Accurate Velocity Estimation Research Articles

Accurate FPGA-Based Velocity Measurement with an Incremental Encoder by a Fast Generalized Divisionless MT-Type Algorithm.

Velocity measurement by an incremental encoder is an important issue for advanced motion control applications such as robotics. In this paper, we deal with a kind of MT-type velocity estimation method. Though the conventional MT method is well known and has been well proven in practice, it requires execution of an arithmetic division operation that prevents an efficient implementation on low-cost FPGA-based control platforms. Thus, we propose a divisionless MT-type algorithm, which can provide a similar performance in velocity estimation accuracy as the conventional method, but requiring significantly less FPGA resources, since it implements only simple arithmetic operations such as addition, subtraction, and multiplication, that can be implemented more easily on the processing hardware. Furthermore, the algorithm is fast in execution, thus, it provides the output in only a few clock cycles. Though the proposed algorithm can be described in a recursive form, the stability of the estimation process is not jeopardized, although it is an important issue in this case. Hence, the algorithm is introduced in a form which assures stability in a wide speed range. We show the implementation of the algorithm on the experimental FPGA platform. The experimental results validated the proposed divisionless MT-type algorithm fully for accurate velocity estimation.

Performance Assessment of Multi-GNSS Precise Velocity and Acceleration Determination over Antarctica

A conventional Differential GPS (DGPS) techniques-based velocity and acceleration method (named here as ‘DVA’) may be difficult to implement in the Antarctic as there is a sparse distribution of reference stations over Antarctica. Thus, in order to overcome the baseline limitations and to obtain highly accurate and reliable velocity and acceleration estimates for airborne gravimetry, a network-based velocity and acceleration determination approach (named here as ‘NVA’), which introduces a wide network of stations and is independent of precise clock information, is applied. Here its performance for velocity and acceleration determination is fully exploited by using Global Positioning System (GPS), GLONASS, Galileo and BeiDou observations. Additionally, a standalone receiver-based method named ‘SVA’, which requires precise clock information, is also implemented for comparison. During static tests and a flight experiment over Antarctica, it was found that the NVA method yields more robust results than the SVA and DVA methods when applied to a wide area network. Moreover, the addition of GLONASS, Galileo and BeiDou systems can increase the accuracy of velocity and acceleration estimates by 39% and 43% with NVA compared to a GPS-only solution.

A novel filter for accurate estimation of fluid pressure and fluid velocity using poroelastography

Fluid pressure and fluid velocity carry important information for cancer diagnosis, prognosis and treatment. Recent work has demonstrated that estimation of these parameters is theoretically possible using ultrasound poroelastography. However, accurate estimation of these parameters requires high quality axial and lateral strain estimates from noisy ultrasound radio frequency (RF) data. In this paper, we propose a filtering technique combining two efficient filters for removal of noise from strain images, i.e., Kalman and nonlinear complex diffusion filters (NCDF). Our proposed filter is based on a novel noise model, which takes into consideration both additive and amplitude modulation noise in the estimated strains. Using finite element and ultrasound simulations, we demonstrate that the proposed filtering technique can significantly improve image quality of lateral strain elastograms along with fluid pressure and velocity elastograms. Technical feasibility of the proposed method on an in vivo set of data is also demonstrated. Our results show that the CNRe of the lateral strain, fluid pressure and fluid velocity as estimated using the proposed technique is higher by at least 10.9%, 51.3% and 334.4% when compared to the results obtained using a Kalman filter only, by at least 8.9%, 27.6% and 219.5% when compared to the results obtained using a NCDF only and by at least 152.3%, 1278% and 742% when compared to the results obtained using a median filter only for all SNRs considered in this study.

A Practical Estimation Method for Center of Mass Velocity in Swimming Direction During Front Crawl Swimming.

