Velocity Error Research Articles

Probing the inner Galactic halo with blue horizontal-branch stars

Context. Stars that are found on the blue horizontal-branch (BHB) evolved from low-mass stars that have completed their core hydrogen-burning main sequence (MS) stage and undergone the helium flash at the end of their red giant phase. Hence, they are very old objects that can be used as markers in studying galactic structure and formation history. The fact that their luminosity is virtually constant at all effective temperatures also makes them good standard candles. Aims. We have compiled a catalogue of BHB stars with stellar parameters calculated from spectral energy distributions (SEDs) constructed using data from multiple large-scale photometric surveys. In addition, we update our previous Gaia Early Data Release 3 (EDR3) catalogue of BHB stars with parallax errors less than 20% by using the SED results to define the selection criteria. The purpose of these catalogues is to create a set of BHB star candidates with reliable stellar parameters. In addition, they provide a more complete full-sky catalogue with candidate objects found along the whole BHB from where RR-Lyrae are found on the instability strip to the extreme horizontal-branch (EHB). Methods. We selected a large dataset of Gaia Data Release 3 (DR3) objects based only on their position on the colour-magnitude diagram (CMD), along with the tangential velocity and parallax errors. The SEDs were then used to evaluate contamination levels in the dataset and derive optimised data quality acceptance constraints. This allowed us to extend the Gaia DR3 colour and absolute magnitude criteria further towards the EHB. The level of contamination found using SED analysis was confirmed by acquiring spectra using the Ondrejov Echelle spectrograph, attached to the Perek 2m telescope at the Astronomical Institute of the Czech Academy of Sciences. Results. We present a catalogue of 9172 Galactic halo BHB candidate stars with atmospheric and stellar parameters calculated from synthetic SEDs. We also present an extended Gaia DR3-based catalogue of 22 335 BHB candidate stars with a wider range of effective temperatures and Gaia DR3 parallax errors of less than 20%. This represents an increase of 33% compared to the our 2021 catalogue, with a contamination level of 10%.

Kinematic analysis of inverted planetary roller screw considering skew error

To reveal the motion characteristics of inverted planetary roller screws under the influence of axial deviation error, the working principle of inverted planetary roller screws was elaborated, and a motion analysis model of inverted planetary roller screws based on deviation error was established. This paper analyzed the angle error, axial displacement error, and relative velocity error of the roller, and comprehensively analyzed the influence of errors and parameters on the motion state.

Research on deflection correction performance of movable crossbeam during pressurization of ultra-large hydraulic press

In this paper, the deflection of the movable crossbeam during the pressurization process of the ultra-large hydraulic press is studied. The electromechanical and hydraulic systems of the ultra-large hydraulic press are analyzed, and a joint AMESim-ADAMS simulation model of the mechanical system, the oil system, and the correction control system are established. The simulation analyzes the deflection control of the working cylinder in the 1600 MN pressurized state, the movable crossbeam in the positive load without deflection correction, positive load with deflection correction, eccentric load with 300 mm of deflection in X-positive direction, and eccentric load with 300 mm of deflection in XZ-positive direction. The results show that the correction control system needs to be turned on synchronously at the beginning of the pressurization; under the pressure of 1600 MN and the maximum eccentricity of 300 mm, the velocity error of the movable crossbeam can be controlled within 7 %, and the parallel control precision can reach 0.14 mm/m.

A Robust Vector-Tracking Loop Based on KF and RTS Smoothing for Shipborne Navigation

High-precision navigation systems are crucial for unmanned autonomous vessels. However, commonly used Global Navigation Satellite System (GNSS) signals are often severely affected by environmental obstruction, leading to reduced positioning accuracy or even the inability to locate. To address the issues caused by signal obstruction in high-precision navigation systems, the research presented in this paper proposes a vector-tracking loop (VTL) structure based on the forward Kalman Filter (KF) and the backward Rauch Tung Striebel (RTS) smoothing algorithm. The introduction of loop filters in the signal-tracking loop improves the tracking accuracy of the carrier and code, thereby enhancing the stability and robustness of the navigation system. The traditional scalar-tracking loop (STL), traditional VTL, and Kalman Filter (KF)-based VTL were compared through shipborne motion experiments, and the proposed method demonstrated superior signal-tracking capability and navigation accuracy. In the experiment, there were three blocking areas along the experimental path. The experimental results show that, when there are signal blockages of 12 s, 18 s, and 40 s, compared to the traditional VTL method, the proposed method can reduce the horizontal position error by 93.9%, 95.8%, and 94.5%, respectively, as well as the horizontal velocity error by 71.1%, 95.8%, and 97.6%, respectively.

