3rd Place Winner: 2022 Smartphone Decimeter Challenge: An RTKLIB Open-Source Based Solution

Everett, Tim

doi:10.33012/2022.18376

Cited by 10 publications

(2 citation statements)

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“…In both cases, all available constellations were used (GPS, Galileo, GLONASS, Beidou) together with final precise GNSS products and a 15 deg elevation mask. (Everett, 2022a), but has generally been more usable and reliable than the standard version in our testing. However, without ambiguity resolution, PPP is expected to be less accurate compared to the results from Gurturk et al (2022).…”

Section: Processing Methodologymentioning

confidence: 91%

Evaluation of a GNSS/Imu/Lidar-Integration for Airborne Laser Scanning Using Rtklib PPK and PPP GNSS Solutions

Pöppl,

Mandlburger,

Pfeifer

2023

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. Airborne laser scanning allows for efficient acquisition of accurate 3D data for large areas. Because georeferencing of the LiDAR data requires knowledge of the platform trajectory, the laser scanner system commonly comprises a global navigation satellite system (GNSS) receiver/antenna and an inertial measurement unit (IMU). The standard processing pipeline consists of GNSS/IMU integration, georeferencing, and subsequent adjustment of the laser data. Here, we consider a holistic GNSS/IMU/LiDAR-integration approach based on least-squares adjustment. The GNSS is loosely coupled, and the GNSS positions are obtained using either postprocessing kinematic or precise point positioning GNSS processing strategies using the open-source software RTKLib. In this contribution, we compare the resulting point clouds to those of a standard processing workflow and evaluate the impact of the different processing strategies on point cloud quality in terms of internal consistency and absolute accuracy for a airborne laser bathymetry (ALB) dataset. Although the GNSS solutions themselves differ strongly, both the PPK- and the PPP-derived point clouds show better strip differences (below 2.5 cm) and similar absolute accuracy (<4 cm RMSE w.r.t. reference targets after correction of constant datum shift) compared to the reference solution.

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Section: Processing Methodologymentioning

confidence: 91%

Evaluation of a GNSS/Imu/Lidar-Integration for Airborne Laser Scanning Using Rtklib PPK and PPP GNSS Solutions

Pöppl,

Mandlburger,

Pfeifer

2023

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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“…The configuration file for the F9P solutions in this set was based on a configuration file included with this code that is optimized for the F9P receiver. The configuration file for the Pixel 5 solutions in this set were based on earlier work done with cellphone datasets for the 2021 and 2022 Google Smartphone Decimeter Challenges [ 19 , 48 ]. In both cases, the configuration files were further optimized based on specific environmental conditions of this data and with some iteration of solutions on a subset of the data.…”

Section: Methodsmentioning

confidence: 99%

Static Positioning under Tree Canopy Using Low-Cost GNSS Receivers and Adapted RTKLIB Software

Tomaštík

Everett²

2023

Sensors

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The decrease in costs and dimensions of GNSS receivers has enabled their adoption for a very wide range of users. Formerly mediocre positioning performance is benefiting from recent technology advances, namely the adoption of multi-constellation, multi-frequency receivers. In our study, we evaluate signal characteristics and horizontal accuracies achievable with two low-cost receivers—a Google Pixel 5 smartphone and a u-Blox ZED F9P standalone receiver. The considered conditions include open area with nearly optimal signal reception, but also locations with differing amounts of tree canopy. GNSS data were acquired using ten 20 min observations under leaf-on and leaf-off conditions. Post-processing in static mode was conducted using the Demo5 fork of the RTKLIB open source software, which is adapted for usage with lower quality measurement data. The F9P receiver provided consistent results with sub-decimeter median horizontal errors even under tree canopy. The errors for the Pixel 5 smartphone were under 0.5 m under open-sky conditions and around 1.5 m under vegetation canopy. The adaptation of the post-processing software to lower quality data was proven crucial, especially for the smartphone. In terms of signal quality (carrier-to-noise density, multipath), the standalone receiver provided significantly better data than the smartphone.

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Smartphone RTK positioning with multi-frequency and multi-constellation raw observations: GPS L1/L5, Galileo E1/E5a, BDS B1I/B1C/B2a

Wang

Zhu

et al. 2023

J Geod

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3rd Place Winner: 2022 Smartphone Decimeter Challenge: An RTKLIB Open-Source Based Solution

Cited by 10 publications

References 0 publications

Evaluation of a GNSS/Imu/Lidar-Integration for Airborne Laser Scanning Using Rtklib PPK and PPP GNSS Solutions

Evaluation of a GNSS/Imu/Lidar-Integration for Airborne Laser Scanning Using Rtklib PPK and PPP GNSS Solutions

Static Positioning under Tree Canopy Using Low-Cost GNSS Receivers and Adapted RTKLIB Software

Smartphone RTK positioning with multi-frequency and multi-constellation raw observations: GPS L1/L5, Galileo E1/E5a, BDS B1I/B1C/B2a

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