Velocity Estimation Error Research Articles

Novel algorithm for X-ray pulsar navigation against doppler effects

In this paper, a new method for novel X-ray pulsar navigation is proposed to overcome the Doppler effects from the motion of a deep space explorer. An analysis was undertaken of the dynamic orbit model of the interplanetary trajectory cruise phase. During a pulsar signal observation period, the deep space explorer can be considered to be at a constant acceleration motion. A Doppler compensation method is proposed based on this analysis. The method demonstrates great advantages in terms of low computational cost. However, there is an evident bias due to the Doppler compensation in the pulse time-of-arrival (TOA). Moreover, the pulse TOA bias and the velocity estimation error of the deep space explorer are correlated, resulting in a decline in Kalman filter performance. To deal with this problem, we constructed a TOA measurement bias model with respect to the state estimation error, and we developed an extended Kalman filter (EKF) with correlated measurement bias and state estimation error. Results from simulations suggest that the proposed navigation method is feasible, accurate, and effective. The proposed navigation method based on EKF with correlated measurement bias and state estimation error proves to be more accurate than a traditional EKF-based method.

Concurrent Spacecraft Attitude and Orbit Estimation with Attitude Control Based on Magnetometer, Gyro, and GPS Measurements through Extended Kalman Filter

The main objective of this research is to provide attitude estimation, orbit estimation, and attitude control algorithms suitable for application to the next Egyptian scientific satellite. Concurrent spacecraft orbit and attitude estimates must be suitable for usage by the attitude control algorithm. The developed estimation algorithms are able to deal with sever tumbling conditions characterized by large initial attitude, angular velocity and position estimation errors. The estimation algorithms could provide attitude estimates within 0.5 o (3-s) and 60 m (3-s) for the position estimation errors. The attitude control algorithm developed is able to bring the spacecraft from its initial tumbling conditions to nadir pointing within an error of only 0.5 o (3-s).

Role of Distribution Function in Vibration Related Error of Strapdown INS in Random Vibration Test

In this paper, a detailed investigation of the random vibration test is presented for strapdown inertial navigation systems (INS). The effect of the random vibration test has been studied from the point of view of navigation performance. The role of distribution functions and RMS value is represented to determine a feasible method to reject or reduce vibration related error in position and velocity estimation in inertial navigation. According to a survey conducted by the authors, this is the first time that the effect of the distribution function in vibration related error has been investigated in random vibration testing of INS. Recorded data of navigation grade INS is used in offline static navigation to examine the effect of different characteristics of random vibration tests on navigation error.

Rigid body attitude estimation based on the Lagrange–d’Alembert principle

Estimation of rigid body attitude and angular velocity without any knowledge of the attitude dynamics model is treated using the Lagrange–d’Alembert principle from variational mechanics. It is shown that Wahba’s cost function for attitude determination from two or more non-collinear vector measurements can be generalized and represented as a Morse function of the attitude estimation error on the Lie group of rigid body rotations. With body-fixed sensor measurements of direction vectors and angular velocity, a Lagrangian is obtained as the difference between a kinetic energy-like term that is quadratic in the angular velocity estimation error and an artificial potential obtained from Wahba’s function. An additional dissipation term that depends on the angular velocity estimation error is introduced, and the Lagrange–d’Alembert principle is applied to the Lagrangian with this dissipation. A Lyapunov analysis shows that the state estimation scheme so obtained provides stable asymptotic convergence of state estimates to actual states in the absence of measurement noise, with an almost global domain of attraction. These estimation schemes are discretized for computer implementation using discrete variational mechanics. A first order Lie group variational integrator is obtained as a discrete-time implementation. In the presence of bounded measurement noise, numerical simulations show that the estimated states converge to a bounded neighborhood of the actual states.

