Research Of Ocean Wind Fields Retrieval Technology By Navigation Radar In Moving Environment

The ocean surface wind field is an important parameter to study the interaction process between atmosphere and ocean, and it has very important significance to the construction and development of marine engineering and the safety of ship. The wind field inversion research by X-band navigation radar has made remarkable achievements, but most of them were based on shore-base radar data. when the platform is in motion, how to inverse the ocean surface wind field in the dynamic environment has become a new topic. Therefore, relying on the research project of "the ocean wave inversion technology by shipborne X-band radar" test,this paper develops the inversion research of ocean surface wind field by X-band radar in the dynamic environment.It is found that the wind field inversion research mostly used shore-base radar data, on the basis of analysis for the domestic and foreign literatures. Due to the need to average over the radar image sequences before wind streak are picked up, the near-far effect of the ship's motion destroys the integrity of the wind streak, so the accuracy of the wind direction inversion is affected. But using radar cross section to obtain the wind direction needn't correct the ship motion and the accuracy are not affected by the radar carrier. In this paper, we establish the harmonic function that was least-squares fitted to the radar cross section as a function of the antenna look direction after processing the radar images, to solve the problem of partial occlusion, then the angle between extraction wind direction and heading was given by the direction that corresponded to the peak of the fitted function and based on the heading,we could calculate the wind direction. Then two kinds of mode functions are compared. Using real radar data to validate the algorithm of ocean wind direction and compare with the data obtained from shipborne dogyane. The experimental results show that the proposed algorithm can be directly applied to the shipborne X-band radar data, and the improved model function has higher precision.The main algorithms of wind speed inversion are neural network method and mode function method. The neural network method has some limitations, because it have to make retraining when it is used to different radar data, and it cannot provide the explicit physical model of radar imaging mechanism. And how to determine the wind speed model has been becoming a key content in the model function method. We establish the function that was least-squares fitted to the wind speed as a function of radar cross section after processing the radar images,then the coefficient can be determined,so we can calculate the wind speed according to the function. Then we research the empirical relationship between the significant wave height and wind speed.Since the wave height is usually in connection with wind speed,fetch and wind duration, when the fetch and wind duration are long enough, the waves reach full growth state,there is a empirical relationship between wind speed and wave height,so we can calculate the wind speed through the relationship. The data analysis show that both the two algorithms exist the problem of low precision and weak correlation. So this paper combines the radar cross section with significant wave height, and puts forward an improved wind speed model function,then it is validated by a large of datas. The last experimental results show that the improved algorithm has higher precision and stronger correlation, and it can meet the needs of the practical application. It is proved that the improved algorithm is effective and feasible.