Reconstruction Of Ocean Front Based On Clustering Sound Speed Profile And Its Influence On Acoustic Propagation

Ocean front is one of the most common and important mesoscale phenomena in the ocean,representing a narrow transition zone between two water masses with different properties.In the sea area where the ocean front exists,due to the drastic changes in temperature,salinity,and so on,it will have an important impact on the structure of the sound speed profile,which will have a very important impact on underwater acoustic detection.Studying on the detection methods of ocean fronts and their acoustic effects is of great significance for underwater acoustic detection and sonar performance evaluation.First of all,this paper studies the methods of detecting the ocean front and sound speed field modeling,and describes three fuzzy clustering methods to explore the feasibility of their application in the identification of sound speed profile categories in the ocean front sea area;Based on the two-dimensional parameterized temperature field model of the ocean front,the sound speed profile is used instead of the temperature profile to improve the model,and a two-dimensional parameterized sound speed field model of the ocean front is proposed;the sound field is calculated using the BELLHOP sound field calculation tool,and acoustic propagation effects are analyzed and discussed under different ocean front environments.Secondly,this paper proposes a geometric reconstruction method of Kuroshio intrusion front based on sound speed profile clustering.The sound speed profile of Kuroshio intrusion front in Luzon Strait is analyzed through fuzzy clustering based on transitive closure and fuzzy C-means clustering to detect the frontal zone of the Kuroshio intrusion front;considering the impact of ocean fronts on acoustic propagation,the transmission loss is calculated to verify the effectiveness of the two algorithms in different depth ranges;finally,this two algorithms are combined,selecting a more effective algorithm in their respective depth ranges,the three-layer geometric optimization structure of the Kuroshio intrusion front in the Luzon Strait is obtained based on the sound speed profile for the first time.Two fuzzy clustering algorithms are used to classify the sound speed profile,which provides a new method for the detection of the ocean front in different depth ranges and the reconstruction of the ocean front geometric model.Finally,the paper analyzes the effectiveness of the ocean front sound speed field model in the prediction of the sound field of the Kuroshio extension front.The fuzzy C-means clustering is used to cluster the surface sound speed of the Kuroshio extension sea area,and the frontal zone of the Kuroshio extension is detected.The sound speed profile is used to replace the temperature profile to reconstruct the sound speed field of the Kuroshio extension front;compared with the actual ocean front calculated by the whole sea depth reanalysis data,the root mean square error of the transmission loss calculated by the model is less than 6d B,which proves The effectiveness of the model;it is proposed to use the melt function in the model to predict the depth change of the convergence area.Compared with the result calculated by the reanalysis of the whole sea depth data,the root mean square error of the depth prediction of the second detection convergence area is 43.3m.This reconstruction method does not rely on the high spatial resolution data of the whole sea depth in the study area,and has reference significance for the rapid and efficient sound speed field reconstruction and acoustic detection in the ocean front environment.