Local thermal non-equilibrium in sediments: Implications for temperature dynamics and the use of heat as a tracer

Understanding streambed thermal processes is of fundamental importance due to the effects of temperature dynamics on stream ecology and solute exchange processes. Local Thermal Equilibrium (LTE) between fluid and solid is usually assumed for modelling heat exchange in streambeds and for inferring pore water flow velocities from streambed temperature data. By examining well established experimental and theoretical relationships of the fluid–solid heat transfer coefficient in a numerical scheme for a range of Reynolds (Re) numbers (0.01>Re>0.001), we show here that, for a range of typical streambed conditions, LTE is not attained. Thus errors in velocity estimates obtained when inverting streambed temperature data assuming LTE can be considerable especially at relatively low flow rates. We show that for certain conditions were the LTE assumption is not valid, inferred pore water velocities of up to 1m/d can be obtained with LTE assumption even if the actual velocities are much smaller or even zero. Ignoring the possibility of Local Thermal Non-Equilibrium (LTNE) will have consequences for the correct estimation of streambed pore water velocity and heat fluxes at low Re values. More laboratory studies are urgently needed to supplement the sparse existing data in this area and further test the findings of this study

Passive Synthetic Aperture Hitchhiker Imaging of Ground Moving Targets - Part 2: Performance Analysis.

In Part 1 of this work, we present a passive synthetic aperture imaging and velocity estimation method for ground moving targets using a network of passive receivers. The method involves inversion of a Radon transform type forward model via a novel filtered backprojection approach combined with entropy optimization. The method is applicable to noncooperative transmitters of opportunity where the transmitter locations and transmitted waveforms are unknown. Furthermore, it can image multiple targets moving at different velocities in arbitrary imaging geometries. In this paper, we present a detailed analysis of the performance of our method. First the resolution analysis in position and velocity spaces is presented. The analysis identifies several factors that contribute positively or negativity towards position and velocity resolution. Next, we present a novel theory to analyze and predict smearing artifacts in position images due to error in velocity estimation of moving targets. Specifically, we show that small errors in the velocity estimation result in small positioning errors. We present extensive numerical simulations to demonstrate the theoretical results. While our primary interest lies in radar, the theory, methods and algorithms introduced in our work are also applicable to passive acoustic, seismic, and microwave imaging.

The Analysis of the UKF-Based Navigation Algorithm during GPS Outage

The unscented Kalman filter (UKF) became very attractive for the navigation sensors data fusion, because of algorithm significant accuracy and implementation advantages. The unscented Kalman filter is based on the unscented transform (UT) to perform the estimation of the system states. The main idea of the unscented transformation is following. It’s more effective to approximate probability distribution function than arbitrary transformation or nonlinear function. The developed sensors data fusion algorithm using the UKF is considered in this work. This algorithm was applied for the state estimation of the loosely coupled GPS/INS integrated navigation system. GPS/INS integrated navigation system contains low cost inertial sensors and low cost GPS receiver. To demonstrate the estimation performance, the processing of sensors data was done using linear Kalman filter (KF), extended Kalman filter (EKF) and UKF. As a result, UKF has lower velocity estimation error than EKF during simulated GPS signal outage. DOI: http://dx.doi.org/10.5755/j01.eee.19.10.5886

Technical Notes: Using Microphone Arrays to Detect Moving Vehicle Velocity

Abstract The noise of motor vehicles is one of the most important problems as regards to pollution on main roads. However, this unpleasant characteristic could be used to determine vehicle speed by external observers. Building on this idea, the present study investigates the capabilities of a microphone array system to identify the position and velocity of a vehicle travelling on a previously established route. Such linear microphone array has been formed by a reduced number of microphones working at medium frequencies as compared to industrial microphone arrays built for location purposes, and operates with a processing algorithm that ultimately identifies the noise source location and reduces the error in velocity estimation

Computationally Efficient Adaption of the Window Size of Discrete Position Differentiators

Digital motion control requires precise and low-noise velocity information. Since this velocity information must be calculated from position encoders in each control cycle, time efficiency of these algorithms is a very important design goal. Additionally, it is required that these algorithms operate over wide ranges of both velocity and acceleration. Model-based feedback observers fulfill these requirements for many applications but in some cases they, for various reasons, cannot be formulated. Various applications have been presented in which adaptive filters are applied to overcome the compromises of fixed-length filters. However, it remains desirable to improve the performance of these methods especially in regions of very low velocity and to lower the computation time. This paper presents a new algorithm for the adaption of the window size of differentiator algorithms and a novel criterion for the velocity estimation. This criterion is used to take the dependence between the system’s acceleration and the velocity estimation error into account. The properties are studied in simulations and compared to other differentiation techniques. Additionally, results from experiments with a 6-degree-of-freedom servohydraulic Stewart–Gough platform equipped with the new velocity estimation scheme are presented and compared to the performance of concurrent algorithms.

