Highly Accurate Time-of-Flight Measurement Technique Based on Phase-Correlation for Ultrasonic Ranging

Khyam, Mohammad Omar; Ge, Shuzhi Sam; Li, Xinde; Pickering, Mark

doi:10.1109/jsen.2016.2631244

Cited by 68 publications

(41 citation statements)

References 38 publications

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“…In recent years, it has been used in absolute distance measurement in laser ranging [21,22]. Methods with similar theoretical bases are also used in ultrasonic ranging and thickness detection [23,24]. Cross-correlation methods are helpful for improving the accuracy and resolution to the phase level.…”

Section: Introductionmentioning

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: Introductionmentioning

confidence: 99%

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

et al. 2019

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“…The traditional POC (phase correlation) technology can only estimate the parameters of pixel level precision, and its registration accuracy needs to be improved. In this paper, an Enhanced Phase Only Correlation (EPOC) method based on frequency domain local sampling Fourier transform is proposed, which can accurately process image correspondence [13]. EPOC constructs a matrix based up sampling transform in the local region around the peak of pixel level accuracy of phase correlation spectrum, and obtains robust, efficient and accurate sub-pixel estimation parameters.…”

Section: Image Correspondence Methodsmentioning

confidence: 99%

Discussion on Robot Embedded Positioning System Based on Image Correspondence Algorithm

2018

IJOMAM

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In order to overcome difficulties in a structured environment and make image correspondence more efficient in image correspondence, and to realize a more robust, precise and efficient correspondence results that are suitable for complex scenes, Hough spectrum characterization and image contour is presented in the discussion. It is a novel and robust approach and it proves the features of Hough spectrum: translation, rotation zoom, and cycle; based on Fourier domain phase related algorithm, an efficient and robust sampling Fourier image correspondence is proposed; at the same time, estimate method based on monocular vision of motion robot is proposed in terms of the application of image correspondence in the motion estimation and positioning system. The experimental results show that this method is able to estimate the motion parameters with high precision, and eventually works out a reliable estimation of robot trajectory.

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“…Thus, each sensor cannot distinguish the reflected wave from others. M. O. Khyam et al [8] applied a chirp signal to ultrasonic ranging. However, there is only one chirp pattern, and it cannot be used for indoor ranging systems that need to distinguish multiple sensors.…”

Section: Related Workmentioning

confidence: 99%

An Ultrasonic Object Detection Applying the ID Based on Spread Spectrum Technique for a Vehicle

Jin

Kim

et al. 2020

Sensors

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When an ultrasonic sensor generates an ultrasonic wave and detects an obstacle from a reflected wave, a signal transmitted by other ultrasonic sensors would be interference. In this paper, to overcome the interference, a transducer transmits a signal with a unique ID modulated. The interference is ignored by verifying that the reflected signal includes its ID. The ID verification process uses a correlation between the received signal and the ID. Therefore, the ID is selected from orthogonal codes with good cross-correlation. Long code has the advantage of being more robust to interference. However, the reflected wave from nearby obstacles might return before the transmission ends. Therefore, the 7-bit Barker code is applied for near obstacle detection and a 31-bit Gold code is used for distant obstacle detection. The modulation technique is DQPSK, which is available in a narrow bandwidth and has a simple receiver structure. In ID recognition based on correlation, a near–far problem occurs due to a large amplitude difference between the received wave and interference. The addition of a zero-crossing detector solves this problem. The hardware is implemented based on the algorithm proposed in this paper. The simulation showed a detection rate of at least 90% and the the result of the real measurement represented a detection rate of 97.3% at 0.5 m and 94.5% at 2 m.

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Highly Accurate Time-of-Flight Measurement Technique Based on Phase-Correlation for Ultrasonic Ranging

Cited by 68 publications

References 38 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

Discussion on Robot Embedded Positioning System Based on Image Correspondence Algorithm

An Ultrasonic Object Detection Applying the ID Based on Spread Spectrum Technique for a Vehicle

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