Measurement Of Motion Parameters Research Articles

Channel error of the air motion parameters measurement system for aircraft with an integrated fuselage flow receiver

Channel error of the air motion parameters measurement system for aircraft with an integrated fuselage flow receiver

An Image Distortion Correction Method Based on Distortion Centre and Parameter Estimation

Abstract We propose a radial distortion correction method based on straight-line feature calibration to address the challenge of image radial distortion when measuring mechanical motion parameters using computer vision technology. This method first independently estimates the distortion center, and then transforms the distortion parameter estimation into an arc fitting problem. The least squares optimization algorithm is applied to quickly and accurately estimate the arc parameter of distorted lines, ultimately achieving precise correction of distortion in wide-angle camera images. This method can reduce lens distortion by 89% to 92%, laying a solid foundation for the application of computer vision technology in the field of mechanical motion parameter measurement.

High-performance motion parameter measurement based on optical phase locking and multi-signal combination

High-performance motion parameter measurement based on optical phase locking and multi-signal combination

Surrogate Modelling for Oxygen Uptake Prediction Using LSTM Neural Network.

Oxygen uptake (V˙O2) is an important metric in any exercise test including walking and running. It can be measured using portable spirometers or metabolic analyzers. Those devices are, however, not suitable for constant use by consumers due to their costs, difficulty of operation and their intervening in the physical integrity of their users. Therefore, it is important to develop approaches for the indirect estimation of V˙O2-based measurements of motion parameters, heart rate data and application-specific measurements from consumer-grade sensors. Typically, these approaches are based on linear regression models or neural networks. This study investigates how motion data contribute to V˙O2 estimation accuracy during unconstrained running and walking. The results suggest that a long short term memory (LSTM) neural network can predict oxygen consumption with an accuracy of 2.49 mL/min/kg (95% limits of agreement) based only on speed, speed change, cadence and vertical oscillation measurements from an inertial navigation system combined with a Global Positioning System (INS/GPS) device developed by our group, worn on the torso. Combining motion data and heart rate data can significantly improve the V˙O2 estimation resulting in approximately 1.7-1.9 times smaller prediction errors than using only motion or heart rate data.

A lightweight model for blade tip image enhancement in helicopter rotor motion parameter measurement system

The helicopter rotor torsion angle is an important motion parameter of a helicopter rotor, which is helpful for the design of helicopter rotor system. The stereoscopic vision-based method measures the torsion angle by computing the directions of the blade tips in the blade tip images. However, the captured blade tip images suffer from blurring and underexposure, which affect the measurement accuracy. To this end, a lightweight deep model is proposed to improve the image quality. In addition, a blade tip image dataset is proposed to train the network. Corresponding experiments demonstrate the effectiveness of the proposed model. Compared to competitive methods, our model stands out with fewer parameters and faster inference time.

Modified method of invariant immersion in the synthesis of measuring procedures for estimating the motion parameters of a maneuvering target

The problem of processing the results of radar measurements of the target motion parameters under conditions of disturbances due to aircraft maneuvers is considered. In order to adapt to the disturbances of measuring procedures, the method of invariant immersion has been modified. The application of the modified method in the case of a linear observation equation leads to a widespread form of a discrete measurement procedure obtained in this paper as a special case of modified invariant immersion equations. On the basis of statistical modeling of digital processing of the results of radar measurements of the movement parameters of the maneuvering target, the efficiency indicators of radar stations are calculated – these are the averaged absolute and relative errors in the measurement of motion parameters, the averaged wiring coefficient and the averaged time of the duration of the breaks of the tracks. Their analysis allows us to assert the high efficiency of using new measuring procedures synthesized using acceleration models in the form of white noise and Singer in the information and measurement systems of radar stations. This becomes possible due to the presence of the matrix coefficient of adaptation in the structure of the modified equations of invariant immersion. The comparison was carried out with Kalman measurement procedures synthesized using these acceleration models. Calculations of performance indicators confirm the reliability of the results obtained, since the wellknown fact of an increase in the error of measuring the height of an aircraft by monopulse radar stations near the surface is demonstrated. The results of the study will be useful in the development of adaptive measurement procedures for information and measurement systems operating under conditions of disturbances of measuring processes, for example, for survey locators.

