Uncertainty Of Velocity Measurements Research Articles

An Observer-Based Adaptive Neural Network Finite-Time Tracking Control for Autonomous Underwater Vehicles via Command Filters

Due to the hostile marine environment, there will inevitably be unpredictable factors during the operation of unmanned underwater vehicles, including changes in ocean currents, hull dimensions, and velocity measurement uncertainties. An improved finite-time adaptive tracking control issue is considered for autonomous underwater vehicles (AUVs) with uncertain dynamics, unknown external disturbances, and unavailable speed information. A state observer is designed to estimate the position and velocity of the vehicle via a neural network (NN) approach. The NN is used to estimate uncertainties and external disturbances. A finite-time controller is designed via backstepping and command filter techniques. A multi-input multi-output (MIMO) filter for AUVs is established, and the corresponding MIMO filter compensation signal is constructed to eliminate the effect of filtering error. All the signals of the closed-loop system are proved to be finite-time bounded. An example with comparison is given to show the effectiveness of our method.

Estimation of Doppler Velocity Degradation Due to Difference in Beam-Pointing Directions

This study investigated the effects of the difference of beam-pointing directions on the Doppler measurements from a spaceborne Ku-band precipitation radar. The Doppler measurement system was a displaced phase center antenna (DPCA) using two antennas that are displaced in the along-track direction. When the beam-pointing directions of the two antennas deviate, Doppler measurements can degrade. The well-known formula for the uncertainty in Doppler velocity measurement is extended to include the effect of the difference of the beam-pointing directions, and a simulation confirmed the formula. The results show that the uncertainty increases from 0.21 to 0.38 m/s for a case of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$S/N = 20$ </tex-math></inline-formula> dB when one antenna footprint center is displaced from the other by half of the half-power beamwidth.

Assessment of the Flow Field and Heat Transfer in a Vane Cooling System Using Magnetic Resonance Velocimetry, Thermochromic Liquid Crystals, and Computational Fluid Dynamics

AbstractComputational fluid dynamics (CFD) is the standard tool in the turbomachinery industry to analyze and optimize internal cooling systems of turbine components, but the code applied has to be validated. This paper presents a combined experimental and numerical study on the flow field and heat transfer in a cooling system consisting of a three-pass serpentine with rib turbulators and trailing edge ejection. The cooling geometry is taken from a stator vane currently used in an industrial gas turbine and operates at a coolant inlet Reynolds number of 45,000. As an experimental technique, magnetic resonance velocimetry (MRV) was used to obtain the three-dimensional time-averaged velocity field of the isothermal flow. The measurements were conducted in a large-scale model and resulted in 3.2 million velocity vectors and measurement uncertainty of 6.1% of the bulk inlet velocity. The local wall heat transfer was measured in a separate experiment using thermochromic liquid crystals (TLC). These measurements yielded the distribution of the heat transfer coefficient on both the pressure and the suction side internal walls with a measurement uncertainty of 12%. The experimental data are used as a reference for the numerical study. In total, eight turbulence models are evaluated here, including one-equation, two-equation, algebraic and differential Reynolds stress models, and a scale adaptive simulation. The results show the differences between the velocity fields and the heat transfer coefficient distribution, allowing for the identification of the optimum turbulence model for this particular type of flow.

LabSAR, a one-GCP coregistration tool for SAR–InSAR local analysis in high-mountain regions

The coregistration of single-look complex (SLC) SAR images for InSAR or offset tracking applications is often performed by using an accurate DEM and precise orbital information. However, in cold regions, such DEMs are rare over high-latitude areas or not up-to-date over fast melting glaciers for instance. To overcome this difficulty, we propose in this article a coregistration method preserving InSAR phase information that only requires a 3D point of reference instead of a full DEM. Developed in a Python toolbox called LabSAR, the proposed method only uses orbital information to coregister the images on the sphere centered on the Earth center passing by the ground control point (GCP). Thanks to the use of the orbital information, the so-called orbital fringes are compensated without having to estimate them. This coregistration method is compared to other approaches in two different types of applications, InSAR and offset tracking, on a PAZ Dual-Pol Temporal Stack covering the Mont Blanc massif (western European Alps). First, InSAR measurements from LabSAR are compared with the results of the Sentinel-1 ESA toolbox (SNAP). The LabSAR interferograms exhibit clearer topographical fringes, with fewer parameters to set. Second, offset tracking based on LabSAR coregistated images is used to measure the displacement of the Bossons glacier. The results are compared with those obtained by a conventional approach developed in the EFIDIR tools. By evaluating the uncertainties of both approaches using displacements over stable areas and the temporal closure error, similar uncertainty values are found. However, velocity values differ between the two approaches, especially in areas where the altitudes are different from the altitude of the reference point. The difference can reach up to 0.06 m/day, which is in the range of the glacier velocity measurement uncertainty given in the literature. The impact of the altitude of the reference point is limited: this single GCP can be chosen at the median altitude of the study area. The error margin on the knowledge of this altitude is 1,000 m, which is sufficient for the altitude to be considered as known for a wide range of study area in the world.

