The evaluation of measurement data plays an increasingly important role in the development of our measurement systems - no matter whether it is the signal of a single sensor or a data stream from different sensors of an integrated system. Today, our work is rarely limited to pure hardware development. Numerous new data evaluation methods allow us to obtain a large amount of valuable information from measurement data that was previously inaccessible.
Full Waveform for the interpretation of LiDAR data
With LiDAR systems, a large number of echoes often return to each emitted pulse - depending on the environment. From this echo sequence, also known as full waveform, various parameters and ultimately also the 3D information of an object can be derived.
If the measuring system operates in a turbid medium such as water, fog or smoke, the light emitted by a LiDAR system is scattered by particles. The result is a strong scattering signal that overlaps with the actual signal of the object to be detected. Only intelligent sharpness and separation algorithms allow the reconstruction of the 3D image under such conditions. The generated data can then be used in applications such as autonomous driving, underwater inspection or disaster control.
Multispectral analysis provides information on material composition
In order to be able to assign additional parameters to an examined 3D object in addition to the pure geometry, a multispectral analysis can be performed in many cases. We use either passive systems, i.e. cameras with corresponding color filters, or active systems, i.e. laser scanners with laser beams of different wavelengths. The analysis of a multispectral signal, for example, allows statements to be made about the state of health of plants, makes it possible to distinguish between ice and water and makes moisture visible in rooms.