Time difference auto‐extraction methods for in situ sound speed measurements in seafloor sediments.

The in situ acoustic measurement of seafloor sediment is an important technical means to obtain the acoustic parameters of seafloor. The time‐of‐flight method is commonly used to calculate the sound speed in seafloor sediment. Accurate identification of signal feature points is essential for determining travel time or travel time difference of acoustic signals. However, the precise identification of feature points, such as the take‐off point of the first wave of a sound wave signal, is challenging. The conventional manual identification method is inefficient and prone to errors. The development of a feature point auto‐identification method is imperative for accurately calculating the travel time of acoustic signals. In this study, we employed the cross‐correlation method, the level threshold method and the short window‐long window energy ratio method to extract the acoustic travel time differences and calculate the sound speeds in seawater and in seafloor sediment. We then analysed the effectiveness of these calculated results. The sound speeds in seawater obtained through the aforementioned methods were compared with the sound speeds measured using a sound velocity profiler. The comparison revealed that these processing methods exhibit a high level of accuracy. The sound speed results in sediments show that the programme‐based auto‐identification methods significantly reduce the standard deviation compared to the manual identification method. This study successfully assessed the processing accuracy of different methods and expanded the processing methods for in situ acoustic signals of seafloor sediments. [ABSTRACT FROM AUTHOR]