Accurate Velocity Measurements Research Articles

Improving the accuracy and robustness of carotid-femoral pulse wave velocity measurement using a simplified tube-load model

Arterial stiffness, as measured by pulse wave velocity, for the early non-invasive screening of cardiovascular disease is becoming ever more widely used and is an independent prognostic indicator for a variety of pathologies including arteriosclerosis. Carotid-femoral pulse wave velocity (cfPWV) is regarded as the gold standard for aortic stiffness. Existing algorithms for cfPWV estimation have been shown to have good repeatability and accuracy, however, further assessment is needed, especially when signal quality is compromised. We propose a method for calculating cfPWV based on a simplified tube-load model, which allows for the propagation and reflection of the pulse wave. In-vivo cfPWV measurements from 57 subjects and numerical cfPWV data based on a one-dimensional model were used to assess the method and its performance was compared to three other existing approaches (waveform matching, intersecting tangent, and cross-correlation). The cfPWV calculated using the simplified tube-load model had better repeatability than the other methods (Intra-group Correlation Coefficient, ICC = 0.985). The model was also more accurate than other methods (deviation, 0.13 ms−1) and was more robust when dealing with noisy signals. We conclude that the determination of cfPWV based on the proposed model can accurately and robustly evaluate arterial stiffness.

Hemodynamics in a three-dimensional printed aortic model: a comparison of four-dimensional phase-contrast magnetic resonance and image-based computational fluid dynamics.

This study aims to compare an electrocardiogram (ECG)-gated four-dimensional (4D) phase-contrast (PC) magnetic resonance imaging (MRI) technique and computational fluid dynamics (CFD) using variables controlled in a laboratory environment to minimize bias factors. Data from 4D PC-MRI were compared with computational fluid dynamics using steady and pulsatile flows at various inlet velocities. Anatomically realistic models for a normal aorta, a penetrating atherosclerotic ulcer, and an abdominal aortic aneurysm were constructed using a three-dimensional printer. For the normal aorta model, the errors in the peak and the average velocities were within 5%. The peak velocities of the penetrating atherosclerotic ulcer and the abdominal aortic aneurysm models displayed a more extensive range of differences because of the high-speed and vortical fluid flows generated by the shape of the blood vessel. However, the average velocities revealed only relatively minor differences. This study compared the characteristics of PC-MRI and CFD through a phantom study that only included controllable experimental parameters. Based on these results, 4D PC-MRI and CFD are powerful tools for analyzing blood flow patterns in vivo. However, there is room for future developments to improve velocity measurement accuracy.

Dynamical Modelling and Vibration Analysis of the Non-coplanarity of the Orthogonal Support of Gyrowheel

In the engineering implementation of gyrowheel, the influence of orthogonal support non-coplanar is inevitable. However, when the gyrowheel is used for satellite inertial angular velocity measurement, this non-ideal factor will inevitably have an adverse impact on the accuracy of angular velocity measurement. Therefore, the dynamic model of gyrowheel with non-coplanar orthogonal support is established, and the influence of the non-coplanarity support on the vibration frequency is analysed. Finally, the correctness of this research is verified by simulation.

High Temporal Resolution Pyrometry and Velocimetry Based on Acoustic Frequency Division Multiplexing

Real-time and accurate flue gas temperature and velocity measurement is crucial for the safety, efficiency, and low emission of a power plant operation. This article describes a new technique for measuring flue gas temperature and velocity based on acoustic frequency division multiplexing (FDM) in a simultaneous way. The FDM method provides a technique that allows the simultaneous utilization of multiple acoustic signals that leads to a greatly reduced measurement cycle time required; therefore, the measurement system’s temporal resolution is significantly improved. With this new FDM method, the composite signal formed of two channels’ is decomposed by using a Butterworth filter for the extraction of the amplitude and phase information of signals passing each of the individual channels. From the derived frequency signals, the time of flight (TOF) on each acoustic path can be obtained. Demonstrated through both a theoretical analysis and experimental results, by applying the new technique, the measurement period can be reduced to 0.083 times (or say less than 10%) of that by using a traditional method. At the same time, the experimental results indicate that the new technique also improves the accuracy of the measurements. The sensitivity of the FDM method is 3.3, and 2.6 times higher than that of the HWA and traditional methods for velocity, and 1.6 and 1.4 times higher for temperature measurement. Moreover, its optimal robustness and precision are verified by several combined experiments with and without wind with background noise.

