A new fast wind vector retrieval algorithm for SeaWinds scatterometer

]According to the main shortcoming of the traditional Maximum Likelihood Estimation(MLE) hased algorithm for its high computational complexity, a new fast wind vector retrieval algorithm for SeaWinds Scatterometer is derived in this paper. The new fast algorithm adopts wind speed standard deviation instead of objective function as its criterion for searching possible wind vector solutions, which leads to lower complexity than traditional MLE algorithm. In order to further reduce retrieval computations, the new algorithm is implemented by a two-step method. First step accomplishes a coarse searching for likely wind vector solutions, while the second step functions as a fine adjustment for each coarse solution. Using sonic SeaWinds L2A and corresponding L2B data, the new algorithm is validated. The results indicate good performance and high retrieval accuracy of the new algorithm for experiment data.Geosciences, MultidisciplinaryRemote SensingCPCI-S(ISTP)