Center of mass (CoM) velocity variation in swimming direction is related to swimming performance and efficiency. However, it is difficult to calculate the CoM velocity during swimming. Therefore, we aimed to establish a practical estimation method for the CoM velocity in swimming direction during front crawl swimming with underwater cameras. Ten swimmers were recorded during front crawl swimming (25m, maximal effort) using a motion capture system with 18 underwater and 9 land cameras. Three CoM velocity estimation methods were constructed (single-hip velocity, both-hips velocity, and both-hips velocity with simulated arm velocity correction). Each model was validated against the actual CoM velocity. The difference between the single-hip velocity and the actual CoM velocity in swimming direction was significantly larger compared with that of the other 2 models. Furthermore, the accuracy of CoM velocity estimation was increased when both-hips velocity was corrected using the simulated arm velocity. The method allowed estimation of the CoM velocity with only 2 underwater cameras with a maximal difference of 0.06m·s-1. This study established a novel and practical method for the estimation of the CoM velocity in swimming direction during front crawl swimming.

A Spectral Approach to Peak Velocity Estimation of Pipe Flows from Noisy Image Sequences

Abstract Motivated by plane wave ultrasound image velocimetry (a.k.a. Echo PIV), we introduce a novel method to globally estimate the velocity field of a laminar and steady flow from the motion of tracer particles. Our approach exploits the fact that the equation of motion for pipe flows of constant circular cross-section is governed by a single global but unknown parameter. We connect this parameter to the Fourier spectrum of the input image sequence of the tracer particles and formulate our motion estimation problem as a spectral support estimation problem. The approach is validated on both simulated and experimental real data. It returns accurate velocity estimates after few seconds runtime and effectively copes with speckle patterns and noise.

3-D Velocity and Volume Flow Measurement In Vivo Using Speckle Decorrelation and 2-D High-Frame-Rate Contrast-Enhanced Ultrasound.

Being able to measure 3-D flow velocity and volumetric flow rate effectively in the cardiovascular system is valuable but remains a significant challenge in both clinical practice and research. Currently, there has not been an effective and practical solution to the measurement of volume flow using ultrasound imaging systems due to challenges in existing 3-D imaging techniques and high system cost. In this study, a new technique for quantifying volumetric flow rate from the cross-sectional imaging plane of the blood vessel was developed by using speckle decorrelation (SDC), 2-D high-frame-rate imaging with a standard 1-D array transducer, microbubble contrast agents, and ultrasound imaging velocimetry (UIV). Through SDC analysis of microbubble signals acquired with a very high frame rate and by using UIV to estimate the two in-plane flow velocity components, the third and out-of-plane velocity component can be obtained over time and integrated to estimate volume flow. The proposed technique was evaluated on a wall-less flow phantom in both steady and pulsatile flow. UIV in the longitudinal direction was conducted as a reference. The influences of frame rate, mechanical index (MI), orientation of imaging plane, and compounding on velocity estimation were also studied. In addition, an in vivo trial on the abdominal aorta of a rabbit was conducted. The results show that the new system can estimate volume flow with an averaged error of 3.65% ± 2.37% at a flow rate of 360 mL/min and a peak velocity of 0.45 m/s, and an error of 5.03% ± 2.73% at a flow rate of 723 mL/min and a peak velocity of 0.8 m/s. The accuracy of the flow velocity and volumetric flow rate estimation directly depend on the imaging frame rate. With a frame rate of 6000 Hz, a velocity up to 0.8 m/s can be correctly estimated. A higher mechanical index (MI = 0.42) is shown to produce greater errors (up to 21.78±0.49%, compared to 3.65±2.37% at MI = 0.19). An in vivo trial, where velocities up to 1 m/s were correctly measured, demonstrated the potential of the technique in clinical applications.

