Sonar Detection Distance Prediction Technology Based On WOA Data Set And Argo Observation

The detection range is an important index of sonar performance.Besides the sonar equipment itself,the factors affecting sonar detection range also include the uncertain and complex marine environment formed by the mixing of ocean temperature,salinity,terrain,wind and wave,density and other factors.The establishment of an accurate prediction of the marine environment in an area is of great significance for maximizing sonar performance.Therefore,data assimilation technology is needed to process data sets and observed values of marine environmental elements,such as temperature and salt,and assist sound channel simulation model to obtain more accurate time-varying and multi-source ocean channels,so as to provide data support of marine environmental elements for accurate prediction of sonar detection area and accurate prediction of sonar performance.From this study to determine the Angle of sonar detection range of equipment,design based on the quality factor of the sonar detection range judgment method,using the Ensemble Kalman Filter algorithm to thermohaline deep in the ocean environment elements such as assimilation,the factors to sound field by BELLHOP software calculation of transmission loss,with the quality factor predicting sonar detection area.The multi-source data assimilation and the space-time prediction assimilation were carried out respectively.The ocean observation data,such as temperature and salinity,were introduced with the assimilation technology.The multi-source assimilation made the background field data absorb the historical data and the current observation data to enrich the data information.The assimilation of the prediction model is carried out to reduce the prediction error of the process model and achieve the purpose of obtaining the propagation loss characteristics of the sound field more accurately,to provide a more accurate temperature and salt database for the more accurate prediction of sonar performance.The results of this paper show that the assimilation technology can assimilate and integrate the data products obtained from different sources,different resolutions,direct observation and indirect data and the model prediction results into a data set of marine environmental elements with more spatial and temporal consistency and physical consistency,such as temperature and salt depth.It can provide important data support for reducing the error of estimation and prediction of sonar detection performance.