中文摘要：

通过高频雷达一阶多普勒谱与海上风向的关系,提出了一种基于神经网络和多波束采样法相结合预测海面风向的新方法.在神经网络不同输入、输出参数情况下对扩展因子为奇数时的仿真数据进行了风向预测,并在扩展因子为偶数时结合多波束采样法进行风向预测,消除了风向的模糊性.通过预测数据和仿真数据对比,发现两者符合较好.从神经网络和多波束采样法相结合的预测结果中可以看出,风向的误差大约为4°—6°,风向扩展因子的平均误差为0.26,为预测海面风场的研究提供一种新的思路和方法.

英文摘要：

According to the relationship between the first-order Doppler of HF radar and the wind direction over the sea surface,a new method of predicting wind direction is proposed with considering the combination of neural network and the method of the beam sampling.Using the simulated data under different input and output parameters of neural network,the wind direction is predicted when the expansion factor is odd number,the combination of the neural network and the beam sampling is utilized to predict the wind direction when the expansion factor is even number,which can eliminate the fuzziness of the wind direction.The predicted result shows a good agreement with the simulated data.From the predicted results by the neural network and the beam sampling,it is find that the error of the wind direction is about 4°-6°and the mean error of the expansion factor of the wind direction is 0.26,which provides a new idea and method of predicting the wind field over the sea surface.