Ultrasound Imaging Velocimetry: Effect of Beam Sweeping on Velocity Estimation

As an emerging flow-mapping tool that can penetrate deep into optically opaque media such as human tissue, ultrasound imaging velocimetry has promise in various clinical applications. Previous studies have shown that errors occur in velocity estimation, but the causes have not been well characterised. In this study, the error in velocity estimation resulting from ultrasound beam sweeping in image acquisition is quantitatively investigated. The effects on velocity estimation of the speed and direction of beam sweeping relative to those of the flow are studied through simulation and experiment. The results indicate that a relative error in velocity estimation of up to 20% can be expected. Correction methods to reduce the errors under steady flow conditions are proposed and evaluated. Errors in flow estimation under unsteady flow are discussed.

Concurrent Spacecraft Attitude and Orbit Estimation with Attitude Control Based on Magnetometer, Gyroscope, and GPS Measurements through Extended Kalman Filter

The main objective of this research is to provide attitude estimation, orbit estimation, and attitude control algorithms suitable for application to the next Egyptian scientific satellite. Concurrent spacecraft orbit and attitude estimates must be suitable for usage by the attitude control algorithm. The developed estimation algorithms are able to deal with sever tumbling conditions characterized by large initial attitude, angular velocity and position estimation errors. The estimation algorithms could provide attitude estimates within 0.5o (3- ) and 60 m (3- ) for the position estimation errors. The attitude control algorithm developed is able to bring the spacecraft from its initial tumbling conditions to nadir pointingwithin an error of only 0.5o (3- ).

Chaos Suppression in forced Van Der Pol Oscillator

paper presents a new method of controlling chaos in the nonlinear Van Der Pol oscillator with uncertainties. The proposed method is based on a nonlinear observer to estimate unmeasured velocity signal coupled to a control law. The observer ensures, firstly, an asymptotic convergence of the velocity estimation error. Then, the control law, which is based on the estimated variables, forces the output system to track a desired trajectory despite presence of uncertainties (external forces) on the system dynamics. Simulation results are provided to show the effectiveness of the proposed control strategy.

An optical flow approach to tracking colonoscopy video

We can supplement the clinical value of an optical colonoscopy procedure if we can continuously co-align corresponding virtual colonoscopy (from preoperative X-ray CT exam) and optical colonoscopy images. In this work, we demonstrate a computer vision algorithm based on optical flow to compute egomotion from live colonoscopy video, which is then used to navigate and visualize the corresponding patient anatomy from X-ray CT data. The key feature of the algorithm lies in the effective combination of sparse and dense optical flow fields to compute the focus of expansion (FOE); FOE permits independent computation of camera translational and rotational parameters, directly contributing to the algorithm's accuracy and robustness. We performed extensive evaluation via a colon phantom and clinical colonoscopy data. We constructed two colon like phantoms, a straight phantom and a curved phantom to measure actual colonoscopy motion; tracking accuracy was quantitatively evaluated by comparing estimated motion parameters (velocity and displacement) to ground truth. Thirty straight and curved phantom sequences were collected at 10, 15 and 20mm/s (5 trials at each speed), to simulate typical velocities during colonoscopy procedures. The average error in velocity estimation was within 3mm/s in both straight and curved phantoms. Displacement error was under 7mm over a total distance of 287–288mm in the straight and curved phantoms. Algorithm robustness was successfully demonstrated on 27 optical colonoscopy image sequences from 20 different patients, and spanning 5 different colon segments. Specific sequences among these were chosen to illustrate the algorithm's decreased sensitivity to (1) recording interruptions, (2) errors in colon segmentation, (3) illumination artifacts, (4) presence of fluid, and (5) changes in colon structure, such as deformation, polyp removal, and surgical tool movement during a procedure.