Continuous Shear Wave Elastography for Liver Using Frame-to-Frame Equalization of Complex Amplitude.

This study addresses a crucial necessity in the field of noninvasive liver fibrosis diagnosis by introducing the concept of continuous shear wave elastography (C-SWE), utilizing an external vibration source and color Doppler imaging. However, an application of C-SWE to assess liver elasticity, a deep region within the human body, arises an issue of signal instability in the obtained data. To tackle this challenge, this work proposes a method involving the acquisition of multiple frames of datasets, which are subsequently compressed. Furthermore, the proposed frame-to-frame equalization method compensates discrepancies in the initial phase that might exist among multiple-frame datasets, thereby significantly enhancing signal stability. The experimental validation of this approach encompasses both phantom tests and in vivo experiments. In the phantom tests, the proposed technique is validated through a comparison with the established shear wave elastography (SWE) technique. The results demonstrate a remarkable agreement, with an error in shear wave velocity of less than 4.2%. Additionally, the efficacy of the proposed method is confirmed through in vivo tests. As a result, the stabilization of observed shear waves using the frame-to-frame equalization technique exhibits promising potential for accurately assessing human liver elasticity. These findings collectively underscore the viability of C-SWE as a potential diagnostic instrument for liver fibrosis.

Indirect tuning of a complementary orientation filter using velocity data and a genetic algorithm

In this paper, the accuracy of inertial sensor orientation relative to the level frame is improved through optimal tuning of a complementary filter by a genetic algorithm. While constant filter gains have been used elsewhere, these may introduce errors under dynamic motions when gyroscopes should be trusted more than accelerometers. Optimal gains are prescribed by a Mamdani fuzzy rule base whose membership functions are found using a genetic algorithm and experimental data. Furthermore, model fitness is not based directly on orientation but the error between estimated and ground truth velocities. This paper has three interrelated novel elements. The main novelty is the indirect tuning method, which is simple, low-cost and requires a single camera and inertial sensor. The method is shown to increase tracking accuracy compared with popular baseline filters. Secondary novel elements are the bespoke genetic algorithm and the time agnostic velocity error metric. The contributions from this work can help improve the localization accuracy of assets and human personnel. This research has a direct impact in command and control by improving situational awareness and the ability to direct assets to safe locations using safer routes. This results in increasing safety in applications such as firefighting and battlespace.

Data-Driven Identification of Crane Dynamics Using Regularized Genetic Programming

The meaningful problem of improving crane safety, reliability, and efficiency is extensively studied in the literature and targeted via various model-based control approaches. In recent years, crane data-driven modeling has attracted much attention compared to physics-based models, particularly due to its potential in real-time crane control applications, specifically in model predictive control. This paper proposes grammar-guided genetic programming with sparse regression (G3P-SR) to identify the nonlinear dynamics of an underactuated crane system. G3P-SR uses grammars to bias the search space and produces a fixed number of candidate model terms, while a local search method based on an l0-regularized regression results in a sparse solution, thereby also reducing model complexity as well as reducing the probability of overfitting. Identification is performed on experimental data obtained from a laboratory-scale overhead crane. The proposed method is compared with multi-gene genetic programming (MGGP), NARX neural network, and Takagi-Sugeno fuzzy (TSF) ARX models in terms of model complexity, prediction accuracy, and sensitivity. The G3P-SR algorithm evolved a model with a maximum mean square error (MSE) of crane velocity and sway prediction of 1.1860 × 10−4 and 4.8531 × 10−4, respectively, in simulations for different testing data sets, showing better accuracy than the TSF ARX and MGGP models. Only the NARX neural network model with velocity and sway maximum MSEs of 1.4595 × 10−4 and 4.8571 × 10−4 achieves a similar accuracy or an even better one in some testing scenarios, but at the cost of increasing the total number of parameters to be estimated by over 300% and the number of output lags compared to the G3P-SR model. Moreover, the G3P-SR model is proven to be notably less sensitive, exhibiting the least deviation from the nominal trajectory for deviations in the payload mass by approximately a factor of 10.

