![]() The experiments are conducted on data set provided by “Istituto Idrografico della Marina Militare Italiana” (IIM), the In this work, we want to analyse the role of sound velocity determination in bathymetric survey and its impact on the accuracy of depth To accurately determine the sound velocity in water, as it varies according to specific parameters (Density, Temperature, and Pressure). Operation of the echo sounder, which uses the principle of acoustic waves to scan the bottom and determine the depth, it is important The method is an alternative for calibrating the SBES the bar check way and has the capacity to meet the requirements in respect to its application in hydrographic surveys.īathymetric surveys are carried out whenever there is a need to know the exact morphological trend of the seabed. The measurements were taken in water areas of the Baltic Sea of low salinity and then verified with measurements in the Mediterranean Sea representing quite high salinity. In respect to the SingleBeam EchoSounder (SBES) immersion depth, i.e., a method commonly used by unmanned surface vessels in seaport measurements, was estimated. ![]() The impact of inaccuracy in determining the sound speed The sound speed in water was determined based on the formulas widely adopted in hydroacoustics and compared with the results obtained from the measurements executed by means of a Conductivity/Salinity Temperature Depth (CTD/STD) probe. The salinity data were obtained via the Internet service from the closest measuring station that registers surface water parameters. It has been assumed that the salinity variation in respect to depth, found in a shallow water area, has insignificant impact on the sound velocity distribution determined by the temperature changes. On temperature measurements executed by means of a laboratory low-cost thermometer with a probe provided with a long cable. The aim of this paper is to present a method of determining sound speed in water, based The designed system prototype can achieve measurement accuracy of 0.05m/s after calibration, which can meet the needs of low-cost and high-precision underwater sound velocity measurement. It is verified by calibration experiments that the neural network calibration algorithm can effectively reduce the nonlinear system error in the measurement, and its effect is better than the traditional linear regression method. Furthermore, according to the sound velocity measurement principle and response characteristics, a calibration algorithm based on Recurrent Neural Network (RNN) and Discrete Wavelet Transformation (DWT) is proposed, which can improve the accuracy and adapt to the nonlinear response of the system by using multiple sets of time data obtained from the measurements. It can be integrated into various underwater measurement platforms and profilers to realize the sound velocity measurement, and it also could be used as a self-contained sound velocity sensor. Its overall volume is small, and the standby power consumption is low. It mainly includes three parts: the control unit, the storage module and the ultrasonic measurement module. In this paper, a low-cost sound velocity profiler is designed based on the time difference method. ![]() The sound velocity profile is the base of various underwater acoustic equipment. ![]()
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