A novel fuzzy flux sliding-mode observer for the sensorless speed and position tracking of PMSMs

This paper proposes a novel fuzzy flux sliding-mode observer (FFSMO) with a phase-locked loop (PLL) for the sensorless speed and position tracking of permanent-magnet synchronous motors (PMSMs). The purpose of the novel FFSMO is to accurately estimate the position and velocity of the rotor. Compared with the conventional sliding-mode observer (SMO), the novel FFSMO can not only eliminate the low-pass filter (LPF) and phase compensation module but also improve the estimation accuracy. To adjust the SMO gain ε and to reduce the chattering of the sliding-mode variable structure, a fuzzy logic controller (FLC) is proposed and integrated into the observer. Moreover, a PLL method is employed to obtain accurate position and velocity estimates and reduce the adverse influence of noise. The stability of the proposed FFSMO is verified using Lyapunov’s second method. An experimental platform is built, and the experimental results show the effectiveness of the FFSMO.

Near-surface velocity estimation using source-domain full traveltime inversion and early arrival waveform inversion

Accurate estimation of near-surface velocity is a key step for imaging deeper targets. We have developed a new workflow to invert complex early arrivals in land seismic data for near-surface velocities. This workflow is composed of two methods: source-domain full traveltime inversion (FTI) and early arrival waveform inversion (EWI). Source-domain FTI automatically generates the background velocity that kinematically matches the reconstructed plane-wave sources from early arrivals with true plane-wave sources. This method does not require picking first arrivals for inversion, which is one of the most challenging and labor-intensive steps in ray-based first-arrival traveltime tomography, especially when the subsurface medium contains low-velocity zones that cause shingled multivalue arrivals. Moreover, unlike the conventional Born-based method, source-domain FTI can determine if the initial velocity is slower or faster than the true one according to the gradient sign. In addition, the computational cost is reduced considerably by using the one-way wave equation to extrapolate the plane-wave Green’s function. The source-domain FTI tomogram is then used as the starting model for EWI to obtain the short-wavelength component associated with the velocity model. We tested the workflow on two synthetic and one onshore filed data sets. The results demonstrate that source-domain FTI generates reasonable background velocities for EWI even though the first arrivals are shingled, and that this workflow can produce a high-resolution near-surface velocity model.

Hydromorphological Numerical Model of the Local Scour Process Around Bridge Piers

The aim of this study was to assess the simulation and prediction of scour processes, both hydrodynamically and morphologically, around vertical and inclined piers. A new version of FLOW-3D v. 11.2, including three sediment transport equations, was extensively used for estimating the scour around the pier. The results of the model in terms of water surface, flow velocity, bed shear stress and scour depth were effectively compared with several sets of the experimental and numerical data in the literature. The model provided an accurate estimation of water surface, flow velocity and bed shear stress. However, the results for the vertical velocity upstream of the pier were underestimated. The predictive capabilities of the model were mainly dependent on the pier shape and inclined direction. The downflow, stream-wise velocity, shear stress and local scour depth were significantly reduced at the inclination angle of the circular pier downstream. However, they were nearly equal to those of an inclined perpendicular circular pier. This study strongly demonstrates that a 3D hydromorphological model can be effectively used to predict the scour depth around piers.

Sparse Antenna and Pulse Placement for Colocated MIMO Radar

Multiple-input multiple-output (MIMO) radar is known for its superiority over conventional radar due to its antenna and waveform diversity. Although higher angular resolution, improved parameter identifiability, and better target detection are achieved, the hardware costs (due to multiple transmitters and multiple receivers) and high-energy consumption (multiple pulses) limit the usage of MIMO radars in large scale networks. On one hand, higher angle and velocity estimation accuracy is required, but on the other hand, a lower number of antennas/pulses is desirable. To achieve such a compromise, in this paper, the Cramér-Rao lower bound (CRLB) for the angle and velocity estimator is employed as a performance metric to design the antenna and the pulse placement. It is shown that the CRLB derived for two targets is a more appropriate criterion in comparison with the single-target CRLB since the two-target CRLB takes into account both the mainlobe width and the sidelobe level of the ambiguity function. In this paper, several algorithms for antenna and pulse selection based on convex and submodular optimization are proposed. Numerical experiments are provided to illustrate the developed theory.

