Delay Error Research Articles

A Geodetic and Astrometric VLBI Experiment at 22/43/88/132 GHz

Extending geodetic and astrometric Very Long Baseline Interferometry (VLBI) observations from traditional centimeter wavebands to millimeter wavebands offers numerous scientific potentials and benefits. However, it was considered quite challenging due to various factors, including the increased effects of atmospheric opacity and turbulence at millimeter wavelengths. Here, we present the results of the first geodetic-mode VLBI experiment, simultaneously observing 82 sources at 22/43/88/132 GHz (K/Q/W/D bands) using the Korean VLBI Network (KVN). We introduced the frequency phase transfer (FPT) method to geodetic VLBI analysis, an approach for calibrating atmospheric phase fluctuations at higher frequencies by transferring phase solutions from lower frequencies. With a 2 minute scan, FPT improved the signal-to-noise ratio of most fringes, some by over 100%, thereby enhancing the detection rate of weak sources at millimeter wavebands. Additionally, FPT reduced systematic errors in group delay and delay rate, with the weighted root mean squares (WRMS) of the postfitting residuals decreasing from 25.0 to 20.5 ps at the W band and from 39.3 to 27.6 ps at the D band. There were no notable differences observed in calibrating atmospheric phase fluctuations at the K band (WRMS = 12.4 ps) and Q band (WRMS = 11.8 ps). This experiment demonstrated that the millimeter waveband can be used for geodetic and astrometric applications with high precision.

Overlap syndromes in sarcoidosis: Unveiling the masquerader

As a multi system granulomatous disease, clinical presentations of sarcoidosis are highly variable. In the absence of a stereotypical clinical presentation such as asymptomatic bilateral hilar adenopathy, Lofgren's syndrome, or lupus pernio, a diagnosis of sarcoidosis typically requires 1) compatible clinical presentation, 2) histologic evidence of granulomatous inflammation, and 3) the exclusion of other causes. The clinical presentation of sarcoidosis is often nonspecific and a variety of other causes of granulomatous inflammation can make diagnosing sarcoidosis a challenge for clinicians. “Overlap syndromes” are often used to describe clinical presentations of sarcoidosis that share histologic and clinical features of other diseases, or when the diagnosis of sarcoidosis is made in association with the coexistence of another diagnosis with similar clinical or histologic findings. Because of the risk of diagnostic delay and diagnostic errors, it is vital for clinicians to be familiar with overlap syndromes in sarcoidosis. The coexistence of sarcoidosis with other diseases can also significantly impact disease management and outcomes. This article will review the most current published data on overlap syndromes in sarcoidosis to aid clinicians in diagnosing and managing these complex patients.

Distributed driving electric vehicle lateral stability control method considering time delay

This paper introduces a novel control method to address lateral stability challenge in distributed driving electric vehicles. By considering inherent time delay and unknown sensor measurement error generated from design, manufacturing, and external disturbances, the proposed approach achieves better robustness. Firstly, we establish a two-degree-of-freedom (2-DOF) dynamic model for lateral motion of an electric vehicle driven by in-wheel motors (EV-DIM). Based on this model, a control system considering time delay and unknown sensor measurement error is constructed. The control system incorporates a controller based on a dual domination gains observer, and its global asymptotic stability is rigorously proved by the Lyapunov method. Numerical simulations and co-simulations via CarSim and Simulink verify the method’s effectiveness. Compared to the sliding mode control, the proposed method shows better performance which indicates this approach promising for enhancing lateral stability of an electric vehicle.

Optimal wideband digital fractional-order differentiators using gradient based optimizer

In this paper, we propose a novel optimization approach to designing wideband infinite impulse response (IIR) digital fractional order differentiators (DFODs) with improved accuracy at low frequency bands. In the new method, the objective function is formulated as an optimization problem with two tuning parameters to control the error distribution over frequencies. The gradient based optimizer (GBO) is effectively employed on the proposed objective function. A wide range of design examples are presented to illustrate the effectiveness of the proposed approach. The proposed approximations are compared to those of recent literature in terms magnitude, phase, and group delay errors. The result reveal that our method can attain approximations have a favorable low frequency performance (with about 60% of relative magnitude error reduction) and maintain a comparable accuracy at most of the Nyquist band to those of the existing ones. Thus, our approximations can be attractive for low frequency applications.

Correction of systematic low-frequency time delay errors in THz systems by absorption line shape optimization.

