Fluid Surface Velocity Estimation Using a 77 GHz Radar Module

Scherhäufl, Martin; Hesch, Clemens; Sevar, Jean-Marie

doi:10.1109/wisnet.2019.8711797

Cited by 10 publications

(5 citation statements)

References 4 publications

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“…The 2004 and 2006 experiments were carried-out with a current-meter over the entire cross-section while, the 2015 data, covers only half river section and is based on the desveloped doppler radar sensor. Eqn (12). with γ = 0.5 provides, in all the cases, a good approximation of the measured distributions.…”

mentioning

confidence: 61%

“…As it can be seen, the obtained data have an error within 3% and they can be used to estimate the velocity profile through eqn. (12).…”

Section: B Monte Molino Sitementioning

confidence: 99%

“…For the above motivations, it is important to use non-contact technologies for monitoring the velocity field, and thus the discharge, either with Surface Velocity Radars (SVR), [7]- [12], or using image-based techniques [13]- [16]. These methods have the advantage of avoiding danger for the operators, particularly in the presence of high flows [17].…”

Section: Introductionmentioning

confidence: 99%

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Noncontact Measurement of River Surface Velocity and Discharge Estimation With a Low-Cost Doppler Radar Sensor

Alimenti

Bonafoni

Gallo

et al. 2020

IEEE Trans. Geosci. Remote Sensing

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River discharge is an important variable to measure in order to predict droughts and flood occurrences. Once the cross-section geometry of the river is known, discharge can be inferred from water level and surface flow velocity measurements. Since river discharges are of particular interest during extreme weather events, when river sites cannot be safely accessed, noncontact sensing technologies are particularly appealing. To this purpose, the present work proposes a prototype of a low-cost Continuous Wave (CW) Doppler radar sensor, able to monitor the surface flow velocity of rivers. The prototype is tested at two gauged sites in central Italy, along the Tiber River. The surface flow velocity distribution across the river is monitored by means of the analysis of the received Doppler signal. The surface velocity statistics are then extracted using a novel algorithm that is optimized to run on a microprocessor platform with minimal computing power (ArduinoUNO). In particular, the radar measurements are used to initialize a 2D Entropy-based Velocity Model (EVM) that is able to estimate river discharges in any flow condition. Finally, the results concerning the observed discharge provided by the EVM prove to be comparable with those obtained with more expensive commercial solutions. The results are important since the described methodology can be extended to small-size Doppler radar sensors onboard Unmanned Aerial Vehicles (UAVs), the latter providing a method for mapping surface velocity of rivers.

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mentioning

confidence: 61%

“…As it can be seen, the obtained data have an error within 3% and they can be used to estimate the velocity profile through eqn. (12).…”

Section: B Monte Molino Sitementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Noncontact Measurement of River Surface Velocity and Discharge Estimation With a Low-Cost Doppler Radar Sensor

Alimenti

Bonafoni

Gallo

et al. 2020

IEEE Trans. Geosci. Remote Sensing

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“…Compared to other studies that have already been undertaken on the topic of detecting the surface velocity of rivers ( [19] or [20]) or the mapping of the surface velocity to the actual river flow velocity ( [18]), this article has shown new opportunities for the use of FMCW radar sensors for river characterisation. Especially the evaluation of range-Doppler plots and the time-averaged velocity distribution of the envelope velocity distribution based on integration of several range-Doppler frames provides a deep insight.…”

Section: Discussionmentioning

confidence: 99%

“…Regarding a flood warning system, the frequency-modulated continuous-wave (FMCW) radar offers the advantage of detecting the water surface level in addition to the surface velocity [19] compared to a Doppler radar. For a stationary mounted FMCW radar sensor, the obtained distance information indicates the surface level of the river taking into account the observation geometry.…”

Section: Introductionmentioning

confidence: 99%

River Surface Analysis and Characterization Using FMCW Radar

Mutschler

Scharf

Rippl

et al. 2022

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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Today's warning systems for floods or droughts require sensor applications that provide a vast array of information. Current systems provide insight into either the water level or the river velocity. In order to obtain additional parameters for the characterisation of the flow behaviour in a non-contact manner, a frequency modulated continuous wave (FMCW) Radar with chirp sequence is used. Since these sensors provide range and velocity information but also enable gathering of additional parameters. The presented measurements in this contribution were performed at four different rivers with a commercially available radar sensor. The results of the classical post-processed two-dimensional fast Fourier transform are used as basis for an image-wise processing approach to obtain additional features for classifying the behaviour of the river surface. For this purpose, the frame-wise enveloping velocities are depicted in a time sequence. Due to processing the detected reflection patterns in relation to time, a characteristic pattern for river flow profiles can be extracted. By reducing the information using time averaging, characteristic features for different flows can be extracted from the spatial envelope velocity distribution. In particular, the resulting insights lead to characteristic features for single flow distributions. That enables novel monitoring systems with new possibilities to classify rivers using radar sensors.

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