Particle swarm optimization for motion compensation in Costas-coded frequency-hopped radar

Signals from Costas-coded frequency-hopped radars exhibit an approximate “thumbtack” ambiguity function and prevent range-Doppler coupling. Therefore, these radars provide high-resolution range and velocity performance. However, the radar signals are highly sensitive to Doppler frequency shifts, and peak divergence arises due to Doppler mismatches when the target is moving. To solve these problems, we thoroughly analyze the effect of velocity on range profiles. Then, we propose a method of motion compensation based on particle swarm optimization using improved waveform entropy as the objective function. The target velocity is accurately determined through an iterative search. After motion compensation, the focus of the target range profile is notably improved. Simulation results confirm that the proposed method has a low computational complexity and retrieves accurate velocity estimates even under low signal-to-noise ratio and high target speeds, suggesting its adaptability and robustness for real-world applications.

Cosmology with the pairwise kinematic SZ effect: calibration and validation using hydrodynamical simulations

We study the potential of the kinematic SZ effect as a probe for cosmology, focusing on the pairwise method. The main challenge is disentangling the cosmologically interesting mean pairwise velocity from the cluster optical depth and the associated uncertainties on the baryonic physics in clusters. Furthermore, the pairwise kSZ signal might be affected by internal cluster motions or correlations between velocity and optical depth. We investigate these effects using the Magneticum cosmological hydrodynamical simulations, one of the largest simulations of this kind performed to date. We produce tSZ and kSZ maps with an area of $\simeq 1600~\mathrm{deg}^2$, and the corresponding cluster catalogues with $M_{500c} \gtrsim 3 \times 10^{13}~h^{-1}M_\odot$ and $z \lesssim 2$. From these data sets we calibrate a scaling relation between the average Compton-$y$ parameter and optical depth. We show that this relation can be used to recover an accurate estimate of the mean pairwise velocity from the kSZ effect, and that this effect can be used as an important probe of cosmology. We discuss the impact of theoretical and observational systematic effects, and find that further work on feedback models is required to interpret future high-precision measurements of the kSZ effect.

Emitter Velocity Estimation Comparison for Frequency Difference of Arrival Measurement Based Single and Multiple Reference Lateration Algorithm

The accuracy at which the instantaneous velocity and position of a non-stationary emitting source estimated using a lateration algorithm depends on several factors such as the lateration algorithm approach, the number and choice of reference receiving station (RS) used in developing the lateration algorithm. In this paper, the use of multiple reference RSs was proposed to improve the velocity estimation accuracy of the frequency difference of arrival (FDOA) based lateration algorithm. The velocity estimation performance of the proposed multiple reference FDOA based lateration algorithm is compared with the conventional approach of using single reference RS at some selected emitter positions using Monte Carlo simulation. Simulation result based on an equilateral triangle RS configuration shows that the use of multiple reference RSs improved the velocity estimation accuracy of the lateration algorithm. Based on the selected emitter positions, a reduction in velocity estimation error of about 0.033 and 1.31 for emitter positions at ranges 0.5 km and 5 km respectively was achieved using the multiple reference lateration algorithm.

Velocity Estimation for Ultralightweight Tendon-Driven Series Elastic Robots

Accurate velocity estimation is an important basis for robot control, but especially challenging for highly elastically driven robots. These robots show large swing or oscillation effects if they are not damped appropriately during the performed motion. In this letter, we consider an ultralightweight tendon-driven series elastic robot arm equipped with low-resolution joint position encoders. We propose an adaptive Kalman filter for velocity estimation that is suitable for these kinds of robots with a large range of possible velocities and oscillation frequencies. Based on an analysis of the parameter characteristics of the measurement noise variance, an update rule based on the filter position error is developed that is easy to adjust for use with different sensors. Evaluation of the filter both in simulation and in robot experiments shows a smooth and accurate performance, well suited for control purposes.