A Fast Method to Estimate the Wall Shear Stress Waveform in Arteries

Introduction Ultrasound has been applied to measure vessel diameter and blood flow velocity to compute the wall shear rate (WSR) in arteries. This paper describes a fast technique to assess the WSR waveform using an image of a pulsed Doppler waveform downloaded from a modern clinical ultrasound scanner. Methods A walled vascular phantom has been developed to mimic the physiological condition of brachial arteries, from where measurements were made. A MATLAB program has been developed and used to compute the WSR waveform in a flow phantom from a pulsed Doppler image. The mean WSR obtained from the WSR waveform was compared with the mean WSR derived from the flow rate obtained from a timed collection method. Measurement errors in Doppler velocity estimates from ultrasound scanners were also investigated and used to determine correction factors in WSR calculations. Results For three different flow phantom depths, 9.5,14.5 and 19.5 mm, the mean percentage errors between the true and measured WSR were found to be 4.5% (SD = 4.0), 7.4% (SD = 5.1) and 14.2% (SD = 4.1) respectively. Conclusions The results demonstrated the feasibility of calculating WSR based solely on an image of the Doppler spectrum and arterial diameter measurement, which opens up the possibility of obtaining WSR estimates from generic scanners.

Lagrangian Point State Estimation with Optimized, Redundant Induction Coil Gauges

This research effort studies the use of redundant induction coil gauges to reduce state estimation uncertainties for moving Lagrangian points (LPs); e.g. discrete points, moving interfaces, projectiles, etc. The technique embeds a small, high-strength magnet at the LP and simultaneously tracks the magnet continuously with five (5) or more induction coils along a single axis of motion. A calibrated coil gauge model is presented as a function of LP position and velocity. The optimized LP state (position and velocity) estimate based upon redundant LP observations allows direct solution for LP velocity; requiring only one differentiation step to obtain acceleration. A specific experimental implementation (Particulate Materials Meso-scale Diagnostics system) is simulated to evaluate and minimize the expected state estimation errors. Induction coil signals with various levels of noise are simulated based upon a prescribed LP state variation with time. The state optimization algorithm attempts to recover the truth state values. Worst-case position estimation errors of ±0.3 mm and velocity estimation errors of ±0.46 m/s are determined for LPs travelling 0–1,000 m/s at realistic in-lab data noise levels.

Insect-inspired high-speed motion vision system for robot control

The mechanism for motion detection in a fly's vision system, known as the Reichardt correlator, suffers from a main shortcoming as a velocity estimator: low accuracy. To enable accurate velocity estimation, responses of the Reichardt correlator to image sequences are analyzed in this paper. An elaborated model with additional preprocessing modules is proposed. The relative error of velocity estimation is significantly reduced by establishing a real-time response-velocity lookup table based on the power spectrum analysis of the input signal. By exploiting the improved velocity estimation accuracy and the simple structure of the Reichardt correlator, a high-speed vision system of 1 kHz is designed and applied for robot yaw-angle control in real-time experiments. The experimental results demonstrate the potential and feasibility of applying insect-inspired motion detection to robot control.

INS/GPS for High-Dynamic UAV-Based Applications

The carrier-phase-derived delta pseudorange measurements are often used for velocity determination. However, it is a type of integrated measurements with errors strongly related to pseudorange errors at the start and end of the integration interval. Conventional methods circumvent these errors with approximations, which may lead to large velocity estimation errors in high-dynamic applications. In this paper, we employ the extra states to “remember” the pseudorange errors at the start point of the integration interval. Sequential processing is employed for reducing the processing load. Simulations are performed based on a field-collected UAV trajectory. Numerical results show that the correct handling of errors involved in the delta pseudorange measurements is critical for high-dynamic applications. Besides, sequential processing can update different types of measurements without degrading the system estimation accuracy, if certain conditions are met.