Identification of venular capillary remodelling: a possible link to the development of periodontitis?

PurposeThe present study measured changes in arteriolar and venular capillary flow and structure in the gingival tissues during the development of plaque-induced gingival inflammation by combining dynamic optical coherence tomography (OCT), laser perfusion, and capillaroscopic video imaging.MethodsGingival inflammation was induced in 21 healthy volunteers over a 3-week period. Gingival blood flow and capillary morphology were measured by dynamic OCT, laser perfusion imaging, and capillaroscopy, including a baseline assessment of capillary glycocalyx thickness. Venular capillary flow was estimated by analysis of the perfusion images and mean blood velocity/acceleration in the capillaroscopic images. Readings were recorded at baseline and weekly over the 3 weeks of plaque accumulation and 2 weeks after brushing was resumed.ResultsPerfusion imaging demonstrated a significant reduction of gingival blood flow after 1 and 2 weeks of plaque accumulation (P<0.05), but by 3 weeks of plaque accumulation there was a more mixed picture, with reduced flow in some participants and increased flow in others. Participants with reduced flux at 3 weeks also demonstrated venular-type flow as determined by perfusion images and evidence of the development of venular capillaries as assessed by the velocity/acceleration ratio in capillaroscopic images. After brushing resumed, these venular capillaries were broken down and replaced by arteriolar capillaries.ConclusionsAfter 3 weeks of plaque accumulation, there was wide variation in microvascular reactions between the participants. Reduced capillary flow was associated with the development of venular capillaries in some individuals. This is noteworthy, as an early increase in venous capillaries is a key vascular feature of cardiovascular disease, psoriasis, Sjögren syndrome, and rheumatoid arthritis—diseases with a significant association with the development of severe gingival inflammation, which leads to periodontitis. Future investigations of microvascular changes in gingival inflammation might benefit from accurate capillary flow velocity measurements to assess the development of venular capillaries.

In-motion initial alignment method for a laser Doppler velocimeter-aided strapdown inertial navigation system based on an adaptive unscented quaternion H-infinite filter

With its advantages of high velocity measurement accuracy and fast dynamic response, the laser Doppler velocimeter (LDVs) is expected to replace the odometer (OD) in combination with a strapdown inertial navigation system (SINS) to give a higher-precision integrated navigation system. Since a LDV has higher velocity measurement accuracy and data update frequency than an OD and Doppler velocity log, a LDV is used for the first time in this paper to aid a SINS in in-motion alignment. Considering that some approximation is used in the alignment model, the uncertainty noise of the sensors during the motion process and the unknown noise parameters during the filter process, an adaptive unscented quaternion H-infinite estimator (AUSQUHE) is proposed. The proposed AUSQUHE method has high robustness since it combines the advantages of an unscented quaternion estimator and H-infinite filter. The adaptive threshold of the H-infinite filter and the adaptive measurement noise covariance matrix are introduced to make the filter adapt to the changing environment and accelerate the convergence of errors. The performance of the proposed method is verified by a vehicle field test with a normal LDV signal and a vehicle test with the LDV signal disturbed by noise. The results show that the proposed method has higher alignment accuracy, faster convergence speed and stronger robustness than the four other compared methods.

Research on Improving the Accuracy of Axial Stress Measurement Based on Ultrasonic Signal Sine Function Interpolation

The accurate measurement of axial stress of bolts is an essential means to ensure the stable operation of an aero-engine. In the measurement of axial stress of bolt by ultrasonic method, the change of ultrasonic velocity caused by stress is not obvious. In order to ensure the accuracy of ultrasonic velocity measurement, it is necessary to measure the difference of ultrasonic propagation time accurately. A high-sampling rate signal is the prerequisite to improve the measurement accuracy of the ultrasonic propagation time difference. In this paper, by studying the characteristics of ultrasonic signals, sine function interpolation is used to improve the time resolution. The experimental results show that after the sine function interpolation is performed on the ultrasonic signal recorded at a sampling rate of 100 MHz, the average error of bolt axial stress measurement is reduced by 4.288 MPa. Therefore, the sine function interpolation method of ultrasonic signals proposed in this paper can effectively improve the measurement accuracy of the propagation time difference, thereby reducing the measurement error of the bolt axial stress in the large-scale high-speed rotating equipment represented by aero-engines.