Free-Surface Velocity Measurement Using Direct Sensor Orientation-Based STIV.

Particle image velocimetry (PIV) is a quantitative flow visualization technique, which greatly improves the ability to characterize various complex flows in laboratory and field environments. However, the deployment of reference objects or ground control points (GCPs) for velocity calibration is still a challenge for in situ free-surface velocity measurements. By combining space-time image velocimetry (STIV) with direct sensor orientation (DSO) photogrammetry, a laser distance meter (LDM)-supported photogrammetric device is designed, to realize the GCPs-free surface velocity measurement under an oblique shooting angle. The velocity calibration with DSO is based on the collinear equation, while the lens distortion, oblique shooting angle, water level variation, and water surface slope are introduced to build an imaging measurement model with explicit physical meaning for parameters. To accurately obtain the in situ position and orientations of the camera utilizing the LDM and its embedded tilt sensor, the camera’s intrinsic parameters and relative position within the LDM are previously calibrated with a planar chessboard. A flume experiment is designed to evaluate the uncertainty of optical flow estimation and velocity calibration. Results show that the proposed DSO-STIV has good transferability and operability for in situ measurements. It is superior to propeller current meters and surface velocity radars in characterizing shallow free-surface flows; this is attributed to its non-intrusive, whole-field, and high-resolution features. In addition, the combined uncertainty of free-surface velocity measurement is analyzed, which provides an alternative solution for error assessment when comparing measurement failures.

A Method for Analysis of Spatial Uncertainty in Image Based Surface Velocimetry

The use of image based velocimetry methods for field-scale measurements of river surface flow and river discharge have become increasingly widespread in recent years, as these methods have several advantages over more traditional methods. In particular, image based methods are able to measure over large spatial areas at the surface of the flow at high spatial and temporal resolution without requiring physical contact with the water. However, there is a lack of tools to understand the spatial uncertainty in these methods and, in particular, the sensitivity of the uncertainty to parameters under the implementer's control. We present a tool specifically developed to assess spatial uncertainty in remotely sensed, obliquely captured, quantitative images, used in surface velocimetry techniques, and selected results from some of our measurements as an illustration of the tool's capabilities. The developed software is freely available via the public repository GitHub. Uncertainty exists in the coordinate transformation between pixel array coordinates (2D) and physical coordinates (3D) because of the uncertainty related to each of the inputs to the calculation of this transformation, and additionally since the transformation itself is generally calculated in a least squares sense from an over determined system of equations. In order to estimate the uncertainty of the transformation, we perform a Monte Carlo simulation, in which we perturb the inputs to the algorithm used to find the coordinate transformation, and observe the effect on the results of transformations between pixel- and physical- coordinates. This perturbation is performed independently a large number of times over a range of the input parameter space, creating a set of inputs to the coordinate transformation calculation, which are used to calculate a coordinate transformation, and predict the physical coordinates of each pixel in the image. We analyze the variance of the physical position corresponding to each pixel location across the set of transformations, and quantify the sensitivity of the transformation to changes in each of the inputs across the field of view. We also investigate the impact on uncertainty of ground control point (GCP) location and number, and quantify spatial change in uncertainty, which is the key parameter for calculating uncertainty in velocity measurements, in addition to positions. This tool may be used to plan field deployments, allowing the user to optimize the number and distribution of GCPs, the accuracy with which their position must be determined, and the camera placement required to achieve a target level of spatial uncertainty. It can also be used to estimate the uncertainty in image-based velocimetry measurements, including how this uncertainty varies over space within the field of view.

