BiCMOS) technology. At 4.33 mW of dc power consumption, the small-signal gain is −8.6 dB at a 3-dB band of 220–250 GHz, resulting in 12.8% of relative bandwidth. The time delay stage provides coarse beam direction control with a maximum steering angle of 43.9° resulting from a maximum delay of 1.47 ps with a resolution of 0.39 ps. Across all tuning states, the root-mean-square delay error is less than 23.7 fs. The following phase shifter enables fine direction control while also compensating ±1.5 dB of gain variation resulting from the time delay. This is achieved while reducing the area consumption to half of what is required for comparable true time delay circuits. In a minimal <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$2\times 1$ </tex-math></inline-formula> antenna array, this enables continuous beam direction control between ±54.6° while limiting the beam squint to less than 2.5°, equating to a more than 75% reduction in comparison to the common phase shift approach.

A Novel SPMSM Sensorless Drive Using Discrete-Time Synchronous-Frequency Adaptive Observer Under Low Frequency Ratio

To improve the stability and accuracy of the estimated position using the conventional sliding mode observer (CSMO) under low frequency ratio (LFR), this article proposes a novel discrete-time synchronous-frequency adaptive observer (SFAO) for surface-mounted permanent magnet synchronous motor (SPMSM) sensorless drives. The proposed SFAO has merits of high amplitude and zero-phase lag of resonant controller at synchronous frequency. The sign function and the low-pass filter (LPF) of CSMO in the proposed observer can be removed and conducive to dispel the inherent chattering of the CSMO as well as phase shift produced by the LPF. Then, taking into account the digital control delay and discretization truncation error, an exact complex-vector discrete-time model in the stationary coordinate is developed. Based on that, the direct discrete-time domain design approach is utilized in the proposed observer, which can be devised by pole placement directly on complex <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">z</i> -domain to assure the stability and position estimation accuracy under LFR. Finally, the availability of the proposed discrete-time SFAO scheme is verified via experiments on a 2.1-kW SPMSM drive.

InSAR Atmospheric Delay Correction Model Integrated from Multi-Source Data Based on VCE

With the rapid development of interferometric synthetic aperture radar (InSAR) measurement technology, its measurement accuracy requirements are increasing. Atmospheric delay errors must be corrected, especially in the case of crustal deformation monitoring, the 20% variation of tropospheric water vapor among InSAR pairs generally produces range from 10 cm to 14 cm deformation errors. Such errors can be of the same magnitude as the annual changes in crustal deformation, or even greater, masking crustal deformation information and seriously affecting the results of crustal deformation monitoring. Therefore, in order to obtain a more accurate InSAR atmospheric delay correction model, this paper calculated and integrated atmospheric delays that were estimated by different sources, including the 37 pressure levels of the fifth generation of the European Centre for Medium-Range Weather Forecasts (ECMWF)) numerical weather prediction model, ECMWF Reanalysis v5 (ERA5), and Global Navigation Satellite System (GNSS) measurement data from the crustal movement observation network of China, based on the variance component estimation (VCE) weighting method. The results showed that the integrated model, based on the VCE method, is better than the generic atmospheric correction online service (GACOS) model for InSAR measuring of crustal deformation. The precision in monitoring crustal deformations was improved by approximately 5 mm, the correlation coefficient of atmospheric delay errors and crustal deformations improved from 0.287 to 0.347, and accuracy improved by approximately 25%. However, the improvement in accuracy was limited because of system error decoherence that was induced by atmospheric noise caused by abundant vegetation or snow cover. Therefore, in order to achieve more accurate results, we recommend the adoption of the multi-source integrated atmospheric delay correction model, based on the VCE method, for InSAR high-precision measuring of crustal deformation and seismic activities.

Elevation Multi-Channel Imbalance Calibration Method of Digital Beamforming Synthetic Aperture Radar

The digital beamforming synthetic aperture radar (DBF-SAR) is proposed by scholars as a promising solution to overcome the constraint of the minimum antenna area of the traditional single-channel SAR to achieve high resolution and wide swath (HRWS) by scan-on-receive (SCORE) in the elevation multiple channel. However, the inevitable channel imbalance between the elevation channels of DBF-SAR will degrade the DBF-SAR image quality. In this paper, we present a method to estimate the sampling time delay error, amplitude error and phase error based on the external calibration data. For the sampling time delay deviation, we adopt to calculate the statistical average of the position deviation of several external calibration points in the reference channel image with that of the error channel image. To avoid noise interference, we image the DBF-SAR original echo-carrying amplitude information to obtain the amplitude error between channels by dividing the absolute values of the complex image data of the error channel. Due to the phase error between channels, the image contrast will decrease. Therefore, the problem of estimating the phase error can be transformed into the problem of maximizing the image contrast. So, in this paper, we use the gradient descent method to optimally estimate the phase error. Finally, the effectiveness of the method is verified by the simulation of airborne measured data and simulation data.