Relationship between Resolution and Velocity Measurement Accuracy of Distance and Velocity Sensor based on Self-coupling Effect

Relationship between Resolution and Velocity Measurement Accuracy of Distance and Velocity Sensor based on Self-coupling Effect

Gray consistency optical flow algorithm based on mask-R-CNN and a spatial filter for velocity calculation.

The optical flow method has been widely used to measure the vehicle velocity by observing the stationary ground with a camera looking-down. However, when there are moving objects on the stationary ground, the interfering optical flow field will be generated, which decreases the velocity measurement accuracy of a vehicle relative to the ground. In order to reduce the effects caused by moving objects, this paper integrates pyramid Lucas-Kanade (LK) algorithm with the gray consistency method to use the information of color images thoroughly. First, a mask region with convolutional neural network (Mask-R-CNN) is used to recognize the objects that have motions relative to the ground, and it covers them with masks to enhance the similarity between pixels and to reduce the impacts of the noisy moving pixels. Then images are decomposed into three channels, red, green, and blue (i.e., R, G, and B), and processed by median filter. Based on the gray consistency method, the optical flow can be obtained by the pyramid LK algorithm. Finally, the velocity is calculated by the optical flow value. The prominent advantages of the proposed algorithm are: (i) increase the velocity measurement accuracy of a vehicle relative to the ground; (ii) use the information of color images acquired with cameras thoroughly and obtain velocity calculation outputs with less fluctuation; (iii) reduce wrong values caused by noises that are from the origin image and introduced by similar color masks. Four experiments are conducted to test the proposed algorithm and results with superior precision and reliability show the feasibility and effectiveness of the proposed method for the velocity measurement accuracy of a vehicle relative to the ground.

Localized time accurate sampling of nonequilibrium and unsteady hypersonic flows: methods and horizons

Modern “non-intrusive” optical methods are providing revolutionary capabilities for diagnostics of hypersonic flow fields. They generate accurate information on the performance of ground test facilities and provide local time accurate measurements of near-wall and off-body flow fields surrounding hypersonic test articles. They can follow the true molecular motion of the flow and detect nonequilibrium states and gas mixtures. They can be used to capture a wide range of turbulent scales and can produce highly accurate velocity, temperature and density measurements as well as time-frozen images that provide intuitive understanding of flow phenomena. Recent review articles address many of these methods and their applications. The methods highlighted in this review are those that have been enabled or greatly improved by new, versatile laser systems, particularly including kHz rate femtosecond lasers and MHz rate pulse burst lasers. Although these methods can be applied to combusting environments, the focus of this review is on external high Mach number flows surrounding test articles and wind tunnel core flow properties. The high repetition rates enable rapid time evolving flows to be analyzed and enable the collection of large data sets necessary for statistical analysis. Future capabilities based on the use of atomic vapor filters and on frequency tunable, injection locked MHz rate lasers are promising.

Reconstruction of Velocity Curve in Long Stroke and High Dynamic Range Laser Interferometry.

To study the law that governs the complex movements of the mechanism in the process of automatic weapon operation, the velocity tracking test technology of photon Doppler velocimetry is introduced to accurately measure velocity, displacement and acceleration, on the condition that there are long displacement and rapid velocity change. In the traditional way, out of interference signal time-frequency (TF) transformation draws TF distribution, and then by modulus maxima frequency extraction, comes to the law of velocity change. Due to the influence resulting from the change of fundamental signal as well as that of light intensity signal in the test, based on the TF distribution obtained by TF transformation, the traditional modulus maxima frequency extraction can extract frequency signals, but they show abnormal sudden changes at some moments, making the velocity discontinuous, unsmooth and unreal, which brings obvious errors to the subsequent calculation of acceleration and accurate displacement. Addressing the above-mentioned problems, this paper proposes a ridge extracting correction algorithm based on modulus maxima frequency extraction; this method, based on a large number of experiments where rodless cylinders are used to simulate the motion of a gun automatic mechanism, conducts a detailed calculation and analysis of the experimental results. A comparison of the two algorithms’ processing results, in terms of the speed, displacement and acceleration, suggests that the ridge extracting correction algorithm successfully corrects the frequency selection error, which draws a more continuous and, therefore, effective curve of the velocity change, and by so doing, the error of the displacement test (within 1.36 m displacement) is reduced from more than 3.6% to less than 0.58%, and the uncertainty dropped 97.07%. All these show that the accurate measurement of velocity, displacement and acceleration, with sudden and rapid velocity changes considered, is realized successfully.