Adaptive UAV Navigation Method Based on AHRS.

To address the inaccuracy of the Constant Acceleration/Constant Velocity (CA/CV) model as the state equation in describing the relative motion state in UAV relative navigation, an adaptive UAV relative navigation method is proposed, which is based on the UAV attitude information provided by Attitude and Heading Reference System (AHRS). The proposed method utilizes the AHRS output attitude parameters as the benchmark for dead reckoning and derives a relative navigation state equation with attitude error as process noise. By integrating the extended Kalman filter output for relative state estimation and employing an adaptive decision rule designed using the innovation of the filter update phase, the proposed method recalculates motion states deviating from the actual motion using the Tasmanian Devil Optimization (TDO) algorithm. The simulation results show that, compared with the CA/CV model, the proposed method reduces the relative position errors by 12%, 23%, and 32% in the X, Y, and Z directions, respectively, and that it reduces the relative velocity errors by 350%, 330%, and 300%, respectively. There is a significant improvement in the relative navigation accuracy.

Trajectory tracking of binocular vision system for picking robot based on fast non-singular terminal sliding mode control

This paper proposes a non-singular fast terminal sliding mode control method for a binocular active vision platform of a picking robot with unknown dynamics. The method uses radial basis function (RBF) neural networks to achieve trajectory tracking accuracy and enhance robustness against external interference. A non-singular fast terminal sliding mode controller is designed for the system’s convergence within a limited time. An adaptive neural network approximates the unknown nonlinear function of the dynamic model. Stability and finite-time convergence of the closed-loop system are established using Lyapunov theory. Experimental verification on the binocular vision platform demonstrates position and speed errors converging to the desired trajectory within 2 and 1 second, respectively. Moreover, when subjected to external interference, the position and velocity errors converge within 0.1 seconds. Simulation experiments confirm the method’s effectiveness in improving convergence speed, trajectory tracking accuracy, and robustness against external interference, while reducing system chattering.

Microwave Photonics Broadband Doppler Velocity Simulator with High Spurious Suppression Ratio by Using Serrodyne Modulation

A Doppler velocity simulation method based on serrodyne modulation is proposed to achieve the frequency shift from hundred hertz to megahertz. One sub-phase modulation (PM) in a dual-parallel dual-drive Mach–Zehnder modulator loads a sawtooth signal to achieve a small frequency shift of the optical carrier. The other three sub-PMs implement carrier-suppressed double-band modulation of the RF signal. The RF signal is directly coupled from the receiving antenna to the modulator’s RF port without any electrical devices like a 90° hybrid, which ensures a broad operational bandwidth of the system. After filtering out one of the RF modulation sidebands by an optical filter, Doppler frequency shifting (DFS) is realized through frequency beating. The half-wave voltage of modulators rapidly decreases at low frequency shifts, leading to an increase in spurious signals. In order to improve the spurious suppression ratio (SSR) of DFS, a digital pre-distortion compensation based on the measured half-wave voltage is implemented in the frequency domain. Experimental results show that SSRs are larger than 35 dB when frequency shifts range from 0.1 kHz to 1 MHz. The RF operation bandwidth covers 2–40 GHz. The effectiveness of a Doppler velocity simulator is evaluated, and the simulation velocity error is less than 0.06 km/h. The proposed method has potential applications in both broadband electronic warfare and traffic metering applications.

The Analytical Validity of Stride Detection and Gait Parameters Reconstruction Using the Ankle-Mounted Inertial Measurement Unit Syde®.

