Roland Schwarz

A well-known technique to enhance the signal to noise ratio (SNR) of repetitive signals is to average them. The coherent parts of the signal add up constructively while the incoherent parts are averaged out. The prerequisite is that the signals are acquired under conditions of high repeatability, i.e., the signals must be sufficiently similar. In the present technical note, we describe an efficient method for maintaining signal similarity by ensuring spatial and temporal proximity of laser waveform signals obtained by a sensor operated from an airborne platform. The method makes use of a few auxiliary parameters such as laser pulse repetition rate, mirror rotation rate, platform altitude and flight speed. The method can be extended to be operated in real time.

A well known technique to enhance the signal to noise ratio (SNR) of repetitive signals is to average them. The coherent parts of the signal add up constructively while the incoherent parts are averaged out. The prerequisite is that the signals are acquired under conditions of high repeatability, i.e.\ the signals must be sufficiently similar. In the present technical note we describe an efficient method for maintaining signal similarity by ensuring spatial and temporal proximity of laser waveform signals obtained by a sensor operated from an airborne platform. The method makes use of a few auxiliary parameters such as laser pulse repetition rate, mirror rotation rate, platform altitude, and flight speed. The method can be extended to be operated in real time.

In contrast to topographic laser scanning, laser hydrography must take into account the presence of two media. A pulsed laser beam, which enters the water from the air at an oblique angle, is refracted at the air–water boundary in the direction of the plumb line. This change in the direction described by Snellius’ law is caused by a slower speed of the light wave in the water, i.e., the phase velocity. Light scattering caused by turbidity gives rise to further deviations from the straight path. Together, the slower speed and the turbidity-induced path extension cause a longer pulse round trip time in the water than in the air. For an accurate measurement, it is important to correct this propagation time extension. It is a common practice to assume the phase velocity as the velocity for the laser pulses in water. In a dispersive medium, however, the phase velocity is only an approximation of the velocity of a pulse. In media with chromatic dispersion, the pulses propagate with a different velocity, i.e., the group velocity. In water, using the group velocity instead of the phase velocity reduces the range dependent bias of the depth measurement at a laser wavelength of 532 nm by more than 1.5%. We present an easy to perform an experiment, which shows that the group velocity differs so much from the phase velocity that this difference should be taken into account. We further discuss the use of group velocity to explain the depth bias using examples from the literature.

We report on a fully integrated, light-weight, and compact airborne laser scanner system for combined hydrographic and topographic surveying. To handle target situations with complex echo signals the entire digitized echo waveforms can be stored on the removable data storage card for subsequent full waveform analysis. Storing the entire waveform allows for pre-detection averaging, which increases SNR (Signal to Noise Ratio) and thus performance. Waveform averaging can also be applied onboard in order to apply signal detection and online waveform processing with averaged waveforms. The user can choose any combination of online waveform processing, offline single waveform processing or offline waveform processing with stacked waveforms. We demonstrate the achievable performance gain by waveform stacking and by different methods of waveform processing and waveform analysis making use of a typical topo-bathymetric dataset.

We present the sensor concept and first performance and accuracy assessment results of a novel lightweight topo-bathymetric laser scanner designed for integration on Unmanned Aerial Vehicles (UAVs), light aircraft, and helicopters. The instrument is particularly well suited for capturing river bathymetry in high spatial resolution as a consequence of (i) the low nominal flying altitude of 50–150 m above ground level resulting in a laser footprint diameter on the ground of typically 10–30 cm and (ii) the high pulse repetition rate of up to 200 kHz yielding a point density on the ground of approximately 20–50 points/m². The instrument features online waveform processing and additionally stores the full waveform within the entire range gate for waveform analysis in post-processing. The sensor was tested in a real-world environment by acquiring data from two freshwater ponds and a 500 m section of the pre-Alpine Pielach River (Lower Austria). The captured underwater points featured a maximum penetration of two times the Secchi depth. On dry land, the 3D point clouds exhibited (i) a measurement noise in the range of 1–3 mm; (ii) a fitting precision of redundantly captured flight strips of 1 cm; and (iii) an absolute accuracy of 2–3 cm compared to terrestrially surveyed checkerboard targets. A comparison of the refraction corrected LiDAR point cloud with independent underwater checkpoints exhibited a maximum deviation of 7.8 cm and revealed a systematic depth-dependent error when using a refraction coefficient of n = 1.36 for time-of-flight correction. The bias is attributed to multi-path effects in the turbid water column (Secchi depth: 1.1 m) caused by forward scattering of the laser signal at suspended particles. Due to the high spatial resolution, good depth performance, and accuracy, the sensor shows a high potential for applications in hydrology, fluvial morphology, and hydraulic engineering, including flood simulation, sediment transport modeling, and habitat mapping.

With recent advancements in unmanned aircraft system (UAS) technology, along with the miniaturization of airborne laser scanning systems, capabilities of unmanned laser scanning (ULS) systems have increased. Traditional terrestrial laser scanning surveys provide high density point clouds (hundreds - thousands of pts/m2) of a focus area, but have limited field-of-view and line-of-sight due to the constrained static nature of the system. While airborne and mobile laser scanning platforms relieve many of these limitations, lower point density (airborne), confined operation pathways (mobile), and higher operational costs become a factor. Here we present results from ULS data acquired over the Hilo Deep Draft Harbor Breakwater in Hawaii in June 2018. Inspecting the breakwater for failures and instabilities is of vital importance for Hilo. At three kilometers length and exposure to open ocean, a terrestrial laser scanning survey of the breakwater is not possible. Airborne and mobile laser scanning are not ideal due to reduced point densities and site access, respectively. In June 2018, using a RIEGL RiCOPTER with VUX laser system, the authors collected highresolution data over the above water breakwater extents. For below water surfaces, a Riegl BDF-1 bathymetric depth finder was operated from the same UAS, used to generate profiles of subaqueous surfaces of the breakwater. These bathymetric transects supplement the detailed topographic data collected above water on the breakwater. We discuss the operational concerns in both project planning and acquisition phases, as well as detailed analysis of the resulting data, used for a rigorous structure inspection program.

The system waveform (SWFM) of a pulsed LiDAR is obtained from the pulse shape received when pointing the sensor towards a flat, extended target with the surface normal equal to the laser beam direction. The SWFM is determined by the shape of the outgoing laser pulse and the transfer characteristics of the receiver. Knowing the SWFM is essential for performing highly accurate range measurements, for interpreting the LiDAR waveforms correctly, and to derive additional attributes for detected target returns. Often the actual SWFM is not known explicitly, and a Gaussian pulse shape is used in lieu thereof. However, the Gaussian pulse, despite its advantageous properties, does not properly address asymmetries and ringing effects typically present in real-life SWFMs. We present a model of the SWFM composed of harmonic and exponential terms which is able to account for these effects while at the same time being mathematically easy to handle. Unfortunately, the approximation of data by a sum of harmonics and exponentials belongs to the class of ill-posed problems. Nevertheless, we present a pragmatic solution to the problem and demonstrate the versatility of the resulting model.