Methods for Velocity Measuring of Navigation Receivers

Automatic monitoring of hydrologic properties such as water velocity at short-time intervals is critical for understanding watershed eco-hydrological processes. This can also be used to study the laws of stream flows and interactions ecological process. The advent of modern electronic technology (and the near-perfection of especially sensor and data collection technologies), has made it possible to use automatic monitoring systems to continuously measure hydrologic properties at short-time intervals. This paper introduces one such paperless flow velocity measuring/recoding system. The system uses a photoelectric sensor that is mainly comprised of photoelectric velocity sensor and pulse recorder. The system uses propellers (with reflective panels and photoemission cells) to transform flow velocities into optical pulse signals. It also uses photosensitive tubes to transform optical pulse signals into electric pulse signals. The electric pulse counts (generated in unit time) are recorded via pulse recorders. This therefore accomplishes automatic monitoring and continuous recording of fluid flow velocity.

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Non-cooperative maritime target position and velocity measuring method based on monocular trajectory intersection for video satellite

Proceedings of the Institution of Mechanical Engineers Part G Journal of Aerospace Engineering ◽

10.1177/0954410017727023 ◽

2017 ◽

Vol 233 (1) ◽

pp. 44-56 ◽

Cited By ~ 1

Author(s):

Shengyi Chen ◽

Haibo Liu ◽

Xiaochun Liu ◽

Qifeng Yu

Keyword(s):

Target Position ◽

Measuring Method ◽

Observation Time ◽

Measuring Error ◽

Target Movement ◽

Practical Applications ◽

High Measurement ◽

Velocity Measuring ◽

Elevation Model ◽

Intersection Method

This paper presents a passive measuring method based on monocular trajectory intersection, aimed at realizing the position and velocity measurement of a non-cooperative maritime target for video satellite. Due to the fact that the target’s moving range is relatively small in comparison to that of the satellite during the observation time, a large measuring error results when directly using the monocular trajectory intersection method for 3D motion measurement. Therefore, the dynamic sea surface elevation model is employed to increase the maritime target movement constraints, which simplifies the 3D spatial motion of the target to 2D surface motion. By combining the surface constraint and monocular trajectory intersection method, measurement robustness for a non-cooperative maritime target can be greatly improved. Furthermore, a line-surface intersection method is proposed to obtain the initial solution for motion parameters, which increases the nonlinear optimization efficiency. Simulation experiments are conducted to analyze the effect of different error factors on position and velocity accuracy. The results indicate that the proposed method achieves high measurement accuracy and is feasible in practical applications for video satellite.

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Validation of Velocity Measuring Devices in Velocity Based Strength Training

International Journal of Computer Science in Sport ◽

10.2478/ijcss-2021-0007 ◽

2021 ◽

Vol 20 (1) ◽

pp. 106-118

Author(s):

Thorben Menrad ◽

Jürgen Edelmann-Nusser

Keyword(s):

Linear Regression ◽

Strength Training ◽

Mean Value ◽

Coefficient Of Determination ◽

Regression Analyses ◽

Measuring Devices ◽

Strength Exercises ◽

Measurement Units ◽

Velocity Measuring

Abstract To control and monitor strength training with a barbell various systems are on the consumer market. They provide the user with information regarding velocity, acceleration and trajectory of the barbell. Some systems additionally calculate the 1-repetition-maximum (1RM) of exercises and use it to suggest individual intensities for future training. Three systems were tested: GymAware, PUSH Band 2.0 and Vmaxpro. The GymAware system bases on linear position transducers, PUSH Band 2.0 and Vmaxpro base on inertial measurement units. The aim of this paper was to determine the accuracy of the three systems with regard to the determination of the average velocity of each repetition of three barbell strength exercises (squat, barbell rowing, deadlift). The velocity data of the three systems were compared to a Vicon system using linear regression analyses and Bland-Altman-diagrams. In the linear regression analyses the smallest coefficient of determination (R2.) in each exercise can be observed for PUSH Band 2.0. In the Bland-Altman diagrams the mean value of the differences in the average velocities is near zero for all systems and all exercises. PUSH Band 2.0 has the largest differences between the Limits of Agreement. For GymAware and Vmaxpro these differences are comparable.

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