A study on the influence of ignition energy on ignition delay time and laminar burning velocity of lean methane/air mixture in a constant volume combustion chamber

This study presents the effect of ignition energy (Eig) on ignition delay time (tdelay) and uncertainty of laminar burning velocity (Su0) measurement of lean methane/air mixture in a constant volume combustion chamber. The mixture at an equivalence ratio of 0.6 is ignited using a pair of electrodes at the 2-mm spark gap. Eig is measured by integrating the product of voltage V(t) and current I(t) signals during a discharge period. The in-chamber pressure profiles are analyzed using the pressure-rise method to obtain tdelay and Su0. Su0 approximates 8.0 cm/s. Furthermore, the increasing Eig could shorten tdelay, leading to a faster combustion process. However, when Eig is greater than a critical value, called minimum reliable ignition energy (MRIE), the additional elevating Eig has the marginal effect on tdelay and Su0. The existence of MRIE supports to optimize the ignition systems and partly explains why extreme-high Eig&gt;&gt; MRIE has less contribution to engine performance.

Impact of the sampling duration on the uncertainty of averaged velocity measurements with acoustic instruments

AbstractAverage velocity in streams is a key variable for the analysis and modelling of hydrological and hydraulic processes underpinning water resources science and practice. The present study evaluates the impact of the sampling duration on the quality of average velocity measurements acquired with contemporary instruments such as Acoustic Doppler Velocimeters (ADV) an Acoustic Doppler Current Profilers (ADCP). The evaluation combines considerations on turbulent flows and principles and configurations of acoustic instruments with practical experience in conducting customized analysis for uncertainty analysis purposes. The study sheds new insights on the spatial and temporal variability of the uncertainty in the measurement of average velocities due to variable sampling durations acting in isolation from other sources of uncertainties. Sampling durations of 90 and 150 s are found sufficient for ADV and ADCP, respectively, to obtain reliable average velocities in a flow affected only by natural turbulence and instrument noise. Larger sampling durations are needed for measurements in most of the natural streams exposed to additional sources of data variability.

Influence of near-wall PIV data on recirculation hemodynamics in a patient-specific moderate stenosis: Experimental-numerical comparison.

Recirculation zones within the blood vessels are known to influence the initiation and progression of atherosclerotic lesions. Quantification of recirculation parameters with accuracy remains subjective due to uncertainties in measurement of velocity and derived wall shear stress (WSS). The primary aim is to determine recirculation height and length from PIV experiments while validating with two different numerical methods: finite-element (FE) and -volume (FV). Secondary aim is to analyze how FE and FV compare within themselves. PIV measurements were performed to obtain velocity profiles at eight cross sections downstream of stenosis at flow rate of 200ml/min. WSS was obtained by linear/quadratic interpolation of experimental velocity measurements close towall. Recirculation length obtained from PIV technique was 1.47cm and was within 2.2% of previously reported in-vitro measurements. Derived recirculation length from PIV agreed within 6.8% and 8.2% of the FE and FV calculations, respectively. For lower shear rate, linear interpolation with five data points results in least error. For higher shear rate either higher order (quadratic) interpolation with five data points or lower order (linear) with lesser (three) data points leads to better results. Accuracy of the recirculation parameters is dependent on number of near wall PIV data points and the type of interpolation algorithm used.

COMPARISON OF ULTRASONIC PULSE VELOCITY TEST RESULTS WITH AND WITHOUT USING TRANSDUCER STABILIZER

Some research on the Ultrasonic Pulse Velocity (UPV) test has not covered much about the problems encountered during the data collection process. Based on experience using UPV test equipment, it is known that instability occurs in reading the test results. This is caused by the inability of the operator, in maintaining the stability of the transducer both in its position and pressure, especially in the measurement with the overhead position. Therefore, in this study a tool was made to make the transducer stable in the test position. Comparison of measurement results shows that, the uncertainty of wave velocity measurement decreases from the range of 4% -17% to 0.2% -0.4%. Meanwhile, the uncertainty of measurement of wave travel time decreased from the range of 0.8% -14% to 0.1% -0.4%. This can be interpreted that, the level of accuracy of measurements using a transducer stabilizer is 99.6% -99.9%. Thus, the use of transducer stabilizers is believed to be able to improve measurement accuracy.