Time-domain terahertz systems can face challenges due to systematic delay errors introduced by the employed delay mechanism, potentially leading to poor data quality. This article introduces a procedure to address these challenges by correcting low-frequency systematic errors that distort the acquired spectra and incorrectly diminish narrow absorption features. Our procedure solves an optimization problem aiming to find the corrected time-signal pairs that maximize the depth of narrow absorption features, and we highlight how the flexibility of the procedure, in principle, allows for correcting error profiles of arbitrary shape. We demonstrate the effectiveness of this approach through experiments using both simulated and experimentally recorded THz data, and the results show significant improvements in spectral accuracy. We believe this can pave the way for more reliable and precise terahertz spectroscopy measurements, enhancing its applications in various scientific and industrial fields.

Optimisation of synchronisation control parameters for enhanced bilateral teleoperation system

Abstract Bilateral teleoperation systems encounter challenges in achieving synchronisation between master and slave robots due to communication time delays. This paper addresses the instability caused by these delays and proposes a solution through advanced control algorithms. Nonlinear optimisation algorithms might only sometimes deliver solutions in the allotted time, particularly when handling complicated, high-dimensional issues or when optimisation iterations are extensive. The study first develops a comprehensive mathematical model encompassing the dynamics and communication intricacies of both master and slave sides in teleoperation. By recognising the limitations of existing proportional-derivative controllers in compensating for communication errors, a sequential quadratic programming-proportional-integral-derivative (SQP-PID) controller is introduced. This controller accumulates and rectifies synchronisation delay errors, ensuring precise control without steady-state deviations. The proposed SQP-PID controller stands out for its ability to handle steady-state errors effectively, offering swift response and maintaining stability. Leveraging the SQP optimisation algorithm, it intelligently tunes the parameters, minimising synchronisation errors. The approach capitalises on the simplicity, performance, and robustness of the SQP-PID controller, providing a promising avenue for enhancing bilateral teleoperation systems’ accuracy and stability, maintaining initial discrepancy with a best fitness value of 0.98 % in varied operating conditions.

Phase extraction method resistant to the nonlinearity for dynamic frequency scanning interferometry.

Dynamic frequency scanning interferometry (DFSI) offers the advantage of drift immunity in distance measurements, making it widely used in industrial applications. However, the nonlinear scanning characteristics of lasers can induce non-stationarity in interference signals, complicating the phase extraction process and decreasing the accuracy of dynamic distance measurement. This study investigates the phase extraction of non-stationary signals with multiple frequency components and proposes a second-order group delay error compensation algorithm. By utilizing complex Morlet wavelets and second-order time-varying signals to construct a group delay model, this algorithm enables precise extraction of non-stationary phases within specific frequency bands, thereby mitigating phase extraction errors in DFSI systems. Experimental results showcase the effectiveness of the algorithm in reducing the standard deviation of distance measurements from 20.26 μm to 11.47 μm by mitigating the nonlinearity. Furthermore, dynamic experiments validate the stability of the proposed algorithm in detecting vibrating and uniformly moving targets.

Performance Analysis of Antenna-relay Selection in CNOMA Systems under Practical Impairments

Selection strategies prove to be a valuable approach in mitigating complexity associated with antenna selection (AS) and relay selection (RS), optimizing signal transmission through a streamlined number of antennas/relays, and enhancing overall system performance. This paper offers a comprehensive analysis, deriving closed-form expressions for the outage probability (OP) and throughput in proposed scenarios that leverage the best relay selection (BRS) and transmit antenna selection (TAS) protocol for cooperative non-orthogonal multiple access (CNOMA), along with partial relay selection (PRS) and TAS protocol for CNOMA. The study extends to Rayleigh fading channels, considering practical impairments such as successful interference cancellation (SIC) error, channel estimation error (CEE), and feedback delay error. In comparing the proposed system to conventional CNOMA, our findings highlight the substantial impact of SIC, CEE, and feedback delay imperfections on the performance of both proposed scenarios. Notably, the application of BRS-based TAS protocol outperforms PRS-based TAS in terms of OP and throughput. The close alignment between analytical, asymptotic, and simulation results attests to the credibility of conducted analysis.

Metrics of Astrometric Variability in the International Celestial Reference Frame. I. Statistical Analysis and Selection of the Most Variable Sources

Using very long baseline interferometry data for the sources that comprise the third International Celestial Reference Frame (ICRF3), we examine the quality of the formal source-position uncertainties of ICRF3 by determining the excess astrometric variability (unexplained variance) for each source as a function of time. We also quantify multiple qualitatively distinct aspects of astrometric variability seen in the data, using a variety of metrics. Average position offsets, statistical dispersion measures, and coherent trends over time as explored by smoothing the data are combined to characterize the most and least positionally stable ICRF3 sources. We find a notable dependence of the excess variance and statistical variability measures on decl., as is expected for unmodeled ionospheric delay errors and the Northern Hemisphere–dominated network geometries of most astrometric and geodetic observing campaigns.