The Longest Delay: A 14.5 yr Campaign to Determine the Third Time Delay in the Lensing Cluster SDSS J1004+4112

We present new light curves for the four bright images of the five image cluster-lensed quasar gravitational lens system SDSS J1004+4112. The light curves span 14.5 yr and allow the measurement of the time delay between the trailing bright quasar image D and the leading image C. When we fit all four light curves simultaneously and combine the models using the Bayesian information criterion, we find a time delay of Δt DC = 2458.47 ± 1.02 days (6.73 yr), the longest ever measured for a gravitational lens. For the other two independent time delays we obtain Δt BC = 782.20 ± 0.43 days (2.14 yr) and Δt AC = 825.23 ± 0.46 days (2.26 yr), in agreement with previous results. The information criterion is needed to weight the results for light curve models with different polynomial orders for the intrinsic variability and the effects of differential microlensing. The results using the Akaike information criterion are slightly different, but, in practice, the absolute delay errors are all dominated by the ∼4% cosmic variance in the delays rather than the statistical or systematic measurement uncertainties. Despite the lens being a cluster, the quasar images show slow differential variability due to microlensing at the level of a few tenths of a magnitude.

Wideband Radio Frequency Interference Cancellation for High-Sensitivity Phased Array Receivers With True Time Delays and Truncated Hadamard Projection

Radio frequency interference (RFI) is a significant challenge for high-sensitivity phased array instruments. RFI can be suppressed using digital signal processing, but to improve dynamic range for wideband RFI, it can be desirable to remove interference in the analog domain before sampling. In previous work, it has been shown that analog true time delay (TTD) stages with a truncated Hadamard transform can place a wide-band spatial null on RFI from a given direction of arrival. We show that TTD and Hadamard projection is mathematically equivalent to a bank of classical narrow-band subspace projection beamformers, but with a structure that allows efficient implementation in either analog circuitry or digital hardware. We analyze how loss in the TTD blocks and time delay errors affect beamformer performance and propose methods for calibrating time delays. Simulation results show that ideal TTD and Hadamard projection matches the bank of subspace projection beamformers and places deep nulls over wideband RFI signals while achieving SNR performance comparable to the maximum signal-to-interference and -noise ratio beamformer.

Removing systematics-induced 21-cm foreground residuals by cross-correlating filtered data

Observations of the redshifted 21-cm signal emitted by neutral hydrogen represent a promising probe of large-scale structure in the universe. However, cosmological 21-cm signal is challenging to observe due to astrophysical foregrounds which are several orders of magnitude brighter. Traditional linear foreground removal methods can optimally remove foregrounds for a known telescope response but are sensitive to telescope systematic errors such as antenna gain and delay errors, leaving foreground contamination in the recovered signal. Non-linear methods such as principal component analysis, on the other hand, have been used successfully for foreground removal, but they lead to signal loss that is difficult to characterize and requires careful analysis. In this paper, we present a systematics-robust foreground removal technique which combines both linear and non-linear methods. We first obtain signal and foreground estimates using a linear filter. Under the assumption that the signal estimate is contaminated by foreground residuals induced by parameterizable systematic effects, we infer the systematics-induced contamination by cross-correlating the initial signal and foreground estimates. Correcting for the inferred error, we are able to subtract foreground contamination from the linearly filtered signal up to the first order in the amplitude of the telescope systematics. In simulations of an interferometric 21-cm survey, our algorithm removes foreground leakage induced by complex gain errors by one to two orders of magnitude in the power spectrum. Our technique thus eases the requirements on telescope characterization for modern and next-generation 21-cm cosmology experiments.