Automatic Vessel Steering in a Storm

Abstract The issues of automatic vessel control in a storm are considered in the paper. Vessel control in a storm is the most difficult stage in the vessel’s wiring, as it requires quick decisions to be made in difficult conditions. Practical experience shows that the deterioration of the working conditions of the crew is usually associated with an increase in the number of control errors, which is completely unacceptable in stormy conditions. To assess the safe speed and course in a storm, Yu. V. Remez has proposed a universal storm diagram, which allows identifying unfavourable combinations of vessel speed and course angles of the waves – the resonant zones, and avoid them. The universal Remez diagram provides for graphical calculations, which, in combination with the visual determination of the wave parameters, gives a very low accuracy. The article examines the possibility of automatic control of a vessel in a storm by automatic measurement of motion parameters and wave parameters, automatic calculation in the onboard controller of the vessel optimal safe speed and course during a storm, automatic maintenance of the optimal safe speed and course of the vessel. The automatic control significantly increases the accuracy of calculations, excludes the human factor, reduces the depletion of the crew, and increases the reliability of the vessel control in a storm. The efficiency and effectiveness of the method, algorithmic and software were tested on Imitation Modelling Stand in a closed loop with mathematical vessel models of the navigation simulator Navi Trainer 5000.

Multi-input adaptive neural network for automatic detection of cervical vertebral landmarks on X-rays

Cervical vertebral landmark detection is a significant pre-task for vertebral relative motion parameter measurement, which is helpful for doctors to diagnose cervical spine diseases. Accurate cervical vertebral landmark detection could provide reliable motion parameter measurement results. However, different cervical spines in X-rays with various poses and angles have imposed quite challenges. It is observed that there are similar appearances of vertebral bones in different cervical spine X-rays. For this, to fully use these similar features, a multi-input adaptive U-Net (MultiIA-UNet) focusing on the similar local features between different cervical spine X-rays is put forward to do cervical vertebral landmark detection accurately and effectively. MultiIA-UNet used an improved U-Net structure as backbone network combining with the novel adaptive convolution module to better extract changing global features. At training, MultiIA-UNet applied a multi-input strategy to extract features from random pairs of training data at the same time, and then learned their similar local features through a subspace alignment module. We collected a dataset including 688 cervical spine X-rays to evaluate MultiIA-UNet. The results exhibited that our method demonstrated the state-of-the-art performance (the minimum average point to point error of 12.988 pixels). In addition, we further evaluated the effect of these landmark detection results on cervical motion angle parameter measurement. It showed that our method was capable to obtain more accurate cervical spine motion angle parameters (the minimum symmetric mean absolute percentage is 26.969%). MultiIA-UNet could be an efficient and accurate landmark detection method for doctors to do cervical vertebral motion analysis.

Motion parameters measurement of user-defined key points using 3D pose estimation

Motion parameters measurement is essential for understanding animal behavior, exploring the laws of object motion, and studying control methods. Nowadays, advanced computer vision based on machine learning technology supports markerless object tracking in 2D videos. However, due to the fact that all objects move in three-dimensional space, this paper introduces a method of measuring motion parameters using 3D pose estimation. First, an enhanced iterative bundle adjustment algorithm is proposed for multi-camera calibration in a multi-camera vision system by adding two control parameters, which dramatically reduces the reprojection error of multi-camera calibration and lays the foundation for high-precision triangulation. Then, a new spatiotemporal loss function is proposed, which considers the relationship between key points that do not constitute limbs, thereby improving triangulation accuracy. The new multi-camera calibration algorithm is evaluated on ChArUco and 3D pose estimation for metronome, planet pendulum, human hand, Koi, and cheetah. The experimental results show that: (1) the two hyper-parameters in the enhanced iterative bundle adjustment algorithm effectively suppress the influence of noise and play a good role in reducing the reprojection error of multi-camera calibration; (2) the spatiotemporal loss function has a strong constraining ability, the time loss can stabilize high frame rate video triangulation to maintain accuracy, while the space loss can improve the accuracy of triangulation for more complex structures; (3) multi-view data fusion is also conducive to improving the accuracy of triangulation. Moreover, the method was successfully applied to some actual measurement scenes: (1) the accurate measurement of the frequency of a metronome; and (2) the success measurement of the movement of a Koi, which conforms to the basic model of fish swimming. Some dynamic measurement results are displayed at https://github.com/wux024/AdamPose.