Development and verification of real-time hybrid model test delay compensation method for monopile-type offshore wind turbines

The real-time hybrid model (RTHM) test is adept at addressing the scale contradiction, the lack of fidelity in wind modelling in hydrodynamic testing facilities and spatial constraints inherent in conventional monopile-type offshore wind turbine (OWT) model testing methods, thus emerging as an effective avenue for conducting physical model tests of Monopile-type OWTs. This method entails the reproduction of aerodynamic loads or platform motions using loading device or vibration tables. Time delays in the physical attributes of the loading device and signal transmission processes within the system can result in error accumulation, with the potential to impact overall system stability. Moreover, time delay compensation algorithms for hybrid model test systems with force control loading can easily generate excessive noise, leading to system divergence. As a result, time delay has emerged as a technical challenge in the RTHM test. To address this issue, this paper has developed second-order and third-order polynomial extrapolation algorithms, alongside an adaptive compensation algorithm. The adaptive compensation algorithm employs the least squares method to identify parameters of the loading system, enabling it to address variations in the time delay of the experimental system caused by the nonlinearity of the loading system and changes in the physical properties of the model. The feasibility and effects of time delay compensation for various algorithms are validated through numerical simulation. Results indicate that the adaptive compensation algorithm surpasses second and third-order polynomial extrapolation compensation algorithms in terms of accuracy and compensation effectiveness. To validate the applicability of the adaptive compensation algorithm, a RTHM test was conducted. Across rotor thrust force (RotThrust) and tower top displacement, there was an average reduction of approximately 5 % and 9 % in the maximum and minimum synchronization errors, respectively. This highlights the efficacy of the delay compensation algorithm in practical applications, notably diminishing time delay errors within the experimental system. The adaptive compensation algorithm continuously adjusts and updates parameters, enhancing the adaptability of the compensation process to time-varying systems.

Comparative analysis of Vedic multiplier using Vedic sutras with existing multipliers in biomedical application

In today's computer world, a lot of real-time applications require rapid processing units. Arithmetic Logic Units (ALU) and Multiply-Accumulate (MAC) are the fundamental parts of these circuits and are necessary for their effective and rapid operation. The most significant prevalent part of digital signal processing devices is multipliers. The multiplier, adder, and registers need to be changed in order to maintain accuracy and increase execution speed, which will improve the performance of the ALU and MAC. The development of greater multipliers is being given priority for application in processors because of the increasing constraints on latency. To accelerate multiplication, it is essential to develop quicker multipliers. Vedic multipliers are preferred over different current expansions due to their low power consumption, fast operation, and efficient use of space. Vedic mathematics-based algorithms are often utilized to build quick, low-power multipliers. In addition to simulation results, this section covers the four sutras of Vedic mathematics: Urdhva Tiryakbhyam, Ekadhikena Purvena, Ekanyunena Purvena, and Nikhilam. Vedic multipliers are also compared to a variety of modern multipliers, including booth, Wallace, and array multipliers. All of the sutras are evaluated according to area, speed, power, propagation delay, and mean relative error (MRE) in the current research. The results of the study will be applied in the biomedical field.

A Sequence-to-Sequence Car-Following Model for Addressing Driver Reaction Delay and Cumulative Error in Multi-Step Prediction

A Sequence-to-Sequence Car-Following Model for Addressing Driver Reaction Delay and Cumulative Error in Multi-Step Prediction

A practical approach for calibration of MMW MIMO near-field imaging

Near-field millimeter-wave (MMW) imaging techniques typically employ multiple-input-multiple-output (MIMO) arrays to obtain high-resolution images. However, the image quality can be seriously affected by array miscalibration. In this paper, a simple and efficient calibration method for MMW MIMO arrays is proposed and validated with real data. The approach makes use of a metal plate as a reference target to collect data in the presence and absence of the reference target. By processing the two sets of received data, we can reduce the effects of inter-channel coupling and environmental interference. The method calculates the reflected position and transmission distance of the electromagnetic wave based on the transmission model of the electromagnetic wave by the metal plate. And the transmission distance difference of all transceiver pairs is eliminated. Then, the delay error and phase error between the channels are successively calculated. Numerical simulations and real measured data are processed to validate the proposed calibration method. The results demonstrate that it is an effective tool for calibrating MMW MIMO arrays.