Inline Directionally Independent Peak Velocity Evaluation Reduces Error in Peak Antegrade Velocity Estimation in Patients Referred for Cardiac Valvular Assessment

The purpose of this article is to evaluate the utility of a tool in quantifying the peak antegrade velocity when assessing patients with cardiac valvular pathology. Directionally independent peak velocity evaluation (MaxVelocity, Siemens Healthcare) phase-contrast cardiac MRI was performed for 44 patients referred to our institution with a diagnosis or concern for aortic valvular disease or undergoing imaging for thoracic aortic aneurysm. In addition, standard through-plane phase-contrast MR angiography at the level of the aortic valve was performed. The MaxVelocity technique provides a simple tool to extract the magnitude of the peak velocity, independently of its direction, from phase-contrast imaging with velocity encoding. Recent echocardiography (within 1 month) and assessment of peak forward velocity at the level of the aortic valve were required for inclusion in the study. The MaxVelocity technique shows significantly lower error in estimating peak antegrade velocity at the level of the aortic valve than does standard unidirectional through-plane phase-contrast MRI, using transthoracic echocardiography as the reference noninvasive imaging method. Relative to standard through-plane imaging, MaxVelocity more closely approximates echocardiography for noninvasive assessment of peak antegrade velocity. Improved accuracy is critical for surgical decision making in patients with aortic valvular disease. Therefore, MaxVelocity provides an easy approach to quantify peak velocity as part of a routine clinical MRI protocol.

MICROWAVE CONTRAST IMAGING OF BREAST TISSUE FROM LOCAL VELOCITY ESTIMATION

This paper proposes a new method to display microwave images of breast tissue, based on estimation of local microwave velocity from time of ∞ight measurements. Its computational demands are low compared with tomography. It has two major components: 1) the estimation of the travel time of microwaves across the tissue between a set of antennae using a wavelet decomposition, and 2) the estimation of the microwave velocity fleld from the set of travel times using a low dimensional set of radial basis functions to model local velocity. The technique is evaluated in 2-D on clinical MR-based numerical breast phantoms incorporated in Finite-Difierence Time-Domain simulations. The basis functions, used with a regularisation scheme to improve numerical stability, reduce the dimensionality of the inverse problem for computational e-ciency and also to improve the robustness to error in velocity estimation. The results support previously published flndings that the wavelet transform is suitable for robust measurement of time of ∞ight even in clinically signiflcant simulations, and shows that the velocity contrast images can be constructed so difierent regions of breast tissue type can be distinguished. In particular, the presence of a tumour is clearly detected, demonstrating the potential of this approach for breast screening. Keywords: Biomedical signal processing; Microwave imaging; Image reconstruction.

Elliptical dip moveout for 3D seismic imaging in the presence of azimuthal anisotropy

Seismic images of the earth’s interior can be significantly distorted by complex wave propagation effects arising from 3D structural velocity variations, combined with the presence of azimuthal velocity anisotropy within some of the rock layers. Most image-processing techniques attempt to separate and compensate for both of these phenomena sequentially; they rarely address both simultaneously. These approaches implicitly assume that the effects of 3D structural velocity and azimuthal anisotropy are separable, whereas in fact, both effects are coupled together in the seismic data. In the presence of strong azimuthal velocity anisotropy, this can lead to significant errors in seismic velocity estimation and degraded quality of subsurface images, especially for large source-receiver offsets, wide azimuths, and steep geologic dips. Such imaging errors can greatly increase the uncertainty associated with exploring, characterizing, developing and monitoring subsurface geologic features for hydrocarbons, geothermal energy, [Formula: see text] sequestration, and other important geophysical imaging applications. Our approach simultaneously addressed velocity structure and azimuthal anisotropy by development of an elliptic dip moveout (DMO) operator. We combined the structural-velocity insensitivity of isotropic DMO with elliptic moveout representative of azimuthal velocity anisotropy. Forward and adjoint elliptical DMO operators were then cascaded together to form a single elliptical moveout (EMO) operation, which had a skewed saddle-like impulse response that resembles an isotropic azimuthal moveout operator. The EMO operator can be used as a prestack data conditioner, to estimate azimuthal anisotropy in a domain that is relatively insensitive to 3D velocity structure, or to compensate and map the data back to its original prestack domain in its approximately equivalent isotropic wavefield form. We demonstrated that EMO can reduce structural dip image errors of 10°–20° or more for realistic azimuthal velocity anisotropy values at far offsets.