Inter-Satellite Single-Difference Ionospheric Delay Interpolation Model for PPP-RTK and Its Positioning Performance Verification

In PPP-RTK, obtaining accurate atmospheric delay information for the user through interpolation is one of the keys to achieving high-precision real-time positioning. The ionospheric delay that is extracted by a reference network based on uncalibrated phase delay (UPD) products is often difficult to separate from errors such as receiver code hardware delay and UPD reference error. Inter-satellite single-difference (SD) ionospheric delay information is typically provided to the user. This paper proposes an interpolation model that uses the atmospheric delay coefficient to represent the SD ionospheric delay, based on the mean position of the ionospheric pierce point (IPP) of each satellite pair and the center position of the network, which is called the differenced surface model (DSM). We chose four scenarios to compare the interpolation accuracy of the proposed model with the inverse distance-based linear interpolation method (DIM) and USM based on the difference between the longitude and latitude of the reference and ionospheric pierce point (IPP) of every satellite (here, we call it USM for short). The four scenarios involve a medium-scale reference network with an average distance to the reference station of 41 km, a large-scale reference network with an average distance to the reference station of 98 km, and out-of-network users, and a network with a common minimum of three reference stations. The results show that the root mean square (RMS) of the SD residuals of ionospheric delay for DSM were 1.4, 3.2, 2.2, and 1.4 cm, respectively, for the four scenarios that were considered, which are slightly better delay values than those that were achieved using DIM and USM. For the scenario with three reference stations, the interpolation accuracies of DIM and DSM were no different from those for four reference stations, indicating that the server can still try to provide ionospheric correction service under the condition of fewer reference stations. In contrast, USM could not provide service because it lacked the sufficient number of reference stations. DSM was used as the ionospheric delay interpolation model to analyze GPS and Galileo dual-system PPP-RTK positioning performance. In addition, the atmospheric parameter constraint method of users was used in PPP-RTK in reference networks of different scales. For the 41-km and 98-km reference networks, the time to first fix (TTFF) were 14.5 s and 33.1 s, respectively, and the mean RMS values for the east (E), north (N), and up (U) directions were 0.80, 0.93, and 2.72 cm, respectively, and 1.0, 1.1, and 4.0 cm, respectively, for a period of 5 min after convergence. The fixing rate and positioning accuracy of DSM during the 5-min period were better than those of DIM when the same empirical model was used to determine the mean square error of atmospheric delay.

Task-Space Cooperative Tracking Control for Networked Uncalibrated Multiple Euler–Lagrange Systems

Task-space cooperative tracking control of the networked multiple Euler–Lagrange systems is studied in this paper. On the basis of establishing kinematic and dynamic modeling of a Euler–Lagrange system, an innovative task-space coordination controller is designed to deal with the time-varying communicating delays and uncertainties. First, in order to weaken the influence of the uncertainty of kinematic and dynamic parameters on the control error of the system, the product of the Jacobian matrix and the generalized spatial velocity are linearly parameterized; thus, the unknown parameters are separated from known parameters. The online estimation of uncertain parameters is realized by designing parameters and by proposing new adaptive laws for the dynamic and kinematic parameters. Furthermore, to describe the transmission of time-varying delay errors among networked agents, a new error term is introduced, obtained by adding the observation error and tracking error, and the coefficient of the network mutual coupling term related to the time-varying delay rate is added with reference to the generalized space velocity and task-space velocity of the Lagrange systems. In the end, the influence of the time-varying delay on the cooperative tracking control error of the networked multiple Euler–Lagrange systems is eliminated. With the help of Lyapunov stability theory, the tracking errors and synchronization errors of this system are calculated by introducing the Lyapunov–Krasovskii functional; the asymptotic convergence results rigorously prove the stability of the adaptive cooperative control systems. The simulation results verify the excellent performance of the controller.

A Pulse Delay Control Method by External Trigger to Underwater Illumination

Aiming at the problem of high precision pulse synchronization control in digital signal processing, we proposed an external trigger synchronization control method by double-layer hierarchical delay. The method consists of hardware circuit and control algorithm. The hardware circuit employs the main control unit and the digital delay unit, in which the main control unit makes the coordination between the digital delay unit and the peripheral circuit, and the two-layer digital delay unit performs multiple fixed period delay operation according to the instruction of the main control unit. The control algorithm adopts the two-layer hierarchical control mode, decomposes the total delay time according to the two-layer delay precision, and performs the combined delay in the two-layer digital delay unit successively. The delay result achieves a fixed delay of less than 40 ns, a delay step of 0.25 ns and a delay range of less than 1000 ns. The method adopts the combination of hardware and software to realize the external trigger double-layer hierarchical delay synchronization control, which has the characteristics of high delay step and pulse width adjustment accuracy and small cumulative delay error. It is suitable for the application scenarios of lidar echo signal and ultra-wide spectrum power source synthesis.