Characterizing the spatial structure and aliasing effect of ocean tide loading on InSAR measurements

Ocean tide loading (OTL) displacements, shown as long-wavelength errors in Interferometric Synthetic Aperture Radar (InSAR), must be considered in large-scale applications. Despite efforts to explore the impacts of OTL on InSAR, most studies use individual interferograms and simple metrics, which fail to characterize the spatial structure of OTL. Moreover, the OTL contribution to InSAR time series remains relatively unexplored. The aliasing effect and related biases due to OTL, which are common to space-geodetic time series, are primarily theoretical with few practical observations for InSAR. This study comprehensively explores the statistical properties of OTL and their impacts on InSAR measurements, using the Southwest United Kingdom and Northwest France as study areas. Spatially, OTL artifacts on interferograms exhibit an escalating magnitude along the principal direction that aligns with the coastline's orientation. Temporally, the aliasing effect originating from OTL introduces periodic signals with prominent 15/64-day cycles into the Sentinel-1 InSAR time series, causing high velocity biases (up to ∼1 cm/yr) and uncertainties (up to ∼5 mm/yr) for short time spans. Applying OTL correction mitigates the noise level in the displacement time series, leading to a 16% improvement in accuracy, as validated against the Global Navigation Satellite System (GNSS). The study proposes the “overlapping effect” concept, which links InSAR tropospheric delay errors and OTL effects. It underscores the importance of accurate error assessment and removal. Neglecting this interaction may result in a 13% underestimation of the tropospheric error correction efficacy.

Performance of the neural network-based prediction model in closed-loop adaptive optics.

Adaptive optics (AO) technology is an effective means to compensate for atmospheric turbulence, but the inherent delay error of an AO system will cause the compensation phase of the deformable mirror (DM) to lag behind the actual distortion, which limits the correction performance of the AO technology. Therefore, the feed-forward prediction of atmospheric turbulence has important research value and application significance to offset the inherent time delay and improve the correction bandwidth of the AO system. However, most prediction algorithms are limited to an open-loop system, and the deployment and the application in the actual AO system are rarely reported, so its correction performance improvement has not been verified in practice. We report, to our knowledge, the first successful test of a deep learning-based spatiotemporal prediction model in an actual 3 km laser atmospheric transport AO system and compare it with the traditional closed-loop control methods, demonstrating that the AO system with the prediction model has higher correction performance.

InSAR-DEM Block Adjustment Model for Upcoming BIOMASS Mission: Considering Atmospheric Effects

The unique P-band synthetic aperture radar (SAR) instrument, BIOMASS, is scheduled for launch in 2024. This satellite will enhance the estimation of subcanopy topography, owing to its strong penetration and fully polarimetric observation capability. In order to conduct global-scale mapping of the subcanopy topography, it is crucial to calibrate systematic errors of different strips through interferometric SAR (InSAR) DEM (digital elevation model) block adjustment. Furthermore, the BIOMASS mission will operate in repeat-pass interferometric mode, facing the atmospheric delay errors introduced by changes in atmospheric conditions. However, the existing block adjustment methods aim to calibrate systematic errors in bistatic mode, which can avoid possible errors from atmospheric effects through interferometry. Therefore, there is still a lack of systematic error calibration methods under the interference of atmospheric effects. To address this issue, we propose a block adjustment model considering atmospheric effects. Our model begins by employing the sub-aperture decomposition technique to form forward-looking and backward-looking interferograms, then multi-resolution weighted correlation analysis based on sub-aperture interferograms (SA-MRWCA) is utilized to detect atmospheric delay errors. Subsequently, the block adjustment model considering atmospheric effects can be established based on the SA-MRWCA. Finally, we use robust Helmert variance component estimation (RHVCE) to build the posterior stochastic model to improve parameter estimation accuracy. Due to the lack of spaceborne P-band data, this paper utilized L-band Advanced Land Observing Satellite (ALOS)-1 PALSAR data, which is also long-wavelength, to emulate systematic error calibration of the BIOMASS mission. We chose climatically diverse inland regions of Asia and the coastal regions of South America to assess the model’s effectiveness. The results show that the proposed block adjustment model considering atmospheric effects improved accuracy by 72.2% in the inland test site, with root mean square error (RMSE) decreasing from 10.85 m to 3.02 m. Moreover, the accuracy in the coastal test site improved by 80.2%, with RMSE decreasing from 16.19 m to 3.22 m.

