Building an accurate and large digital terrain model (DTM) of the seabed is a key issue in various applications, especially for covert rapid environment assessment using autonomous underwater vehicles (AUVs). New AUV generations are capable of acquiring bathymetry with multiple acoustic sensors: single-beam echosounder, Doppler velocity log, multibeam echosounder (MBES), interferometric sidescan sonar (ISSS), etc. As these sensors acquire the seabed with different geometries, they can be combined to produce a DTM in shorter time. For example, ISSS can reach a wide swath in shallow water but it shows an information gap at nadir, which is usually covered by completing an additional track. Simultaneously using the MBES to acquire the nadir removes the need for this additional track and reduces the energy consumption of the whole survey. This paper focuses on fusion algorithms to extract best information of the two sensors (MBES and ISSS) to feed DTM production software with optimal bathymetric information. This problem may be solved by taking into account the average information of the two sensors. However, the sensors do not always give accurate information and the average information therefore becomes biased. Another way to tackle the problem is to select a priori information given by the better of the two sensors based on a given geometric parameter (e.g., grazing angle). In this case, when the assumed best sensor fails, the information produced by the second sensor cannot be used to compensate for the erroneous information. Our approach consists in using all the available information and fuses it ahead of producing the DTM. Based on the theory of belief functions, this paper presents a framework to fuse the information coming from the two swath bathymetric sensors (MBES and ISSS). The belief theory, applied successfully to other fields, has been extended to handle the bathymetric information. The reliability and the uncertainty of each sonar are introduced in the fusion process to improve the estimation and the accuracy of the final terrain model. First, simulated sonar data, with perfectly known ground truth, are used to quantitatively assess the performance of the fusion process by comparing DTM obtained with and without fusion. Then, the experimental validation is conducted on actual data, acquired simultaneously by the two sonars systems (Klein K5000 ISSS, Reson 8125 MBES) mounted on the DAURADE AUV. Our evaluation of the fusion method shows significant quantitative and qualitative improvement in the production of the final DTM.

A multispectral and multiangle analysis of seabed backscatter intensity has been conducted using data from a calibrated single-beam echosounder (SBES) with five frequency channels deployed over four homogeneous areas with different sediment types in the Bay of Brest (France). The SBES transducers were tilted at incidence angles from 0° to 70° to record the seafloor backscatter angular response at discrete frequencies ranging from 35 to 450 kHz. The recorded backscatter levels were analyzed for their angular dependence (average backscatter strength versus frequency and angle) as well as for their sample statistical distribution. The angle and frequency dependence of the seafloor backscatter obtained using a calibrated SBES can potentially be used to calibrate multibeam systems, and it can also help in elucidating the physical processes of backscatter controlled by the interaction between the acoustic wave characteristics and the sediment properties. Backscatter measurements for each area showed a consistent frequency dependence with little variation between the four sediment types.

For health and impact studies of water systems, monitoring underwater environments is essential, for which multi-frequency single- and multibeam echosounders are commonly used state-of-the-art technologies. However, the current scarcity of sediment reference datasets of both bottom backscatter angular response and water column scattering hampers empirical data interpretation. Comprehensive reference data derived from measurements in a controlled environment should optimize the use of empirical backscatter data. To prepare for such innovative experiments, we conducted a feasibility experiment in the Delta Flume (Deltares, The Netherlands). Several configurations of sonar data were recorded of the flume floor and suspended sediment plumes. The results revealed that flume reverberation was sufficiently low and that the differential settling of fine-sand plumes in the water column was clearly detected. Following this successful feasibility test, future comprehensive experiments will feature multi-frequency multi-angle measurements on a variety of sediment types, additional scatterers and sediment plumes, resulting in reference datasets for an improved interpretation of underwater backscatter measurements for scientific observation and sustainable management.

This study presents a detailed analysis of Angular Response Curves (ARC) extracted from a multi-spectral seabed backscatter dataset utilizing both calibrated single-beam (SBES) and multibeam echosounders (MBES). Five calibrated SBES transducers were tilted from −9° to 70° to measure ARC at different discrete frequencies ranges from 35 kHz to 440 kHz (three to four frequencies per transducer). Additionally, three frequencies −200 kHz, 300 kHz and 400 kHz - were used with the MBES. Experimental data were collected in the Bay of Concarneau, located on the French Northwest coast, across seven different ground-truthed sediment types. The study aims to investigate the effects of frequency and pulse length on ARC shape and intensity. Furthermore, a novel method for estimating seabed angular backscatter from standard SBES volume backscatter strength (Sv) is used. A key aspect of this research is the intercalibration of the multibeam and singlebeam systems to ensure consistency and reliability in MBES backscatter measurements. These findings contribute to a better understanding of acoustic wave interactions with sediment properties across different wavelengths and pulse durations, ultimately improving seabed characterization accuracy.