Toward on-sky adaptive optics control using reinforcement learning

Context. The direct imaging of potentially habitable exoplanets is one prime science case for the next generation of high contrast imaging instruments on ground-based, extremely large telescopes. To reach this demanding science goal, the instruments are equipped with eXtreme Adaptive Optics (XAO) systems which will control thousands of actuators at a framerate of kilohertz to several kilohertz. Most of the habitable exoplanets are located at small angular separations from their host stars, where the current control laws of XAO systems leave strong residuals. Aims. Current AO control strategies such as static matrix-based wavefront reconstruction and integrator control suffer from a temporal delay error and are sensitive to mis-registration, that is, to dynamic variations of the control system geometry. We aim to produce control methods that cope with these limitations, provide a significantly improved AO correction, and, therefore, reduce the residual flux in the coronagraphic point spread function (PSF). Methods. We extend previous work in reinforcement learning for AO. The improved method, called the Policy Optimization for Adaptive Optics (PO4AO), learns a dynamics model and optimizes a control neural network, called a policy. We introduce the method and study it through numerical simulations of XAO with Pyramid wavefront sensor (PWFS) for the 8-m and 40-m telescope aperture cases. We further implemented PO4AO and carried out experiments in a laboratory environment using Magellan Adaptive Optics eXtreme system (MagAO-X) at the Steward laboratory. Results. PO4AO provides the desired performance by improving the coronagraphic contrast in numerical simulations by factors of 3–5 within the control region of deformable mirror and PWFS, both in simulation and in the laboratory. The presented method is also quick to train, that is, on timescales of typically 5–10 s, and the inference time is sufficiently small (&lt;ms) to be used in real-time control for XAO with currently available hardware even for extremely large telescopes.

Research on Fingerprint and Hyperbolic Fusion Positioning Algorithm Based on 5G Technology

With the development of the Internet of Things technology, higher requirements are put forward for the positioning accuracy of objects. This paper presents an indoor fusion positioning algorithm based on the 5th Generation Mobile Communication Technology (5G), which effectively solves two problems. The first is that fingerprint positioning is susceptible to environmental changes and results in inaccurate fingerprint matching. The second is the problem of the hyperbolic positioning algorithm based on the line-of-sight fluctuating too much in complex indoor environments. This paper uses a 5G flexible subcarrier interval of Orthogonal Frequency Division Multiplexing (OFDM) to significantly reduce the time delay error of Time Of Arrival (TOA), and an improved genetic algorithm and the weighted hyperbolic algorithm are used to estimate the optimal position coordinates. In the offline database establishment stage of fingerprint positioning, the Channel State Information-reference signal (CSI-RS) of multiple-beam sets provides high-dimensional information for subsequent training and prediction. The online stage cooperates with the improved residual network model to make predictions. Finally, the positioning information and the error distribution function generated by the two positioning processes are simultaneously used as the input of the Kalman filter to obtain the precise position coordinates. The simulation results show that in complex indoor scenes where line-of-sight propagation and non-line-of-sight propagation paths are mixed, the accuracy of this method can reach below 0.82 m. Thus, the positioning accuracy is significantly improved compared with other methods, which can meet most indoor scene positioning needs.

Simulation Study on the Influence of Sampling Delay on the Accuracy of Energy Metabolism Measurement

Indirect energy metabolism measurement is the gold standard for providing nutritional support for critical illness. The accuracy of the measurement data directly affects the outcome of the disease. In order to study the influence of sampling delay on the accuracy of energy metabolism measurement under mechanical ventilation, the Matlab/Simulink platform and respiratory electrical model were used for simulation and quantitative analysis. The results show that the error of indirect energy metabolism measurement increases with the increase of sampling delay, the error of sampling delay in mechanical ventilation mode is larger than that of spontaneous breathing, and the error of sampling delay in PCV mode of mechanical ventilation is larger than that in VCV mode. Therefore, there should be different sampling delay compensation strategies under severe mechanical ventilation and its different control modes.