Evaluating Uncertainties of Phase Velocity Measurements from Cross-Correlations of Ambient Seismic Noise

Abstract Ambient-noise tomography (ANT) has become a well-established method to image the crust and uppermost mantle structures in the past 15 yr. Having a good estimate of uncertainties of phase velocity dispersion measurements in ANT is critical as they can guide the level of data fitting in tomography. However, to date, there are still no systemic studies to evaluate these uncertainties. In this study, we obtain cross correlations with different stacking durations from 17 yr of ambient-noise data recorded at 120 stations in the United States. We analyze the variations of signal-to-noise ratio (SNR) and phase velocities of cross correlations. We find that the uncertainties of phase velocities are affected by SNRs, interstation distances, and stacking durations. However, none of those three variables can be solely used as a proxy to estimate the uncertainties of phase velocity measurements. Based on our analysis, we graphically present empirical relations of uncertainties of phase velocity measurements as a function of SNR, interstation distance, and stacking duration. These relations can be employed as a guide to estimate phase velocity uncertainties in applications of ANT, assisting in evaluating the reliability of resulting models from ANT.

Robust Tracking Control of Robot Manipulators With Actuator Faults and Joint Velocity Measurement Uncertainty

This article solves the safe trajectory tracking control problem of robot manipulators with actuator faults, uncertain dynamics, and external disturbance. Another key issue met in practical robot engineering, i.e., joint velocity measurement uncertainty is also investigated. A robust control framework is presented. In this approach, a novel reconstruction law is preliminarily developed to estimate velocity measurement uncertainty, while the estimation error is finite-time stable. An adaptive control law is, then, designed by using the joint position, the estimated velocity, and the reconstructed knowledge of velocity measurement uncertainty. The key advantage of this methodology is that actual joint velocity and any prior knowledge of actuator faults are not required. The effectiveness of this proposed scheme is experimentally validated on a real robot arm.

Regularized tomographic PIV for incompressible flows based on conservation of mass.

Three-dimensional and three-component (3D3C) velocity measurements have long been desired to resolve the 3D spatial structures of turbulent flows. Recent advancements have demonstrated tomographic particle image velocimetry (tomo-PIV) as a powerful technique to enable such measurements. The existing tomo-PIV technique obtains 3D3C velocity field by cross-correlating two frames of 3D tomographic reconstructions of the seeding particles. A most important issue in 3D3C velocity measurement involves uncertainty, as the derivatives of the measurements are usually of ultimate interest and uncertainties are amplified when calculating derivatives. To reduce the uncertainties of 3D3C velocity measurements, this work developed a regularized tomo-PIV method. The new method was demonstrated to enhance accuracy significantly by incorporating the conservation of mass into the tomo-PIV process. The new method was demonstrated and validated both experimentally and numerically. The results illustrated that the new method was able to enhance the accuracy of 3D3C velocity measurements by 40%-50% in terms of velocity magnitude and by 0.6°-1.1° in terms of velocity orientation, compared to the existing tomo-PIV technique. These improvements brought about by the new method are expected to expand the application of tomo-PIV techniques when accuracy and quantitative 3D flow properties are required.

DO-LPV-based robust 3D path following control of underactuated autonomous underwater vehicle with multiple uncertainties

This study investigates a path following problem of underactuated autonomous underwater vehicle under multiple uncertainties in three-dimensional space. The uncertainties are partly induced by hydrodynamic coefficient uncertainty, ocean currents and unmodeled hydrodynamics, namely dynamic uncertainties. In addition, velocities are assumed to be measured with bounded noise, which is called velocity measurement uncertainties. To address this issue, a compound robust path following control strategy is developed. At the kinematic level, an improved kinematic controller is developed by utilizing disturbance observer to recover the unknown time-varying attack and side-slip angular velocity. At the dynamic level, a novel dynamic tracking model is firstly established via linear parameter varying (LPV) technique, by which multiple uncertainties are expressed in a comprehensive way. Subsequently, a robust LPV controller is employed to track desired velocities generated by kinematic controller, which has less dependence on accurate model and exact velocity measurement. Finally, rigorous stability analysis proves the uniform and ultimate boundedness of path following errors. The comparative numerical results also substantiate the efficacy and superiority of designed method.

