# Frequency-Dependent Acoustic Reflection for Soil Classification in a Controlled Aquatic Environment
###### Abstract
The first advance in acoustic seafloor classification came through multibeam echo sounders, with [PERSON] et al. [2] demonstrating their potential for investigating seafloor processes in coastal zones. Their research showed that while these initial acoustic systems could provide basic information about seafloor properties, they were limited by their narrow coverage area and inability to capture detailed spatial variations in seabed characteristics. Multibeam echo sounders (MBESs) development marked a significant leap forward in remote seafloor characterization capabilities. [PERSON] and [PERSON] [5] demonstrated MBES's ability to simultaneously collect both bathymetric data and backscatter information across wide swaths of the seafloor, while [PERSON] et al. [6] showed how these systems could maintain high resolution even in deeper waters. [PERSON] [12] further validated MBES's effectiveness by successfully implementing automated acoustic seabed classification techniques using multibeam data. However, [PERSON] and [PERSON] [13] identified critical limitations in raw MBES data interpretation, particularly distinguishing between sediments with similar acoustic properties. While MBES systems represented an advance over single-beam systems, several fundamental limitations persist in their application. [PERSON] et al. [14] demonstrated that backscatter strength measurements are inherently affected by the angle of incidence, making it difficult to isolate the proper acoustic response of the seafloor material itself. This limitation becomes particularly significant when distinguishing between different sediment types, as the angular dependence can mask subtle differences in material properties. [PERSON] and [PERSON] [15] identified that amplitude-based backscatter analysis struggles to differentiate between sediments with similar grain sizes, noting that multiple factors beyond the sediment composition influence the acoustic response. [PERSON] et al. [16] highlighted another critical limitation: the acoustic signal's interaction with the water column and various environmental factors can significantly impact the received backscatter data. Their research showed that variations in water properties and the presence of suspended particles can alter the acoustic response, making it challenging to establish consistent classification parameters. This observation was further supported by [PERSON] and [PERSON] [17], who found that even calibrated seafloor backscatter data could yield inconsistent results when analyzing similar sediment types under different environmental conditions. [PERSON] et al. [18] emphasized that acoustic methods primarily analyze the total returned signal strength without considering the specific spectral characteristics of various materials interacting with acoustic energy. The angular range analysis (ARA) technique, initially developed and validated by [PERSON] and [PERSON] [1], provided a methodological framework for analyzing MBES backscatter data. This approach was further refined by [PERSON] et al. [19], who demonstrated its effectiveness in linking visual interpretations with acoustic signatures. [PERSON] and [PERSON] [4] introduced a Bayesian statistical method for classifying seafloor sediments using multi-beam backscatter data. By analyzing the acoustic response patterns probabilistically, their approach aimed to improve classification accuracy. However, their research revealed significant limitations in differentiating between sediment types with similar acoustic properties, particularly in areas with mixed sediments or gradual transitions between substrate types. To address these classification challenges, [PERSON] and [PERSON] [20] developed Geocoder, a comprehensive software tool for processing backscatter data from various sonar systems. [PERSON] et al. [6] later demonstrated how this tool applies radiometric corrections to account for transmission losses and beam-pattern effects, aiming to produce standardized backscatter measurements. However, despite these processing advances, [PERSON] et al.