Enhanced Disturbance Suppression Method Based on NonlinearH∞Filtering for Distributed POS in Aerial Earth Observation Imaging Application

Multinode remote sensing imaging loads have long been a fascinating focus of aerial earth observation applications, where the load denotes the device or equipment located on the aircraft for a specific task, such as aerial camera, scanning laser, and synthetic aperture radar. In order to guarantee high-quality imaging, distributed position and orientation system (POS) serves as high accuracy spatio-temporal reference information for remote sensing loads to realize motion compensation. As a result of the working environment, the flexible structure of the wing will suffer the external disturbance, then for distributed POS, the lever arm between the master system below the abdomen and slave system under the wing is time-varying, also the noise disturbance influences markedly on the motion parameters measurement accuracy. Then aiming at the transfer alignment accuracy improvement of distributed POS, a central difference <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$H_{\infty }$ </tex-math></inline-formula> filtering algorithm is proposed, which adopts the central difference Kalman filtering to realize nonlinear state estimation and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$H_\infty $ </tex-math></inline-formula> filtering to suppress the disturbance influence on estimation, then the high accuracy motion parameters can be obtained. The flight test results show that the developed algorithm can effectively deal with the disturbance influence on transfer alignment estimation and enhance the parameter estimation accuracy, which can be used in aerial earth observation imaging.

Devising a method for measuring the motion parameters of industrial equipment in the quarry using adaptive parameters of a video sequence

The method and structural scheme of an information-measuring system for determining the parameters of objects' movements (technological equipment in the quarry for extracting block natural stone) have been proposed. A distinctive feature of time video sequences containing images of measured objects is their adaptation and adjustment in accordance with the intensity of movement and accuracy requirements for measurement results. Structural and software-algorithmic methods were also applied for improving the accuracy of measurements of motion parameters, namely: complexation of two measuring channels and exponential smoothing of digital references. One of the measuring channels is based on a digital video camera, the second is based on an accelerometer mounted on an object and two integrators. Exponential smoothing makes it possible to take into consideration the previous countdowns of movement parameters with weight coefficients. That ensures accounting for the existing patterns of movement of the object and reducing the errors when measuring the parameters of movement by (1.4...1.6) times. The resulting solutions have been implemented in the form of an information and measurement system. The technological process of extracting blocks of natural stone in the quarry was experimentally investigated using a diamond-rope installation. Based on the contactless measurement of motion parameters, it is possible to ensure control over this process and improve the quality of blocks made of natural stone. Based on the experimental study of measurement errors, recommendations were given for the selection of adaptive parameters of a video sequence, namely the size of images and the value of the inter-frame interval. In addition, methods for the software-algorithmic processing of measuring information were selected, specifically exponential smoothing and averaging the coordinates of the contour of an object, measured in 30 adjacent lines of the image

Research on Measurement Method of Parachute Scanning Platform Based on MEMS Device.