True eddy accumulation trace gas flux measurements: proof of concept

Abstract. Micrometeorological methods to quantify fluxes of atmospheric constituents are key to understanding and managing the impact of land surface sources and sinks on air quality and atmospheric composition. Important greenhouse gases are water vapor, carbon dioxide, methane, and nitrous oxide. Further important atmospheric constituents are aerosols, which impact air quality and cloud formation, and volatile organic compounds. Many atmospheric constituents therefore critically affect the health of ecosystems and humans, as well as climate. The micrometeorological eddy covariance (EC) method has evolved as the method of choice for CO2 and water vapor flux measurements using fast-response gas analyzers. While the EC method has also been used to measure other atmospheric constituents including methane, nitrous oxide, and ozone, the often relatively small fluxes of these constituents over ecosystems are much more challenging to measure using eddy covariance than CO2 and water vapor fluxes. For many further atmospheric constituents, eddy covariance is not an option due to the lack of sufficiently accurate and fast-response gas analyzers. Therefore, alternative flux measurement methods are required for the observation of atmospheric constituent fluxes for which no fast-response gas analyzers exist or which require more accurate measurements. True eddy accumulation (TEA) is a direct flux measurement technique capable of using slow-response gas analyzers. Unlike its more frequently used derivative, known as the relaxed eddy accumulation (REA) method, TEA does not require the use of proxies and is therefore superior to the indirect REA method. The true eddy accumulation method is by design ideally suited for measuring a wide range of trace gases and other conserved constituents transported with the air. This is because TEA obtains whole air samples and is, in combination with constituent-specific fast or slow analyzers, a universal method for conserved scalars. Despite the recognized value of the method, true eddy accumulation flux measurements remain very challenging to perform as they require fast and dynamic modulation of the air sampling mass flow rate proportional to the magnitude of the instantaneous vertical wind velocity. Appropriate techniques for dynamic mass flow control have long been unavailable, preventing the unlocking of the TEA method's potential for more than 40 years. Recently, a new dynamic and accurate mass flow controller which can resolve turbulence at a frequency of 10 Hz and higher has been developed by the first author. This study presents the proof of concept that practical true eddy accumulation trace gas flux measurements are possible today using dynamic mass flow control, advanced real-time processing of wind measurements, and fully automatic gas handling. We describe setup and methods of the TEA and EC reference flux measurements. The experiment was conducted over grassland and comprised 7 d of continuous flux measurements at 30 min flux integration intervals. The results show that fluxes obtained by TEA compared favorably to EC reference flux measurements, with coefficients of determination of up to 86 % and a slope of 0.98. We present a quantitative analysis of uncertainties of the mass flow control system, the gas analyzer, and gas handling system and their impact on trace gas flux uncertainty, the impact of different approaches to coordinate rotation, and uncertainties of vertical wind velocity measurements. Challenges of TEA are highlighted and solutions presented. The current results are put into the context of previous works. Finally, based on the current successful proof of concept, we suggest specific improvements towards long-term and reliable true eddy accumulation flux measurements.

Towards consideration of epistemic uncertainty in shear-wave velocity measurements obtained via seismic cone penetration testing (SCPT)

Seismic cone penetration testing (SCPT) is a powerful geotechnical site characterization tool, allowing for simultaneous collection of routine cone penetration testing data and rapid downhole-type measurements of shear-wave velocity (VS). However, the uncertainties associated with developing VS profiles from SCPT measurements are rarely considered or communicated to the end-user. One important source of VS uncertainty is related to how the shear wave travel times are interpreted from the recorded waveforms, while another critical source of uncertainty is related to the analysis method used to transform the travel times to velocities. In this study, four common ways of obtaining travel times were considered: (i) first arrival picks, (ii) peaks and troughs picks, (iii) crossover picks, and (iv) the peak response of the cross-correlation function. Using these different travel times, a number of VS profiles were developed using four different velocity analysis methods: (i) pseudo-interval, (ii) true-interval, (iii) corrected vertical travel time slope-based, and (iv) raytracing. Through consideration of multiple wave arrival time and velocity analysis methods, a robust and meaningful quantification of the intramethod, depth-dependent epistemic uncertainty in VS obtained from several example SCPT datasets has been developed. VS uncertainty is further examined through consideration of the intermethod variability and bias between SCPT and direct-push crosshole testing.

Investigation of velocity and temperature measurement sensitivities in cross-correlation filtered Rayleigh scattering (CCFRS)