Three-Dimensional Tracking of an Aircraft Using Two-Dimensional Radars

Accurate three-dimensional (3-D) position and velocity estimates of an aircraft are important for air traffic control (ATC) systems. An ATC 2-D radar measures the slant range and azimuth of an aircraft. Thus, a single measurement from a 2-D radar is not sufficient to calculate the 3-D position of an aircraft. Previous researchers have used the multiple-model-based height-parametrized (HP) extended Kalman filter with Cartesian state vector (HP-CEKF) with one or two 2-D radars for an aircraft with nearly constant velocity and altitude. However, the filter initialization algorithms contain errors. In this paper, in addition to the HP-CEKF, we present the HP Cartesian unscented Kalman filter (HP-CUKF) and HP Cartesian cubature Kalman filter (HP-CCKF). We also present two new nonlinear filters for the two-radar problem. The first filter uses modified spherical coordinates based HP-UKF (HP-MSCUKF) where the range and azimuth are components of the target state. The second filter uses a cubature Kalman filter with filter initialization by the bias-compensated pseudolinear estimator. We also consider the climbing motion of an aircraft with nearly constant climbing rate, which has not been studied before. All four aforementioned HP filters use the single-point track initiation algorithm. The state estimation accuracy of an aircraft is analyzed as a function of the distance of the aircraft from the radar(s). We compare the performance of the nonlinear filters with the posterior Cramer-Rao lower bound. The normalized computational times of all algorithms in all scenarios are presented. Our results show that accurate 3-D trajectory estimates of an aircraft can be obtained using one or two ATC 2-D radars.

Localization of Indoor Mobile Robot Using Minimum Variance Unbiased FIR Filter

The demand of indoor localization has recently grown quickly in industries. In general, a localization system is required to be reliable, fast, and have high accuracy. In this paper, the ultrawideband (UWB) technique is combined with the inertial navigation sensor (INS) to form a coupled UWB/INS localization framework, which inherits the advantages from both components. A minimum variance unbiased finite impulse response (MVU FIR) method is then applied to obtain accurate position and velocity estimations from noisy measurements. Two experiments and several simulations are conducted. Compared with the traditional Kalman filter (KF) and particle filter, the MVU FIR filter exhibits better immunity to the errors about a priori knowledge of noise variances. It can handle the kidnapped problem, and recover from some extreme failures satisfactorily. Moreover, the MVU FIR filtering algorithm is fast and easily implementable. Its online computational time is even lower than that of the KF, which is favorable in localization applications. Note to Practitioners —For indoor robot localization, an effective filtering algorithm can improve the accuracy significantly. Existing and commonly used filtering approaches suffer from weak robustness to the imprecise a priori knowledge of noise variances used, unsatisfied performance when dealing with sudden behaviors of robot, and large online computational load. This paper suggests a new practical method to estimate the current state using finite past measurements with a finite impulse response filter gain computed off-line. By testing it within the coupled ultrawideband/inertial navigation sensor localization framework under different operating conditions, we demonstrate that the proposed method can effectively overcome the above problems, providing fast, accurate, and reliable estimation in a practical environment.

Evaluation of Velocity Estimation Methods Based on Their Effect on Haptic Device Performance

This paper comparatively evaluates the effect of real-time velocity estimation methods on the passivity and fidelity of virtual walls implemented using haptic interfaces. Impedance width or $Z$ -width is a fundamental measure of performance in haptic devices. Limited accuracy of velocity estimates from position encoder data is an impediment in improving the $Z$ -width in haptic interfaces. We study the efficacy of Levant's differentiator as a velocity estimator to allow passive implementation of higher stiffness virtual walls as compared to some of the commonly used velocity estimators in the field of haptics. We first experimentally demonstrate feasibility of Levant's differentiator as a velocity estimator for haptics applications by comparing $Z$ -width performance achieved with Levant's differentiator and commonly used finite difference method (FDM) cascaded with a low-pass filter. A novel $Z$ -width plotting technique combining the passivity and fidelity of haptic rendering is proposed, and used to compare the haptic device performance obtained with Levant's differentiator, FDM+low-pass filter, first-order adaptive windowing (FOAW), and Kalman-filter-based velocity estimation methods. Simulations and experiments conducted on a custom single degree-of-freedom haptic device demonstrate that the stiffest virtual walls are rendered with velocity estimated using Levant's differentiator, and the highest wall rendering fidelity is achieved by FOAW-based velocity estimation scheme.