Conditional adaptive time series compensation and control design for multi-axial real-time hybrid simulation

The structural performance of critical infrastructure during extreme events requires testing to understand the complex dynamics. Shake table testing of buildings to evaluate structural integrity is expensive and requires special facilities that can allow for the construction of large-scale test specimens. An attractive alternative is a cyber-physical testing technique known as Real-Time Hybrid Simulation (RTHS), where a large-scale structure is decomposed into physical and numerical substructures. A transfer system creates the interface between physical and numerical substructures. The challenge occurs when using multiple actuators connected with a coupler (i.e., transfer system) to create translation and rotation at the interface. Tracking control strategies aim to reduce time delay errors to create the desired displacements that account for the complex dynamics. This paper proposes two adaptive control methodologies for multi-axial real-time hybrid simulations that improve capabilities for a higher degree of coupling, boundary, complexity, and noise reduction. One control method integrates the feedback proportional derivative integrator (PID) control with a conditional adaptive time series (CATS) compensation and inverse decoupler. The second proposed control method is based on a coupled Model Predictive Control (MPC) with the CATS compensation. The performance of the proposed methods is evaluated using the virtual multi-axial benchmark control problem consisting of a steel frame as the experimental substructure. The transfer system consists of a coupler that connects two hydraulic actuators generating the translation and rotation acting at the joint. Through sensitivity analysis, parameters were tuned for the decoupler components, CATS compensation, and the control design for PID, LQG, and MPC. Comparative results among different control methods are evaluated based on performance criteria, including critical factors such as reduction in the time delay of bothactuators. The research findings in this paper improve the tracking control systems for the multi-axial RTHS of building structures subjected to earthquake loading. It provides insight into the robustness of the proposed tracking control methods in addressing uncertainty and improves the understanding of multiple output controllers that could be used in future cyber-physical testing of civil infrastructure subjected to natural hazards.

Integrated simulation and control environment for the development and safe start-up of cable driven parallel robots

ABSTRACT This article presents a new environment designed to facilitate the conceptualization and automation of CDPRs (Cable Driven Parallel Robots). Utilizing a platform for robotic simulation, an industrial controller, and a data gateway to communicate both systems, it is possible to emulate CDPR motion in early design, development, and start-up phases. Thus, this simulation environment allows to test how the robot will behave in advance in order to obtain a safer and more reliable first operation with the real robot. An spatially under-constrained CDPR with four cables was used to validate the capabilities of the proposed integrated environment, comparing its performance against an industry-standard hardware prototype. Both the simulation model and the real prototype performed the same trajectory in order to assess a time delay and position errors between them. Evaluation results revealed that the simulation accurately replicated the performance of its industrial counterpart, with a peak divergence of 0.27% in the position of the robot under various speed scenarios. This occurs even when accounting for latency arising from data exchange connecting the industrial control unit to the simulation. The results have shown that the environment is suitable for trajectory control of new CDPR architectures under different dynamic conditions.

A differential-based method for correcting ultra-short baseline positioning results

The primary factors influencing the positional accuracy of an ultra-short baseline (USBL) system are errors in sound speed, delay, installation deviation, and the bending of sound rays. Premised on the USBL positioning model, an error contribution model including ranging error, delay error, sound speed error and array element installation deviation was constructed. In parallel, an indirect difference correction method with additional coefficients was proposed based on the geometric correlation of the error function model. Specifically, a reference beacon was deployed on the seabed, and differential correction was achieved by directly computing target coordinates, integrating them with the positional data from the reference beacon. The proposed method demonstrated efficacy in mitigating errors associated with gradual variations or pronounced geometric correlations, including discrepancies in sound speed, bending of sound rays, and deviations in the installation of array elements. The correction method was applied to the USBL positioning, and the simulation results show that the proposed method notably enhanced both accuracy and consistency in positioning, particularly in shallow water environments characterised by significant sound speed errors. The sea trial data from the R/V Dayang Yihao in the Western Pacific demonstrate that the proposed method can effectively mitigate the errors induced by sound ray bending in deep-sea environments. The mean absolute error (MAE) and standard deviation (STD) were reduced by 51.3% and 55.3%, respectively, compared with the results of the USBL direct solution.

Railway Signal Electronic Control System Based on BP Neural Network

Railway signal system is the core system of railway command train operation. After the installation of the system equipment is completed, a comprehensive test shall be carried out through joint debugging and joint testing, and the applicability of the system to the design requirements shall be generally evaluated according to the test results. This paper focuses on the research of railway signal electronic control system. Based on BP neural network, fault information can be quickly and accurately identified in a relatively short time, and accurate electronic signal control can be realized in a complex system environment. The final result of the study shows that the difference in delay error of railway signal transmission under BP neural network technology is small, there are some subtle differences in 5 different modes, but the impact is small, in mode 1, the target time value is 0.236s, The actual reflection time is 0.322s, it can be seen that the error is controlled within 0.2s, which is feasible. Through the analysis of delay error of railway signal electronic control system, BP neural network has certain advantages in railway signal transmission.