The cross-correlation filtered Rayleigh scattering method is presented for planar measurements of time-averaged velocity, temperature, density, and pressure using laser scanning, Rayleigh scattering, and cross-correlation-based signal processing. Of particular note, the methods and analyses presented show that velocity and temperature measurements are obtainable at acceptable uncertainties for many aerodynamic applications with or without particles present. In the current work, velocity and temperature measurement uncertainties for this method are analysed by Monte Carlo simulations and evaluation of the Cramér–Rao lower bounds for the signals generated in this approach with aerodynamic applications in mind. A key aspect considered is the relative strength of Rayleigh (molecular) scattering and Mie (particle) scattering contributions to the simulated flow signal. Compared to particle-based velocity estimation, the effects due to convolution between the molecular filter and the broadband Rayleigh scattering spectrum are found to increase the estimator variance of the velocity. For given flow conditions, the velocity error associated with the signal processing routine with noise-free signals is found to be less than , and bias error associated with discrete sampling in the laser frequency domain is within . For these same conditions, temperature measurement simulations indicate bias error bounds of 0. 014% with random uncertainty bounds of less than  ±1.4% for a signal with no Mie scattering contribution, and bias error bounds of less than  ±0.14% with random uncertainty bounds of less than 3.2% for flows contaminated with Mie scattering sources at a signal-to-noise ratio of 25 dB or greater. This technique is also being further developed to measure density and pressure using the principles of laser Rayleigh scattering in flows containing particles of unknown sizes and concentrations.

Wire-mesh sensors: A review of methods and uncertainty in multiphase flows relative to other measurement techniques

Abstract Void fraction has always been an important parameter in the study of multiphase flows and its measurement has proven difficult over the years. This paper is a state of the art review of the application of conductivity based wire-mesh sensors (WMS) for the measurement of void fraction, bubble size, and gas fraction velocity in multiphase flows and their associated uncertainties. At this point in time there is no golden standard for void fraction measurement, so a large bulk of this work is on the uncertainty of the WMSs relative to other void fraction measurement methods, namely radiative methods. It is shown using the available data that the WMS have a void fraction measurement uncertainty of ±10.5% over a variety of flow regimes relative to other measurement methods. However, the accuracy of the instrument is largely based on its applicability to a particular flow. For example, the WMS is an excellent choice when entrapment in the sensor due to surface tension is minimized resulting in best results at higher flow rates compared to radiative methods. An assessment into the uncertainty of velocity and bubble size measurements is also performed: analyzing the current algorithms available and studies on these measurements in comparison with high speed cameras and ultrafast X-ray tomography. The current functioning form of the wire-mesh sensors were developed by Prasser in 1998 as a tomographic technique for the measurement of void fraction using a conductivity approach, as performed by earlier researchers. Later developments with the senors resulted in various techniques that allow for the measurement of velocity and interfacial area concentration.

Identification of meteorite source regions in the Solar System

Over the past decade there has been a large increase in the number of automated camera networks that monitor the sky for fireballs. One of the goals of these networks is to provide the necessary information for linking meteorites to their pre-impact, heliocentric orbits and ultimately to their source regions in the solar system. We re-compute heliocentric orbits for the 25 meteorite falls published to date from original data sources. Using these orbits, we constrain their most likely escape routes from the main asteroid belt and the cometary region by utilizing a state-of-the-art orbit model of the near-Earth-object population, which includes a size-dependence in delivery efficiency. While we find that our general results for escape routes are comparable to previous work, the role of trajectory measurement uncertainty in escape-route identification is explored for the first time. Moreover, our improved size-dependent delivery model substantially changes likely escape routes for several meteorite falls, most notably Tagish Lake which seems unlikely to have originated in the outer main belt as previously suggested. We find that reducing the uncertainty of fireball velocity measurements below ∼ 0.1 km/s does not lead to reduced uncertainties in the identification of their escape routes from the asteroid belt and, further, their ultimate source regions. This analysis suggests that camera networks should be optimized for the largest possible number of meteorite recoveries with measured speed precisions of order 0.1 km/s.

Influence of speckle effect on doppler velocity measurement

In a coherent Lidar system, velocity measurement of a target is achieved by measuring Doppler frequency shift between the echo and local oscillator (LO) signals. The measurement accuracy is proportional to the spectrum width of Doppler signal. Actually, the speckle effect caused by the scattering of laser from a target will broaden the Doppler signal's spectrum and bring uncertainty to the velocity measurement. In this paper, a theoretical model is proposed to predict the broadening of Doppler spectrum with respect to different target's surface and motion parameters. The velocity measurement uncertainty caused by the broadening of spectrum is analyzed. Based on the analysis, we design a coherent Lidar system to measure the velocity of the targets with different surface roughness and transverse velocities. The experimental results are in good agreement with theoretical analysis. It is found that the target's surface roughness and transverse velocity can significantly affect the spectrum width of Doppler signal. With the increase of surface roughness and transverse velocity, the measurement accuracy becomes worse. However, the influence of surface roughness becomes weaker when the spot size of laser beam on the target is smaller.