Measuring uncertainty of ultrasonic longitudinal phase velocity estimation using different time-delay estimation methods based on cross-correlation: Computational simulation and experiments

Costa‐Júnior, José Francisco Silva; Cortela, Guillermo; Maggi, Luis Eduardo; Rocha, Tiago F.D.; Pereira, Wagner Coelho de Albuquerque; Costa-Félix, Rodrigo Pereira Barretto da; Alvarenga, André Victor

doi:10.1016/j.measurement.2018.01.073

Cited by 39 publications

(17 citation statements)

References 37 publications

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“…In this experiment, the sampling rate is 1 GHz, and we interpolate it to 2.5 GHz using linear interpolation. Interpolation is commonly used in cross-correlation calculations to improve the measurement resolution, without affecting the accuracy [43,44]. The time resolution is 0.4 ns, in theory.…”

Section: Tof By the Cross-correlation Methodsmentioning

confidence: 99%

A High-Resolution Ultrasonic Ranging System Using Laser Sensing and a Cross-Correlation Method

et al. 2019

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Ultrasound has been proven to be a valid tool for ranging, especially in water. In this paper, we design a high-resolution ultrasonic ranging system that uses a thin laser beam as an ultrasonic sensor. The laser sensing provides a noncontact method for ultrasound detection based on acousto-optic diffraction. Unlike conventional methods, the ultrasound transmitted from the transducer is recorded as the reference signal when it first passes through the laser. It can be used to improve the accuracy and resolution of the time-of-flight (TOF) by a cross-correlation method. Transducers with a central frequency of 1 MHz and diameters of 20 mm and 28 mm are used in the experiment. Five targets and a test piece are used to evaluate the ranging performance. The sound velocity is measured by the sound velocity profiler (SVP). The repeatability error of TOF is less than 4 ns, and the theoretical resolution of TOF is 0.4 ns. The results show a measurement resolution within one-tenth of the wavelength of ultrasound and an accuracy better than 0.3 mm for targets at a distance up to 0.8 m. The proposed system has potential applications in underwater ranging and thickness detection.

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Section: Tof By the Cross-correlation Methodsmentioning

confidence: 99%

A High-Resolution Ultrasonic Ranging System Using Laser Sensing and a Cross-Correlation Method

et al. 2019

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“…GRF and inertial readings were time-aligned prior to each recording (maximum 30 s each) by determining the delay corresponding to the peak of the cross-correlation function among the vertical force and vertical acceleration signals at the beginning of the recording ( Figure 3 ). The maximum synchronization error when dealing with cross correlation algorithms is typically lower than 1 sampling period [ 31 ]. In our case this is 10 ms, thus entailing a standard uncertainty lower than 3 ms.…”

Section: Methodsmentioning

confidence: 99%

Machine-Learning Based Determination of Gait Events from Foot-Mounted Inertial Units

Zago

Tarabini

Spiga

et al. 2021

Sensors

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A promising but still scarcely explored strategy for the estimation of gait parameters based on inertial sensors involves the adoption of machine learning techniques. However, existing approaches are reliable only for specific conditions, inertial measurements unit (IMU) placement on the body, protocols, or when combined with additional devices. In this paper, we tested an alternative gait-events estimation approach which is fully data-driven and does not rely on a priori models or assumptions. High-frequency (512 Hz) data from a commercial inertial unit were recorded during 500 steps performed by 40 healthy participants. Sensors’ readings were synchronized with a reference ground reaction force system to determine initial/terminal contacts. Then, we extracted a set of features from windowed data labeled according to the reference. Two gray-box approaches were evaluated: (1) classifiers (decision trees) returning the presence of a gait event in each time window and (2) a classifier discriminating between stance and swing phases. Both outputs were submitted to a deterministic algorithm correcting spurious clusters of predictions. The stance vs. swing approach estimated the stride time duration with an average error lower than 20 ms and confidence bounds between ±50 ms. These figures are suitable to detect clinically meaningful differences across different populations.

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“…OF measurements can be challenging when it comes to measuring the time elapse between two fast signals at speeds greater than 10m/s. One of the most widely used methods here is the classical normalized cross-correlation (NCC) method [9,2,8,1,11]. A reference window is defined on the first signal and compared with windows in the second signal delayed by a fixed time lag: a cross-correlation coefficient is then determined between the two windows.…”

Section: Introductionmentioning

confidence: 99%

“…Because of this disadvantage, the pulse counting method is still mainly used in small embedded optic flow sensors although it gives less accurate results. Some authors such as [1,11,24,12] have presented faster methods of calculation for finding maximum correlations. The method proposed by the latter authors [1,12] consists of interpolating the cross-correlation curve with a parabolic interpolation or a SINC function.…”

Section: Introductionmentioning

confidence: 99%

“…Some authors such as [1,11,24,12] have presented faster methods of calculation for finding maximum correlations. The method proposed by the latter authors [1,12] consists of interpolating the cross-correlation curve with a parabolic interpolation or a SINC function. A maximum correlation can be obtained by calculating only three correlations and extrapolating the maximum correlation from them.…”

Section: Introductionmentioning

confidence: 99%

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Fast normalized cross-correlation for measuring distance to objects using optic flow, applied for helicopter obstacle detection

Viel

Viollet

2021

Measurement

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The fast normalized cross-correlation (NCC) calculation method presented here features low computational requirements, which makes it suitable for being implemented in real time onboard micro-controllers with very few computational resources. This method was adapted for making distance measurements, using a high speed optic flow sensor operating at 20m/s. An application of this study is to develop a proof of concept of an innovative optic flow sensor fixed at the tip of an helicopter's blade (from Airbus Helicopter) to measure the distance to various obstacles (wall, cliff...) in the azimuthal plane (rotor plane) during hovering flight. Due to its small size, this sensor developed in this paper can also be also adapted for Micro aerial vehicles (MAVs). This method of calculation requires less memory than the reference method, at the expense of some extra arithmetical operations, but it is still significantly lighter than the classical NCC method. An algorithm for implementing this method in real-time robotic applications is presented. Experimental results confirm the efficiency of this highly time-saving method.

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Measuring uncertainty of ultrasonic longitudinal phase velocity estimation using different time-delay estimation methods based on cross-correlation: Computational simulation and experiments

Cited by 39 publications

References 37 publications

A High-Resolution Ultrasonic Ranging System Using Laser Sensing and a Cross-Correlation Method

A High-Resolution Ultrasonic Ranging System Using Laser Sensing and a Cross-Correlation Method

Machine-Learning Based Determination of Gait Events from Foot-Mounted Inertial Units

Fast normalized cross-correlation for measuring distance to objects using optic flow, applied for helicopter obstacle detection

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