一种新的海洋风场矢量估计算法

基于合成孔径雷达(SAR)图像的海面风场估计已经得到广泛认可。多数风速反演算法是以估计的风向、校正的δvv为先验条件,应用海风模型计算而得的。在相同风向的情况下,应用不同的海风模型会得到不同的风速反演值,因此选择合适的模型是风场估计的关键。同时,风向数据的精确度也很重要,即使不大的误差也会给风速的反演结果带来明显偏差。为解决上述问题这里提出一种不需要预先已知风向数据的风场估计算法。该算法将基于海洋SAR图像中风浪的条纹信息,以及风浪条纹生成的自相关函数的周期性估计风速数据,同时由风浪条纹的最短周期方向估计风向数据,从而估计出完整的风场矢量。仿真结果显示,该算法对风速和风向数据有较高的估计精度。

A new ocean wind field estimation algorithm

Wind field information estimate of sea surface from Synthetic Aperture Radar(SAR)images has been widely acceptable.Most algorithms of wind filed estimates use wind direction and corrected δvv as priori information before it sent into geophysical model function.Considered the same wind direction,different geophysical model function would gain different wind velocity,so it’s crucial to selected model function.Moreover,the accuracy of wind direction data is very important,tiny error in wind direction can lead to obvious difference in wind velocity.It will give a new algorithm which doesn’t need the priori wind direction information;and it can estimate wind velocity based on texture information of the ocean SAR image and the periodic of generated autocorrelation function,at the same time,estimate wind direction by the shortest period stripe data of winds and waves image,then get complete wind vector.The simulation results show that this method can give higher accuracy for wind field estimation.