Optimizing High Precision RTK/PPK GNSS Algorithms Using Real-World Data

Lacambre, Jean-Baptiste; Barford, Tim; Oudart, Nicolas; Lieffering, Patrick; Morvant, Guirec; Guyot, Benoît

doi:10.33012/2022.18500

Cited by 7 publications

(1 citation statement)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The Doppler radar is a continuous wave (CW) radar with a K-band frequency at 24.125 GHz, which lies in the microwave spectrum. The radar emits microwaves with (Lacambre et al, 2022). PPK processing was carried out using the freeware Emlid Studio 1.6 (Eker et al, 2022;Tamimi & Toth, 2023).…”

Section: Doppler Radar Deployment and Interpretation Of Doppler Spectramentioning

confidence: 99%

Measuring river surface velocity using UAS-borne Doppler radar

Zhou,

Riis-Klinkvort,

Jørgensen

et al. 2024

Preprint

View full text Add to dashboard Cite

Using Unmanned Aerial Systems (UAS) equipped with optical RGB cameras and Doppler radar, surface velocity can be efficiently measured at high spatial resolution. UAS-borne Doppler radar is particularly attractive because it is suitable for real-time velocity determination, because the measurement is contactless, and because it has fewer limitations than image velocimetry techniques. In this paper, five cross-sections (XSs) were surveyed within a 10 km stretch of Rönne Å in Sweden. Ground-truth surface velocity observations were retrieved with an electromagnetic velocity sensor (OTT MF Pro) along the XS at 1 m spacing. Videos from a UAS RGB camera were analyzed using both Particle Image Velocimetry (PIV) and Space-Time Image Velocimetry (STIV) techniques. Furthermore, we recorded full waveform signal data using a Doppler radar at multiple waypoints across the river. An algorithm fits two alternative models to the average amplitude curve to derive the correct river surface velocity: a Gaussian one peak model, or a Gaussian two peak model. Results indicate that river flow velocity and propwash velocity caused by the drone can be found in XS where the flow velocity is low, while the drone-induced propwash velocity can be neglected in fast and highly turbulent flows. To verify the river flow velocity derived from Doppler radar, a mean PIV value within the footprint of the Doppler radar at each waypoint was calculated. Finally, quantitative comparisons of OTT MF Pro data with STIV, mean PIV and Doppler radar revealed that UAS-borne Doppler radar could reliably measure the river surface velocity.

show abstract

Section: Doppler Radar Deployment and Interpretation Of Doppler Spectramentioning

confidence: 99%

Measuring river surface velocity using UAS-borne Doppler radar

Zhou,

Riis-Klinkvort,

Jørgensen

et al. 2024

Preprint

View full text Add to dashboard Cite

show abstract

Measuring River Surface Velocity Using UAS‐Borne Doppler Radar

Zhou,

Riis‐Klinkvort,

Jørgensen

et al. 2024

Water Resources Research

View full text Add to dashboard Cite

Using Unoccupied Aerial Systems (UAS) equipped with optical RGB cameras and Doppler radar, surface velocity can be efficiently measured at high spatial resolution. UAS‐borne Doppler radar is particularly attractive because it is suitable for real‐time velocity determination, because the measurement is contactless, and because it has fewer limitations than image velocimetry techniques. In this paper, five cross‐sections (XSs) were surveyed within a 10 km stretch of Rönne River in Sweden. Ground‐truth surface velocity observations were retrieved with an electromagnetic velocity sensor (OTT MF Pro) along the XS at one m spacing. Videos from a UAS RGB camera were analyzed using both Particle Image Velocimetry (PIV) and Space‐Time Image Velocimetry (STIV) techniques. Furthermore, we recorded full waveform signal data using a Doppler radar at multiple waypoints across the river. An algorithm fits two alternative models to the average amplitude curve to derive the correct river surface velocity based on Gaussian models with: (a) one peak, and (b) two peaks. Results indicate that river flow velocity and propwash velocity caused by the drone can be found in XS where the flow velocity is low, while the drone‐induced propwash velocity can be neglected in fast and highly turbulent flows. To verify the river flow velocity derived from Doppler radar, a mean PIV value within the footprint of the Doppler radar at each waypoint was calculated. Finally, quantitative comparisons of OTT MF Pro data with STIV, mean PIV and Doppler radar revealed that UAS‐borne Doppler radar could reliably measure the river surface velocity.

show abstract