SHAKING: Adjusted spherical harmonics adding KrigING method for near real-time ionospheric modeling with multi-GNSS observations

Precise positioning based on Global Navigation Satellite System (GNSS) technique requires high accuracy ionospheric total electron content (TEC) correction models to account for the ionospheric path delay errors. We present an adjusted Spherical Harmonics Adding KrigING method (SHAKING) approach for regional ionospheric vertical TEC (VTEC) modeling in real time. In the proposed SHAKING method, the VTEC information over the sparse observation data area is extrapolated by the Adjusted Spherical Harmonic (ASH) function, and the boundary distortion in regional VTEC modeling is corrected by the stochastic VTEC estimated using Kriging interpolation. Using real-time GPS, GLONASS and BDS-2/3 data streams of the Crust Movement Observation Network of China (CMONOC), the SHAKING-based regional ionospheric VTEC maps are re-constructed over China and its boundary regions. Compared to GNSS VTECs derived from the independent stations, the quality of SHAKING solution improves by 13–31% and 6–33% with respect to the ASH-only solution during high and low geomagnetic periods, respectively. Compared to the inverse distance weighting (IDW) generated result, significant quality improved of SHAKING-based VTEC maps is also observed, especially over the edge areas with an improvement of 60–80%. Overall, the proposed SHAKING method exhibits notable advantage over the existing regional VTEC modeling techniques, which can be used for regional TEC modeling and associated high-precision positioning applications.

Assessment of ZTD Derived from COSMIC Occultation Data with ECWMF, Radiosondes, and GNSS.

Global Navigation Satellite System (GNSS) signals generate slant tropospheric delays when they pass through the atmosphere, which is recognized as the main source of error in many spatial geodetic applications. The zenith tropospheric delay (ZTD) derived from radio occultation data is of great significance to atmospheric research and meteorology and needs to be assessed in the use of precision positioning. Based on the atmPrf, sonPrf, and echPrf data from the Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) Data Analysis and Archiving Center (CDAAC) from 1 January to 31 December 2008 and 2012, we obtained the ZTDs of the radio occultation data (occZTD) and the corresponding radiosonde (sonZTD) and ECWMF data (echZTD). The ZTDs derived from ground-based global positioning system (GPS) observations from the International GNSS Service (IGS) were corrected to the lowest tangent point height of the matched radio occultation profile by the barometric height formula (gnsZTD). The statistical results show that the absolute values of the bias between occZTD and echZTD, sonZTD, or gnsZTD are less than 5 mm, and the standard deviations are approximately 20 mm or less, indicating that occZTD had significant accuracy in the GNSS positioning model even when the local spherical symmetry assumption error was introduced when the Abel inversion algorithm was used to obtain the refractive index profile of atmPrf. The effects of the horizontal/vertical matching resolution and the variation in the station height/latitude on the biases of occZTD and gnsZTD were analyzed. The results can be used to quantify the performance of radio occultation data for tropospheric delay error correction in dynamic high-precision positioning.

Tropospheric Delay Correction of VLBI Stations for the Real‐Time Trajectory Determination of the Chang'E‐5 Spacecraft

AbstractThe Chang'E‐5 (CE‐5) spacecraft was launched on 24 November 2020 with the purpose to implement unmanned lunar surface sampling and return. Very long baseline interferometry (VLBI) technique played an important role in real‐time precise trajectory determination and attitude determination of the CE‐5 spacecraft in the Earth to Moon transfer, circumlunar, landing, and ascending phases. However, tropospheric delay is one of the main error sources for VLBI observations which has to be corrected accurately for precise trajectory determination. To deal with this error properly, a prediction model (TRO_P) and a method with Global Navigation Satellite System observations (TRO_G) are proposed for tropospheric zenith delay correction for real‐time and 30 min latency trajectory determination of the CE‐5 spacecraft, respectively. The results demonstrate that the mean root mean square (RMS) of residual error of VLBI delay and delay rate for TRO_P are 0.62 ns and 0.75 ps/s at low elevation angle, respectively. Moreover, the improvement for the mean RMS of VLBI delay using TRO_G is 39.5% meaning from 0.43 to 0.26 ns compared with that using the method with meteorological data (TRO_S) at low elevation angle. This study can provide a reference for tropospheric delay calibration for trajectory determination of the spacecraft using VLBI or other techniques.

Cross-Regional Transmission Control for Satellite Network-Assisted Vehicular Ad Hoc Networks

Vehicular ad hoc networks (VANETs) have attracted increasing attention in cross-regional communication. The interconnection between VANETs and satellite networks expands their communication range. To improve the transmission performance of heterogeneous networks composed of VANETs and satellite networks, this paper proposes an end-to-end transmission control scheme for satellite network-assisted VANETs, analyzes the bandwidth delay product of multihop VANETs through heterogeneous networks, and establishes a transmission control model applicable to cross-regional environments. To address the long delay and high bit error rate in heterogeneous networks, the model designs the congestion window in the slow start and congestion avoidance of the transmission scheme. The data transmission volume is increased in the slow start, and various packet losses are distinguished in congestion avoidance. The experimental results show that the scheme can achieve good transmission performance in heterogeneous networks composed of VANETs and satellite networks. The results show that VANETs data can be effectively transmitted in heterogeneous networks. Compared with the traditional transmission scheme, this simple and practical end-to-end transmission control scheme can improve speed by 83.49 kbps and reduce transmission duration time of FTP server by <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$4.72\times 10^{3}$ </tex-math></inline-formula> s. The results of this study provide a reference for massive data transmission in heterogeneous networks of VANETs and satellite networks.