This paper studies the measurement of motion parameters of a parachute scanning platform. The movement of a parachute scanning platform has fast rotational velocity and a complex attitude. Therefore, traditional measurement methods cannot measure the motion parameters accurately, and thus fail to satisfy the requirements for the measurement of parachute scanning platform motion parameters. In order to solve these problems, a method for measuring the motion parameters of a parachute scanning platform based on a combination of magnetic and inertial sensors is proposed in this paper. First, scanning motion characteristics of a parachute-terminal-sensitive projectile are analyzed. Next, a high-precision parachute scanning platform attitude measurement device is designed to obtain the data of magnetic and inertial sensors. Then the extended Kalman filter is used to filter and observe errors. The scanning angle, the scanning angle velocity, the falling velocity, and the 2D scanning attitude are obtained. Finally, the accuracy and feasibility of the algorithm are analyzed and validated by MATLAB simulation, semi-physical simulation, and airdrop experiments. The presented research results can provide helpful references for the design and analysis of parachute scanning platforms, which can reduce development time and cost.

A measurement method of motion parameters in aircraft ground tests using computer vision

The purpose of this work is aiming at the problem of high precision and large-scale measurement of motion parameters of aircraft ground test. Based on the traditional vision measurement method of motion parameters, a new measurement method of motion parameters based on intersected planes is discussed. Firstly, the measurement of 3D coordinates of laser spots was performed using the 3 D vision technique combined with plane constraints of curtain wall, the images of laser spot projected on the parallel curtain wall were processed using the centroid method, the calibration of multi-coordinates were unified by the unique coordinate system method, then the pose was solved using the proposed method that the normal vector of the intersect plane fixed on the vehicle is used. Finally, according to the measurement principle, the influence of spot center positioning, camera parameter calibration and target geometric error on the calculation results of aircraft motion parameters is analyzed, and the error propagation model is given. The experimental results show that in the measurement range of 8000 mm × 4000 mm × 4000 mm, the measurement error of attitude parameters is less than 0.14°, and the measurement error of position parameters is less than 2 mm. Compared with binocular stereo vision, the accuracy of attitude angle measurement is improved by 100%. Therefore, the measurement method proposed in this paper can achieve high precision and large-scale measurement of the motion parameters of the test aircraft.

Performance Evaluation of Deception Against Synthetic Aperture Radar Based on Multifeature Fusion

Deception is an effective means of jamming against synthetic aperture radar (SAR). The performance of deceptive jamming is affected by the accuracy of parameter measurement and the applied antijamming methods of SAR. In this article, we analyze the accuracy of current deceptive jamming evaluation indicators, propose a new method for evaluating the performance of deceptive jamming based on the combination of typical dominant deceptive jamming evaluation indicators, and recessive indicators extracted by convolutional neural networks, and obtain a level of deceptive jamming using a softmax activation function in a fully connected network. Deceptive jamming images affected by the SAR motion parameter measurement error are taken as training and test sets. Finally, the moving and stationary target acquisition and recognition database is used as a deceptive jamming template in order to verify the effectiveness of the proposed method.

Model Optimization and Calculation Method of Multi-Target Curved Motion Parameters Measurement Using Multi-Screen Intersection Test Mechanism

The parameters calculation model of a six-screen intersection with linear motion is used to test the projectile explosion location parameter under the condition of long-range artillery firing, which brings a significant test error, the main reason for the error is that the projectile has its own gravity during the flight, it makes the flight path of the projectile is a curved trajectory. To improve the test accuracy, this paper uses the projectile particle motion equation and six-screen intersection geometry relationship and considers the impact of the projectile's gravity acceleration and air resistance; it studies a calculation model and method of relative location for projectile proximity explosion under the spatial projectile curved motion. Then, it analyzes the error reason for calculating relative coordinate of projectile passing through the detection screen interval by using six-screen intersection test method based on linear motion. By introducing the gravitational acceleration and air resistance during the projectile flight process, establishes the variable trajectory parameters calculation model for a projectile with the curved motion passing through a six-screen intersection test system. Through the high-altitude projectile proximity explosion location test, this paper uses the method of the ballistic lateral camera to obtain the experimental data of projectile explosion location parameter. It compares the experimental data by using the six-screen intersection test method with linear motion and curved motion. The results show that the calculation model based on the curved motion model is closer to actual coordinate data of the projectile proximity explosion location.