Correction of multi-frequency GPR wave velocity with distorted hyperbolic reflections from GPR surveys of underground utilities

Estimation of Ground Penetrating Radar (GPR) wave velocity and the real part of dielectric permittivity (ε′) play an important role when assessing the condition of buried objects because ε′ is highly affected by moisture and void content in materials. However, errors in velocity occur due to the effect of oblique angles between the alignment of pipelines and GPR traverses during common offset survey. In this paper, field experiments on paving blocks and reinforced concrete were conducted in order to investigate errors caused by the effects of oblique angles on GPR wave velocity. GPR traverses were designed to travel along several oblique angles (θ = 30°, 45°, 60°¸75°, 90°, 105°, 120°, 135° and 150°) relative to the alignment of a ductile iron (DI) pipe. Antennas with various nominal centre frequencies (IDS 200/600, GSSI 400/900 and Sensor & Software 250 MHz) were applied in order to compare the effects. It was found that wider and flatter hyperbolic reflections are obtained and the estimated GPR wave velocity is higher if the included angle between the alignment of the DI pipe and GPR traverse changes from being perpendicular to oblique. The relative error of velocities estimated at oblique angles when compared to that estimated in perpendicular cases can be as much as 44%. Specific steps were taken to correct the errors. It is believed that this study suggests a method whereby the measurement accuracy of velocity estimation for GPR condition surveys of underground utilities can be increased.

Processing methods for photoacoustic Doppler flowmetry with a clinical ultrasound scanner.

Photoacoustic flowmetry (PAF) based on time-domain cross correlation of photoacoustic signals is a promising technique for deep tissue measurement of blood flow velocity. Signal processing has previously been developed for single element transducers. Here, the processing methods for acoustic resolution PAF using a clinical ultrasound transducer array are developed and validated using a 64-element transducer array with a -6 dB detection band of 11 to 17MHz. Measurements were performed on a flow phantom consisting of a tube (580 μm inner diameter) perfused with human blood flowing at physiological speeds ranging from 3 to 25 mm / s. The processing pipeline comprised: image reconstruction, filtering, displacement detection, and masking. High-pass filtering and background subtraction were found to be key preprocessing steps to enable accurate flow velocity estimates, which were calculated using a cross-correlation based method. In addition, the regions of interest in the calculated velocity maps were defined using a masking approach based on the amplitude of the cross-correlation functions. These developments enabled blood flow measurements using a transducer array, bringing PAF one step closer to clinical applicability.

Characterization of a signal recording system for accurate velocity estimation using a VISAR

The linearity of a signal recording system (SRS) in time as well as in amplitude are important for the accurate estimation of the free surface velocity history of a moving target during shock loading and unloading when measured using optical interferometers such as a velocity interferometer system for any reflector (VISAR). Signal recording being the first step in a long sequence of signal processes, the incorporation of errors due to nonlinearity, and low signal-to-noise ratio (SNR) affects the overall accuracy and precision of the estimation of velocity history. In shock experiments the small duration (a few µs) of loading/unloading, the reflectivity of moving target surface, and the properties of optical components, control the amount of input of light to the SRS of a VISAR and this in turn affects the linearity and SNR of the overall measurement. These factors make it essential to develop in situ procedures for (i) minimizing the effect of signal induced noise and (ii) determine the linear region of operation for the SRS. Here we report on a procedure for the optimization of SRS parameters such as photodetector gain, optical power, aperture etc, so as to achieve a linear region of operation with a high SNR. The linear region of operation so determined has been utilized successfully to estimate the temporal history of the free surface velocity of the moving target in shock experiments.