The increasing use of inertial measurement units (IMU) in biomedical sciences brings new possibilities for clinical research. The aim of this paper is to demonstrate the accuracy of the IMU-based wearable Syde® device, which allows day-long and remote continuous gait recording in comparison to a reference motion capture system. Twelve healthy subjects (age: 23.17 ± 2.04, height: 174.17 ± 6.46 cm) participated in a controlled environment data collection and performed a series of gait tasks with both systems attached to each ankle. A total of 2820 strides were analyzed. The results show a median absolute stride length error of 1.86 cm between the IMU-based wearable device reconstruction and the motion capture ground truth, with the 75th percentile at 3.24 cm. The median absolute stride horizontal velocity error was 1.56 cm/s, with the 75th percentile at 2.63 cm/s. With a measurement error to the reference system of less than 3 cm, we conclude that there is a valid physical recovery of stride length and horizontal velocity from data collected with the IMU-based wearable Syde® device.

Optimization of Space-Time image velocimetry based on deep residual learning

Space-Time Image Velocimetry (STIV) is considered to be a highly promising method for river flow measurement due to its safe and efficient features. However, the traditional STIV method is challenged to obtain stable and accurate results when disturbed by external environments such as obstacles, waves and noise. As a consequence, a residual network-based STIV method is constructed by combining STIV with deep learning. In the synthetic dataset validation, benefited from the unique residual module and the relation-aware global attention mechanism, the recognition accuracy of STI texture angle is as high as 99.9 %, which is much higher than that of the Efficient Net b3, ViT16 and VGG19 networks. In the real dataset, the proposed method shows stronger stability and lower error by compared with gradient tensor (GT) and fast Fourier transform (FFT) methods, whose overall recognition accuracy is above 90 % under all types of STI cases, angle error is within 2°, and flow velocity error is around 0.10 m/s. Furthermore, the model was validated by a one-year comparative measurement at the Qilijie hydrological station in 2022, and the results were compared with LSPIV, GT, and FFT methods. The R2 of the model to the measured values is 0.98, the RMSE is 0.17, and the MAE is 0.12 m/s, indicating that the method has sufficient accuracy and robustness for long-term stable and real-time monitoring of river flow.

Statement of Removal

A randomly fluctuated vortex-induced vibration (VIV) affects the localization of moving targets in an underwater acoustic wireless sensor network (UAWSN) to cause an offset time and time synchronization error which disturbs the localization of the non-cooperative moving target. Definition 2.1, theorem 2.2 has been introduced in the present work to describe the genesis and consequences of the VIV effect in UAWSN. An elliptic localization introduces the direct and indirect path measurements of the moving target. The standard CRLB parameter quantifies the VIV effect. The compensation of vortex-induced vibrations (CVV) algorithm is proposed to quantify the degradation of localization performance and to estimate the position of the moving target. The theoretical measurements of position error, velocity error with respect to the variation of noise, number of receiver sensors, and probability of line of sight (LOS) errors are compared to the standard methods. The proposed CVV algorithm improves the localization performance by 32.24% and reduces 34.36% of position errors, and 37.46% of velocity errors up to 600 meters. It can be useful for the sub-aquatic internet of underwater things.

A modified CFD-DEM method for accurate prediction of the minimum fluidization velocity

Monodisperse fluidized bed experiments have been carried out on 13 kinds of particles with different particle sizes in a cylindrical fluidized bed. The accuracy of nine commonly used monodisperse drag models, including the Gidsapow, BVK, and Zhou–Fan models is verified. It is found that the Zhou–Fan model is the most accurate at low and moderate values of the particle Reynolds number. It is found that with the traditional computational fluid dynamics–discrete element method (CFD-DEM) method it is difficult to obtain an accurate minimum fluidization velocity owing to difficulty in obtaining an accurate value of the minimum fluidization solid volume fraction. A modified method is proposed to increase the accuracy of prediction of the minimum fluidized solid volume fraction by using a virtual particle size in the calculation of the particle collision process. The effectiveness of the modified method is verified by comparing the CFD-DEM simulation results with experimental results for Geldart-D particles. The relative error of the minimum fluidization velocity is found to be reduced from 24.6% to 2%.