Measurement of motion parameters of low-altitude flying vehicles near the sea surface

Abstract Increased accuracy requirements are imposed to the systems for measuring the motion parameters of low-altitude flying vehicles. Even a small error in estimating the motion parameter can lead to an accident. Sea wave adds a wave component to the meter error. The paper suggests an architecture of the system for measuring the height of a low-altitude flying vehicles and the carries out the complexation of measuring devices, reducing the influence of the wave component of the error.

A transfer alignment method for airborne distributed POS with three-dimensional aircraft flexure angles

An airborne distributed position and orientation system (POS) appears to satisfy the requirement of multi-point motion parameters measurement. This relies on transfer alignment from a high precision master system to slave systems to obtain high accuracy motion parameters of all points. A key problem for a distributed POS involves determining a method to treat the aircraft flexure appropriately and achieve high precision transfer alignment. In this study, the effect of aircraft flexure on transfer alignment accuracy for airborne earth observation is first analyzed. Based on this, the error model of transfer alignment that considers three-dimensional flexure angles are established, and a transfer alignment based on parameter identification unscented Rauch-Tung-Striebel smoother (PIURTSS) is proposed. The simulations results show that the transfer alignment method based on PIURTSS effectively improves the estimation accuracy.

Method for Measurement of Multi-Degrees-of-Freedom Motion Parameters Based on Polydimethylsiloxane Cross-Coupling Diffraction Gratings

This work presents a multi-degrees-of-freedom motion parameter measurement method based on the use of cross-coupling diffraction gratings that were prepared on the two sides of a polydimethylsiloxane (PDMS) substrate using oxygen plasma processing technology. The laser beam that travels pass the cross-coupling optical grating would be diffracted into a two-dimensional spot array. The displacement and the gap size of the spot-array were functions of the movement of the laser source, as explained by the Fraunhofer diffraction effect. A 480 × 640 pixel charge-coupled device (CCD) was used to acquire images of the two-dimensional spot-array in real time. A proposed algorithm was then used to obtain the motion parameters. Using this method and the CCD described above, the resolutions of the displacement and the deflection angle were 0.18 μm and 0.0075 rad, respectively. Additionally, a CCD with a higher pixel count could improve the resolutions of the displacement and the deflection angle to sub-nanometer and micro-radian scales, respectively. Finally, the dynamic positions of hovering rotorcraft have been tracked and checked using the proposed method, which can be used to correct the craft’s position and provide a method for aircraft stabilization in the sky.

Fabrication of a cost-effective MEMS-based piezoresistive cantilever sensor for gait movement analysis

Gait analysis measurement is a method to access and identify gait events and the measurements of motion parameters involving the lower part of body. This significant method is widely used in rehabilitation, sports as well as health diagnostic towards improving the quality of life. However, it is not routine practice due to costs involved in creating and using gait labs. Alternatively, inertial sensors such as micro cantilever accelerometer can be used in the development of cheap and wearable gait analysis systems. Human stride segmentation measurement based on micro-accelerometer cantilever is used in the study of the lower limb movement patterns that include walk, jump and run; and the measurements of the motion parameters. A complete system consists of a fabricated sensor, a Wheatstone bridge circuit and a signal amplifier tailored for real-time stride analysis measurement is proposed. The novel fabrication method of an accelerometer sensor using laser micromachining is introduced in order to develop a simple way in realizing the sensor formation. This study allows us to optimize the requirements of hard-mask and fabrication process steps by reduction of 30% and 25% respectively. In the general framework, this research activity is focused towards development of piezoresistive cantilever formation using laser micromachining for fast fabrication development for real life gait and stride segmentation measurement application.

Absolute ballistic gravimeters

Operating principle of modern ballistic gravimeters is based on the measurement of motion parameters of a macroscopic test body or a cloud of cold atoms in the gravity field and calculation of free-fall acceleration using the measured motion parameters from the test body motion equation. There are about 200 transportable ballistic gravimeters in the world, the best of which feature uncertainty of a few units of 10−8 ms−2. Metrological assurance system for absolute gravimeters is being developed. Improvements in absolute gravimeters will allow their use on moving platforms.