A method to enhance the noise robustness of correlation velocity measurement using discrete wavelet transform

Navigation at sea requires accurate velocity measurement of a vehicle relative to the seabed. Correlation velocity measurement techniques are efficiently used to measure the velocity of underwater vehicles because they are not affected by sound speed compared to Doppler techniques, have several advantages such as small size and power consumption and tracking deep seabed. We consider the relationship of maximum correlation coefficient and signal-to-noise ratio (SNR), which are important parameters in correlation velocity measurement and present the maximum correlation coefficient equation according to SNR. Next, we propose a method of the noise robustness enhancement using discrete wavelet transform (DWT) in correlation velocity measurement. In addition, we evaluate the noise robustness of the proposed method and various methods of correlation velocity measurement through simulation, and present the maximum correlation coefficient equation according to SNR of our method. Simulation results show that new method of correlation velocity measurement using wavelet thresholding proposed in this paper improves the noise robustness of correlation velocity measurement more than various methods. In addition, in correlation velocity log (CVL) operating under low SNR below 6 dB, the maximum correlation coefficient of new method increases more than 0.1 than the classical method. Simulation results show that the new method of correlation velocity measurement considerably improved the noise robustness of spatial CVL than classical method, and the noise robustness of new method is highest among various methods of correlation velocity measurement.

Flexible Doppler ultrasound device for the monitoring of blood flow velocity.

Thrombosis and restenosis after vascular reconstruction procedures may cause complications such as stroke, but a clinical means to continuously monitor vascular conditions is lacking. Conventional ultrasound probes are rigid, particularly for postoperative patients with fragile skin. Techniques based on photoplethysmography or thermal analysis provide only relative changes in flow volume and have a shallow detection depth. Here, we introduce a flexible Doppler ultrasound device for the continuous monitoring of the absolute velocity of blood flow in deeply embedded arteries based on the Doppler effect. The device is thin (1 mm), lightweight (0.75 g), and skin conforming. When the dual-beam Doppler method is used, the influence of the Doppler angle on the velocity measurement is avoided. Experimental studies on ultrasound phantoms and human subjects demonstrate accurate measurement of the flow velocity. The wearable Doppler device has the potential to enhance the quality of care of patients after reconstruction surgery.

Direct target localization and vector-velocity measurement method based on bandwidth synthesis in distributed high frequency surface wave radar

The accuracy of target position and velocity measurement is one of the most concerned indexes of Distributed High Frequency Surface Wave Radar (HFSWR). The target localization of HFSWR is commonly achieved by indirect positioning approach. Recently, some direct positioning methods using the raw signals collected on all base-stations have been studied, which have superior positioning performance compared with indirect approaches. But there is almost no joint estimation method for target position and vector-velocity. In this paper, a novel direct target localization and vector-velocity measurement method based on bandwidth synthesis (BS-DTL) in distributed HFSWR system is investigated to improve the accuracy of the target. BS-DTL algorithm that makes full use of the information of all base-stations is considered for the joint estimation of target position and vector-velocity. This paper studies the detection and estimation performance of the BS-DTL algorithm and traditional direct target localization method (DTL). Numerical simulation results show that the proposed algorithm outperforms the traditional DTL method and the position and vector-velocity can be accurately estimated.

A novel flow and pressure catheter for complete interventional cardiology physiology management