Transfer alignment method based on installation deviation angle estimation for array POS

Transfer alignment of array Position and Orientation System (POS) is the key technology to provide motion information for airborne earth observation high-precision imaging. Because the large deviation angle between main Inertial Measurement Unit (IMU) and slave IMU is difficult to accurately measure by existing methods, the transfer alignment accuracy will be seriously affected. Aiming at this issue, a transfer alignment method based on installation deviation angle estimation for array POS is proposed. This method includes two steps: pre-estimation and improved transfer alignment. First, two deviation angles are calculated by angular velocity and acceleration using quaternion optimization method respectively. The higher-precision deviation angle is fused by two deviation angles using their respective weights, which are calculated by Signal to Noise Ratios (SNRs). Second, the result of pre-estimation is used in transfer alignment. Residual errors of deviation angle are considered as state variables and be compensated online. Compared with the existing methods, the velocity, position and attitude errors calculated by this method are reduced by 15.4%, 31.7% and 66.5% respectively. The proposed method significantly reduces the adverse effect of installation deviation angle on measurement accuracy of array POS.

Model-Scale Evaluation of Autonomous Ship Landing Guidance and Control Modes

This paper presents the results of an extensive model-scale experimental evaluation of autonomous ship landing guidance and control modes, with flight tests performed in the Maneuvering and Seakeeping (MASK) Basin at the U.S. Naval Surface Warfare Center Carderock Division. The experiments were performed using a commodities-based multirotor unmanned aerial vehicle (UAV) operating from a 20-ft-long model scale ship subject to scaled wave conditions. During testing, two separate guidance algorithms were evaluated: a quadratic programming (QP) based landing algorithm that plans the trajectory to a forecasted deck state and a simpler “baseline??? method that tracks deck motions while closing the distance between the aircraft and deck at a constant rate. Both algorithms commanded a Froude-scaled explicit model following control law, and the control law parameters were modified to progressively degrade aircraft tracking bandwidths. The results showed that the predictive capabilities of the QP algorithm allowed more direct landing paths to be planned when compared to the baseline algorithm and also allowed the QP algorithm to land with lower tracking bandwidths. But while the QP algorithm performed well in the majority of cases, there were several landings where a combination of poor deck state predictions and how the QP algorithm utilizes predictions to choose a land time resulted in significant terminal velocity and attitude errors. The baseline guidance algorithm, on the other hand, proved to be both simple and reliable when the UAV was in high bandwidth configurations but required a high reference tracking bandwidth.

A dual-stage correction approach for high-precision phase-shifter in Fizeau interferometers

This paper proposes a dual-stage correction approach for a high-accuracy phase-shifter in Fizeau laser interferometers, effectively reducing the phase shift errors in PSI (Phase-Shifting interferometry) and improving the precision of surface profile measurements. The precision of PSI depends on the displacement accuracy of the reference mirror, and the function of the phase shifter is to drive the reference mirror to generate wavelength-level displacements with nanometer-level accuracy. The first-stage correction aims to reduce the nonlinearity error of the reference mirror by ULPS (Ultra-High Linearity Phase Shifter). The second-stage correction aims to reduce the average velocity error and plane velocity uniformity error of the reference mirror by AVIC (Auto Velocity Iterative Correction). The experimental results indicate that, after the first-stage correction, ULPS exhibits a 0.05 % nonlinearity, a 2.5 nm repeatability, and a 0.2 nm resolution under a load of 20 kg, and its nonlinearity surpassing all phase-shifters documented in the literature. After the second-stage correction, the average velocity error and plane velocity uniformity error of the reference mirror are reduced to 0.07 %.

Research on high sensitivity optical fiber sensing method for simultaneous measurement of seawater velocity and temperature