Data Integrity Attack in Dynamic State Estimation of Smart Grid: Attack Model and Countermeasures

A smart grid integrates advanced sensors, efficient measurement methods, progressive control technologies, and other techniques and devices to achieve safe, efficient and economical operation of the grid system. However, the diversified and open environment of a smart grid makes energy and information of the smart grid vulnerable to malicious attacks. As a representative cyber-physical attack, the data integrity attack has an extremely severe impact on the grid operation for it can bypass the traditional detection mechanisms by adjusting the attack vector. In this paper, we first present the attack strategy against dynamic state estimation of power grid in the perspective of adversary and formulate the data integrity attack detection problem that has the characteristic of sequential decision making as a partially observable Markov decision process. Then, a deep reinforcement learning-based approach is proposed to detect against data integrity attacks, which utilizes the Long Short-Term Memory layer to extract the state features of previous time steps in determining whether the system is currently under attack. Moreover, the noisy networks are employed to ensure effective agent exploration, which prevents the agent from sticking to the non-optimal policy. The principle of a multi-step learning is adopted to increase the estimation accuracy of Q value. To address the sparse rewards problem, the prioritized experience replay is proposed to increase training efficiency. Simulation results demonstrated that the proposed detection approach surpasses the benchmarks in the comparison metrics: delay error rate and false rate. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —In this paper, we present a deep reinforcement learning-based algorithm to defend against the data integrity attacks of smart grid. Most of the previous works discretized the system states and utilized the current state information to identify whether the system is under attack. For this reason, the detection policy may totally ignored the continuously changing characteristics of the grid states, which will lead to poor detection performance. Moreover, the attacked system states only accounts for a small part of the entire grid operation states, the probability of sampling the experience containing the attack state is extremely small, which limits the learning efficiency of previous RL-based detection approaches. In order to increase the accuracy of detection, we first present the attack strategy against power grid’s dynamic state estimation in the perspective of adversary and formulate the partially observable Markov decision process model of attack detection problem. Moreover, we propose a deep reinforcement learning-based detection approach combining the LSTM network to extract the system state features of the previous time steps to determine whether the system is currently being attacked. To address the sparse rewards problem, the prioritized experience replay is used to increase learning efficiency. The experiments demonstrate the effectiveness of proposed detection scheme compared with benchmarks in terms of detection delay as well as accuracy. In conclusion, the proposed detection scheme is helpful in defending against the data integrity attacks without obtaining the opponent’s strategy in advance and can be conveniently applied to the real-world security management system of smart grid.

Realization of Music-Assisted Interactive Teaching System Based on Virtual Reality Technology.

Virtual reality technology has attracted researchers' attention because it can provide users with a virtual interactive learning environment. Based on the theory of virtual reality technology, this paper proposes the system model design and architecture of virtual interactive music-assisted interactive teaching and realizes key technologies such as modeling, music-assisted interactive teaching scene interaction, and database access. In the simulation process, based on the VRML/X3D bottom interactive system template, after comprehensive application research, comparative analysis of various modeling methods, the system verified the use of digital cameras combined with the modeling technology based on music elements to collaboratively establish VRML virtual model connections. For inline node function, we combined it with Outline3D to realize VRML integration and then use VizX3D, X3D-Edit to build X3D model and realize the conversion from VRML to X3D, which solves the system completeness problem of music-assisted interactive teaching. The experimental results show that, according to the statistical analysis of the data after the experiment, when the position changes in the virtual 3D music-assisted interactive teaching scene, it will be displayed in the plane layer, and the real-time coordinates of the virtual music-assisted interactive teaching scene displayed in HTML have case. By analyzing the scenes and dynamic effects in the works, the effects of the virtual world can be better displayed through the performance of details. The better accuracy and delay error reached 89.7% and 3.11%, respectively, which effectively improved the effect and feasibility of applying virtual reality technology to music-assisted interactive teaching.