Research On High Frequency Ground Wave Radar Sea-state Parameters Inversion Based On The Ocean Dynamic Model And Prediction

High-frequency ground wave radar has good coverage,real-time performance and resolution in the field of marine monitoring,therefore it has been strongly supported and globally developed in marine weather forecasting and marine environmental monitoring.S ea state inversion is relatively mature and accurate in retrieving flow fields,but for single-station radar,it cannot detect the tangential velocity of ocean currents;there are still many limitations and deficiencies in retrieving wave fields and wind f ields.In general,wind field,wave field,and flow field are usually extracted and inverted separately,which makes the sea state parameters relatively independent.Therefore,the simple sea state inversion does not take advantage of the constraint relationship between the parameters in ocean dynamics and hydrodynamics.This paper mainly studies the two-dimensional shallow water model,uses ocean dynamic model to couple the sea state parameters,and proposes a single-station radar method to solve the ocean current vector velocity by using the coupling relationship.Firstly,this article introduces the interaction between high-frequency radio waves and rough sea level,which will produce spikes in the radar echo spectrum,and according to the amplitude and position of the first and second order spectra,the sea state parameters can be extracted.This is the theoretical basis of sea state remote sensing.Secondly,this paper studies the two-dimensional shallow water model in ocean dynamics,which is suitable for the actual application scenario of a certain radar.This model is used to simulate the M2 component with the largest amplitude in the tide,and the correctness of the obtained result is verified.Later,method based on previous procedures would be adop ted in the radar application scenario.Meanwhile,the result can also be used as a follow-up reference and verification standard.Then,this paper introduces a more accurate method to extract wave height and radial velocity,which are used as the input and driving conditions of the model.Thirdly,this paper derives the applicable method of the two-dimensional shallow water model in the calculation of the tangential velocity of the single-station radar.The method is validated and error analyzed with reference to the tidal process,which ve rifies the effectiveness and feasibility of the algorithm.Then applying this algorithm to calculate the actual data of a certain radar and explain the rationality of the result.Finally,this article introduces the windspeed extraction method,as well a s the wind speed prediction which adopted the deep learning network method,analyzes and compares the characteristics and performance of each network,and draws the conclusion that the CNN-LSTM network has the best performance.In fact,wind field can be used as forcing field,and the force can be added to the control equation of two-dimensional shallow water,which can describe the influence of wind field on wave flow,and make the two-dimensional shallow water model more effective.