Abstract Ischemia with No Obstructive Coronary Artery (INOCA) in angina patients increases the risk of major cardiac events, with a 1.5x increased mortality rate. There is a link between COVID-19 infection and impairment in the myocardial micro-vasculation which may cause an increase of INOCA patients. Fractional Flow Reserve (FFR), is the standard of care in cardiology but its diagnostic function is only related to Obstructive Coronary Artery disease (or epicardial) and it is ineffective with INOCA. The lack of effective and accurate tools for timely evaluation of coronary impairments creates a clinical unmet need. The PhysioCath catheter was developed within the Eurostars project “FP-Catheter, E!113577” aims to resolve this need a provide an effective tool to interventional cardiologists. The main project outcome is a catheter prototype equipped with a blood flow velocity sensor based on a thermo-convection principle, and a fiber optic pressure sensor (based on Fabry-Perot principle). While the use of Fabry-Perot type of sensor is already standard in the industry, the use of a thermo-convection sensor represents a progress with respect the state of the art. The sensor creates an overheat of 7°C above the physiological blood's temperature (considered as being within the safety limits), and it exchanges thermal power with the blood stream. The power is then measured and converted to velocity by means of a calibration curve. The project encompassed interviews with 14 clinical experts, the summary of the interviews indicated that the preferred form of the device is an over the wire microcatheter, with rapid exchange. Within the project then, it was developed a 3Fr microcatheter, with a rapid exchange section of 24cm. Both pressure sensor and flow velocity sensor were integrated in this embodiment. Finally, the PhysioCath prototype was evaluated in a bench test study. The test setup was composed by an anatomical silicone phantom of the aortic root and the coronaries (Elastrat, Geneva, Switzerland), perfused with a peristaltic pump (Harvard Apparatus, Holliston MA, US). The measurements performed by the flow velocity sensor were compared against and external doppler flow velocity sensor. While the pressure measurement was assessed for stability and presence of drift. The data processing revealed and extreme accuracy in the measurement of flow based indexes like CFR (±6% variability), accuracy of the blood flow velocity measurement (±10%), and extreme stability in the measurement of both pressure and flow velocity. In the second part of the project (that is currently ongoing), it will be studied the performance of the device within an animal setting. In conclusion, the PhysioCath device is a microcatheter integrating bot pressure measurement and blood flow velocity measurement. Its performance is of very high accuracy and stability, that represent a main step ahead with respect the current state of the art, based mainly on thermodilution. Funding Acknowledgement Type of funding sources: Public grant(s) – EU funding. Main funding source(s): Eureka-Eurostars Test benchMicrocatheter prototype

Automated segmentation of biventricular contours in tissue phase mapping using deep learning.

Tissue phase mapping (TPM) is an MRI technique for quantification of regional biventricular myocardial velocities. Despite its potential, clinical use is limited due to the requisite labor-intensive manual segmentation of cardiac contours for all time frames. The purpose of this study was to develop a deep learning (DL) network for automated segmentation of TPM images, without significant loss in segmentation and myocardial velocity quantification accuracy compared with manual segmentation. We implemented a multi-channel 3D (three dimensional; 2D + time) dense U-Net that trained on magnitude and phase images and combined cross-entropy, Dice, and Hausdorff distance loss terms to improve the segmentation accuracy and suppress unnatural boundaries. The dense U-Net was trained and tested with 150 multi-slice, multi-phase TPM scans (114 scans for training, 36 for testing) from 99 heart transplant patients (44 females, 1-4 scans/patient), where the magnitude and velocity-encoded (Vx , Vy , Vz ) images were used as input and the corresponding manual segmentation masks were used as reference. The accuracy of DL segmentation was evaluated using quantitative metrics (Dice scores, Hausdorff distance) and linear regression and Bland-Altman analyses on the resulting peak radial and longitudinal velocities (Vr and Vz ). The mean segmentation time was about 2 h per patient for manual and 1.9 ± 0.3 s for DL. Our network produced good accuracy (median Dice = 0.85 for left ventricle (LV), 0.64 for right ventricle (RV), Hausdorff distance = 3.17 pixels) compared with manual segmentation. Peak Vr and Vz measured from manual and DL segmentations were strongly correlated (R≥ 0.88) and in good agreement with manual analysis (mean difference and limits of agreement for Vz and Vr were -0.05 ± 0.98 cm/s and -0.06 ± 1.18 cm/s for LV, and -0.21 ± 2.33 cm/s and 0.46 ± 4.00 cm/s for RV, respectively). The proposed multi-channel 3D dense U-Net was capable of reducing the segmentation time by 3,600-fold, without significant loss in accuracy in tissue velocity measurements.

Position observation-based calibration method for an LDV/SINS integrated navigation system.

With the advantages of high velocity measurement accuracy and fast dynamic response, the laser Doppler velocimeter (LDV) is expected to replace the odometer to be combined with a strapdown inertial navigation system (SINS) to form a higher precision integrated navigation system. However, LDV scale factor error and misalignment angles between LDV and inertial measurement unit will affect the accuracy of navigation. Considering that not all global navigation satellite system (GNSS) receivers can directly provide velocity information and current mainstream calibration methods are sensitive to the measurement noise and outliers of velocity and position information, a robust calibration method aided by GNSS is proposed in this paper, which is based on position observation. Different from current popular calibration methods, the attitude information of the GNSS/SINS integrated navigation system obtained by an adaptive Kalman filter is used to construct the observation vector together with LDV velocity outputs and GNSS position outputs in this method. The LDV scale factor error and the misalignment angle are determined by the ratio of two observation vector modulus and the Davenport's q-method method, respectively. The accuracy and robustness of the calibration method are verified by one vehicle test with normal GNSS signals and one vehicle test with GNSS signals with outliers. And the horizontal position error of dead reckoning of the calibrated LDV/SINS integrated system are less than 0.0314% and 0.1033% of the mileage, respectively.

