Analysis On The Difference And Main Influencing Factors Of Multi-band Sea Clutter Characteristics In Different Sea Areas

The sea clutter characteristics of different sea areas in real marine environment play an important role in radar detection,remote sensing,SAR imaging,situation awareness and other applications.Because of the complexity and variability of the sea environment in different sea areas,there are obvious differences in sea clutter,so it is necessary to establish a real sea clutter database.However,it is very expensive to obtain the sea clutter characteristic data through field experiments.It is necessary to combine the multi-band sea clutter characteristic modeling of different sea areas,coordinate the measurement data with the theoretical model,and use deep learning to study and evaluate the sea clutter characteristics and influencing factors,which is an effective research method.This paper mainly studies the simulation modeling of sea clutter characteristics in different sea areas,and analyzes the differences and main influencing factors of sea clutter.Based on the real marine environment data of different sea areas,combined with time-varying multi-scale sea clutter characteristics modeling and high-performance simulation calculation,this paper reveals the physical mechanism of sea spike under the condition of small friction angle,high sea situation at high frequency,and establishes the sea clutter database of different sea areas with multi physical fields.The main factors of marine environment include wind speed,wind direction,wave height,wave direction and wave period,which affect the difference of sea clutter in different sea areas.The main research results and characteristics of this paper are summarized as follows:1.Due to the complexity and variability of the marine environment in different sea areas,there are obvious differences in sea clutter,so it is necessary to establish a real sea clutter database.Based on the European Centre for Medium-Range Weather Forecasts(ECMWF)data from 2015 to 2017,this paper establishes a multi physical field spatiotemporal distribution database of wave types and marine environmental factors in Bohai Sea,Yellow Sea,East China Sea,Taiwan Strait and South China Sea,including the large probability value range of marine environmental factors in different sea areas in four seasons.The database is used to establish the theoretical model of sea electromagnetic scattering,the characteristics of sea clutter and deep learning to provide reliable real marine environment with multi physical field conditions.2.The traditional sea electromagnetic scattering model based on the wind wave spectrum only considers wind speed and direction,thus it cannot analyze the difference of sea clutter characteristics under the same sea conditions in different sea areas.In this paper,the mixed gravity wave spectrum of wave height,wave direction and wave period is considered,combining with the instantaneous Efouhaily tension wave model based on wind speed and wind direction,the multi-scale sea surface geometric modeling of the actual marine environment is realized.The foam modified dual scale algorithm is improved to study the electromagnetic scattering characteristics of different sea areas under the same wind direction and the difference mechanism is revealed.3.Based on the real ocean environment data of different sea areas,combined with time-varying multi-scale sea clutter modeling and high-performance simulation calculation,this paper reveals the physical mechanism of sea spike under the condition of small angle of friction,high sea situation and high frequency,and establishes the sea clutter database of multi physical fields in different sea areas.This paper focuses on the study of multi physical field parameters and depth cognitive model of sea clutter statistical characteristics and various parameters of marine environment by using deep learning.Factor analysis method is proposed and applied to the analysis of influencing factors of sea clutter differences in different sea areas.Taking the marine environment data of the same sea area as an example,combined with the analysis of time series and Doppler characteristics of sea clutter,it is found that HH polarization is often higher than VV polarization when the actual sea clutter is in high frequency and high sea conditions,and in the case of small angle of friction,when the grazing angle is taken as 10°,5° and 3°,it can be found from the polarization ratio of HH and VV polarization amplitude of S and X-band that with the increase of sea condition,the wave band increases and the grazing angle decreases,the HH polarization is greater than VV polarization.The multi-path effect,diffraction effect and complex scattering effect of the sea surface are more prominent under the condition of high sea condition and small grazing angle,which may also be the main scattering mechanism of "sea peak" phenomenon.4.The traditional sea spike extraction method is complex and has many limitations.In this paper,the analysis algorithm of isolated forest abnormal data is introduced to calculate the abnormal fraction of sea clutter characteristic data in different sea areas.It is found that the time period when the abnormal fraction of marine environment is less than-0.1 is highly correlated with severe weather such as typhoon;at the same time,it is found that the correlation of the time period when the abnormal fraction of the mean value of different polarizations is less than-0.1 and the radar echo anomalies is highly correlated,and in the period of abnormal marine environment,sea spike is more likely to occur.The above research results provide technical support for marine electromagnetic situation awareness.