Research On New Method Of Non-acoustic Detection For Anti-submarine

With the development of submarine noise deduction and"stealth"technology,How to efficiently promote detection technology becomes an urgent problem in the anti-submarine war of modern warfare situations. As a new kind of anti-submarine detection technology, non-acoustic detection technology has efficiently overcome the deficiency of sonar detection technology and attracted much attention from more and more countries. Under this condition, how to develop non-acoustic detection technology and assess its functions becomes an important research project of domestic and foreign researchers. Moreover, their research should focus on what kind of strategic decisions will be made based on various submarine detection data. These two problems are exactly solved through computer simulation technology and decision-support system.Firstly, this paper introduces the mathematic model of ocean wave spectrum and simulates random wave surfaces under various ocean conditions by means of the mathematic model of random ocean wave and the equi-energy divided method. These random waves are combined with the ocean surface waves induced by the internal waves of submarine underwater movements, which helps simulate the wave changes caused by submarines at different speeds under different ocean conditions. Secondly, the paper further studies submarine's thermal wakes floating and the feature that submarine's underwater movements will cause the rising of regional ocean water temperature. Based on ocean-air exchange theory and the anomaly of atmospheric refractive index, it introduce the submarine detection method of ocean-air exchange. Furthermore, the paper studies the signals of radar echoes and study the non-acoustic submarine detection methods of radar echoes on the ocean surface. This method builds its foundation upon the abnormal signals of radar echoes on the ocean surface which are caused by the altered roughness and radar cross-section of ocean surface in the areas of submarine movements. This alteration results from the wake flow and trace caused by submarine underwater movements. Moreover, due to the incorrect results of single submarine detection method, it further studies the fuzzy pattern recognition and study level classification method of submarine threat on the basis of the fuzzy pattern recognition. At the end, in order to prevent from the large-scale and blindfold search on submarines, it study a level classification method of submarine regional threat on the basis of grey cluster assessment. Based on the fusion calculation of various detection data and assessment about the possible areas of submarine activities, it gains the full knowledge of how possible a submarine appears in various areas and provides some supports for the correct decisions in the anti-submarine war.From the second chapter, this paper will start to have a simulation experiment about every detection method and data fusion technology. The results of this experiment are also analyzed and assessed to provide a reference for the further research on anti-submarine non-acoustic detection technology and decision support system research.