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3D reconstruction of lake surface using camera and lidar sensor fusion
Title
3D reconstruction of lake surface using camera and lidar sensor fusion
Creator
Khan, Shahrukh
Date
2020
Description
Global Navigation Satellite System Reflectometry (GNSS-R) relies upon detecting the GNSS signals reflected off a surface and then analyzing...
Show moreGlobal Navigation Satellite System Reflectometry (GNSS-R) relies upon detecting the GNSS signals reflected off a surface and then analyzing the reflected signal to obtain surface characteristics. GNSS-R has become one of the many additional applications of the readily available GNSS signals, alongside more traditional remote sensing of ionospheric monitoring, beyond the intended GNSS purposes of providing position, navigation, and timing estimation. In previous work, GPS signals reflected off Lake Michigan in Chicago have been collected using a specially designed portable sensor suite. The data collected is then analyzed to differentiate between surface ice and water conditions, as well as obtain other characteristic information such as surface reflectivity. The goal is to provide a way for remote sensing of seasonal ice formation beyond just satellite imagery which can be affected by cloud cover. To confirm the validity of the GNSS-R results there needs to be a separate reference against which to compare. This work demonstrates the sensor fusion between camera and lidar to reconstruct the lake surface, to provide that truth reference for comparison against the results of the GPS reflectometry signal processing. For this setup, the camera provides visual information about the lake surface, while the lidar provides distance information with respect to the sensor suite. Combining the data from the two sensors allows backward projection of the camera image to reconstruct the lake surface and its features. The backward projection relies upon knowledge of the camera's intrinsic properties alongside distance information of the features captured by the camera. Each pixel of the camera image is then transformed to its 3D position relative to the sensor system. This produces a 3D map of the lake surface, as captured by the sensors. The estimated point at which the GPS signal reflects off the surface, the specular point, is calculated by the satellite position at the time of interest and the receiver location. This point is then mapped onto the reconstructed surface to identify the exact location where the signal reflected and compare the surface visually to the results from the signal analysis.Time-varying camera-lidar-specular-point maps of the data campaigns conducted for this project are created for comparison with the GPS signal analysis. Multiple data campaigns were performed during which the Lake Michigan surface had surface ice, water or a mixture of the two. The lake surface is reconstructed for different timestamps, using the appropriate image frame and lidar frame. Combining chronologically, the changes in the lake surface can then be observed along with the movement of the specular point, due to the movement of the GPS satellites. Any satellites passing over a boundary between water and ice on the lake surface are identified and time stamped, to then be compared to the GPS signal analysis results.
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