Aiming at the need of high sensitivity flow velocity and temperature sensor in ocean research, an optical fiber sensor for the simultaneous measurement of seawater velocity and temperature was proposed by coupling a reflective Panda fiber polarization interferometer with a hollow cylindrical cantilever, which combining the stress sensitivity of Panda fiber and optical vernier effect to achieve simultaneous measurement and sensitization of flow velocity and temperature. Firstly, the theoretical formulas of velocity sensitivity and temperature sensitivity were obtained by theoretical derivation and finite element simulation. Secondly, a velocity and temperature measurement system was established experimentally, and the maximum velocity sensitivity was –233.86 nm/(m/s) at 0.42 m/s with the mean relative error compared with the theoretical sensitivity was 3.8 %, the maximum temperature sensitivity was −14.5 nm/(°C) with the mean relative error compared with the theoretical sensitivity was 8 %. Finally, nine different sets of seawater velocity and temperature were measured using the sensitivity matrix and compared with the Acoustic Doppler Velocimetry and Conductivity-Temperature-Depth meter, the mean relative error of velocity and temperature measurement results were 2.8 % and 2 %, respectively. The optical fiber sensor based on the cantilever is expected to play an important role in the field of ocean flow field measurement because of high sensitivity and the ability to measure velocity and temperature simultaneously.

A new strategy for prestack time migration velocity analysis to assess and mitigate structural uncertainty

Velocity uncertainty represents a significant contributor to structural uncertainty in seismic imaging. Therefore, improving velocities and enhancing the resolution of velocity spectra are crucial for reducing structural uncertainty. In the present study, a novel approach is introduced to increase velocity resolution and mitigate structural uncertainty. The methodology's impact on spatial and temporal uncertainty of image points is compared with the improved velocity continuation method. The proposed strategy involves modifying the equations of the weighted semblance method and integrating them into the equations of the velocity continuation method. Specifically, the vertical analysis window of the weighted semblance, typically applied on coherency panels is changed to a horizontal window that is applied on common-image gathers. Correspondingly, the weighting factor is adjusted using a time-adaptive function. The velocity uncertainty equation in the velocity continuation method is then replaced by the new weighted semblance eq. A similar substitution can be performed for structural uncertainty equations. These new equations are then used on common-image gathers obtained by the velocity continuation method to increase the accuracy of the velocity model and then investigate changes in structural uncertainty. In the proposed strategy, prestack time migration is initially conducted on seismic common-offset sections using various constant velocities within a predefined range. Subsequently, the weighted semblance technique is used for automatic velocity model updating in all common-image gathers. The new velocity model is then used for final prestack time migration. In the equations pertaining to velocity uncertainty, a width equivalent to one standard deviation on both sides of the picked velocity value is considered as the uncertainty range. By narrowing this width through the proposed method, it is expected to mitigate subsequent structural uncertainty, specifically for 1D media. Results from applying the presented method on synthetic and marine seismic data demonstrate its effectiveness in reducing structural uncertainty for 1D time migrated images compared to the velocity continuation method. It is also shown that horizontal structural uncertainty is significantly more sensitive to velocity errors rather than vertical uncertainty. An added benefit is that the increased resolution in velocity spectra also provides appropriate panels for automatic velocity picking.

Experimental and numerical study of the gated and ungated ogee spillway

This study was carried out by combining numerical modeling and experimental measurements to investigate the hydraulic characteristics of ungated and gated ogee spillways with high head ratios. The primary objective was to validate the use of a numerical model as a complementary approach to the experimental model for simulating the hydraulic behavior of these spillways, providing a more comprehensive understanding of their hydraulic properties under varying conditions of head ratios and relative gate openings. An Acoustic Doppler Velocimeter (ADV) was used to measure the vertical flow velocity distributions, and ultrasonic sensor wave gauges were used to obtain the time history of the water level. The results of the measurements were compared with the simulation results using a model fitted with three different turbulence models (realizable k-ε, RNG k-ε, k-ω SST). The numerical model was developed using OpenFOAM. With respect to the ungated spillway, three different head ratios ranging from 1.4 to 4.6, which correspond to high head ratios, were investigated. Similarly, three different relative gate openings ranging from 0.5 to 2 were investigated for the gated spillway. The results of water surface profiles and velocity profiles suggest that the numerical and experimental models achieve a good agreement for sections located further away from the spillway. For the ungated spillway, the simulation results for the near-spillway sections are enhanced when the head ratio increases. Considering the velocity profiles and error analysis, the realizable k–ε model was found to best predict the results of the experimental model. A discussion about the discharge equation, velocity fields, pressure fields, and the corner separation zone is also included in this study.