LiDAR requires navigation data to conduct a survey. We combine the navigation data with the LiDAR data to create a georeferenced Pointcloud. LiDAR devices know where points are in relation to themselves, but they need to be told where they are in the world to be able to build a Pointcloud while moving the LiDAR. The navigation data often comes from an inertial navigation system (INS). An INS is a sophisticated combiner of inertial measurement unit (IMU) and global navigation satellite system (GNSS) data to get the best navigation data – so a device knows where it is in the world and how it is moving. OxTS has been a global leader in inertial and GNSS since 1998. The coordinates from the INS are added vectorially to the point coordinates of the LiDAR to get the final coordinates that would be used in the Pointcloud. This allows one to put their LiDAR device on a vehicle like a van or an unmanned aerial vehicle (UAV) with an INS and survey large areas efficiently instead of doing multiple static surveys and stitching them together.
Angles that seem tiny to us can become very large problems over large distances. Imagine two lines are meant to be exactly parallel but instead there is a 0.5° offset between them. This appears small perhaps if we focus on the point where the lines cross but extrapolate this angle over 10m and you will have a linear displacement between the lines of roughly 10×0.5/360 2π=0.09m=9cm. This is a problem called boresight misalignment and it occurs when you have two coordinate systems that are not exactly aligned. And this becomes a problem in applications where you are looking for centimetre accuracy and you are looking at objects some tens-of-metres away, for example, LiDAR surveying. People want to get the most accurate Pointclouds but to do this they will have to get the most accurate angular calibration between the coordinate frames of the navigation device and the LiDAR. Over distances of 50m you can imagine that these angles must be calibrated to 0.1° and this is extremely difficult. The human eye cannot often perceive angles more accurately than a degree and even CAD modelled mountings will find this difficult when all is said and done. The mounting of the IMU inside the INS unit and the true laser coordinate system can also differ from the specification by such small angles.
On top of the issue with angles you also have the question of linear displacements. The LiDAR and INS will be mounted some distance away from each other and this also has to be measured. This is often less of a problem than the angular displacement because its effect is not exacerbated by distance but it can be a problem particularly when surveying the same area from multiple directions. If you had a 5cm offset in one axis between the reality and your measurements then you will have a constant 5cm offset in that axis in all the points of your Pointcloud, however if you then turn around and survey in the opposite direction, that same 5cm offset is applied in the opposite direction. You will then have two iterations of all the objects you surveyed, 10cm apart. This is often referred to as ‘double-vision’. For a georeferenced Pointcloud to have the highest accuracy in the location of its points, it needs to have a well calibrated setup with the angles and displacements as close to reality as possible.
The OxTS Georeferencer software offers users the ability not only to create Pointclouds with their data but to also calibrate the setup they used.
This ‘What is a Georeferenced Pointcloud?’ article is part of our ‘What is a Pointcloud?’ series.