High Spatial and Temporal Resolution Bistatic Wind Lidar

The high-resolution bistatic lidar developed at the Physikalisch-Technische Bundesanstalt (PTB) aims to overcome the limitations of conventional monostatic lidar technology, which is widely used for wind velocity measurements in wind energy and meteorology applications. Due to the large measurement volume of a combined optical transmitter and receiver tilting in multiple directions, monostatic lidar generally has poor spatial and temporal resolution. It also exhibits large measurement uncertainty when operated in inhomogeneous flow; for instance, over complex terrain. In contrast, PTB’s bistatic lidar uses three dedicated receivers arranged around a central transmitter, resulting in an exceptionally small measurement volume. The coherent detection and modulation schemes used allow the detection of backscattered, Doppler shifted light down to the scale of single aerosols, realising the simultaneous measurement of all three wind velocity components. This paper outlines the design details and theory of operation of PTB’s bistatic lidar and provides an overview of selected comparative measurements. The results of these measurements show that the measurement uncertainty of PTB’s bistatic lidar is well within the measurement uncertainty of traditional cup anemometers while being fully independent of its site and traceable to the SI units. This allows its use as a transfer standard for the calibration of other remote sensing devices. Overall, PTB’s bistatic lidar shows great potential to improve the capability and accuracy of wind velocity measurements, such as for the investigation of highly dynamic flow processes upstream and in the wake of wind turbines.

A proposal for designing the source mass to accurately determine G with atom interferometry

The Newtonian gravitational constant G has proved to be one of the most difficult constants to measure in physics. The improvement of measuring G with the atomic interferometry method is significantly limited by the positioning accuracy of the atom clouds and source masses, and the measurement accuracy of the atomic velocity. In this article, we propose an idea for designing the source masses to determine G with atom interferometry, in which a nearly uniform gravitational field in the motion region of the atom clouds is constructed. This design can greatly reduce the influence of the uncertainty of the atomic initial position and velocity on the precision of G measurement, since these atomic initial conditions affect the interferometer phase shift by coupling themselves with the gravitational gradient. Finally, we present a scheme for measuring G with a relative standard uncertainty of 27 parts per million.

Kalman filtering approach to particle track filtering and track uncertainty quantification for 3D PTV measurement

Three-dimensional Particle Tracking Velocimetry (3D-PTV) is a non-invasive flow measurement technique that computes the velocity field by reconstructing 3D particle positions of individual tracer particles and by subsequently tracking those positions. The particle velocity measurement accuracy depends on the faithful reconstruction of 3D particle positions. The complex measurement chain in 3D-PTV involves several steps, from calibration to 3D position reconstruction and particle position tracking, each having its own source of error. Additionally, higher seeding density increases the uncertainty in particle reconstruction and tracking, which in turn, increases the noise in the estimated tracks. A noisy track decreases the measurement accuracy and amplifies any noise in the PTV-derived quantities of interest, which includes acceleration, pressure and vorticity. Thus, track filtering techniques are critical in a 3D-PTV measurement. Track fitting using polynomial functions, filtering methods adopted from signal processing and object tracking are among the well-established techniques used to achieve smooth position, velocity estimates from reconstructed particle trajectories. The Kalman filter is one such filtering technique that is widely used in various applications. The strength of the Kalman filter lies in its ability to perform noise reduction that is informed by existing physical models and the uncertainty estimates of recorded measurements. However, the measurement uncertainty input to the Kalman filter needs to be known at priori, which in many cases may not be available or could be difficult to estimate. In the literature on Kalman filters and their variants applied to 2D-PIV/PTV, the position uncertainty data fed to the filter is either user-defined or estimated based on global noise levels in the PTV measurements. But instantaneous position and velocity uncertainty quantification for individual particle positions/tracks has been challenging in the 3D PTV community. Recent work by Bhattacharya and Vlachos (2020) provides an estimate of the uncertainty in the reconstructed particle positions for a 3D PTV measurement. This position uncertainty estimate dynamically updates the filter gain for each track and enables the evaluation of the performance of the Kalman filter in 3D PTV track filtering.