Application of dynamic-clustering-based fitness-sharing genetic algorithm to wind vector retrieval for scatterometer
动态聚类适应值共享遗传算法在散射计风矢量反演中的应用

Wind vector retrieval is the key to scatterometer data processing. The design of traditional wind vector retrieval algorithm excessively depends on the detailed distribution shape of the objective function. Taking SeaWinds as an example, according to the multiple solution problem of wind vector retrieval and its ambiguity solution property, a wind vector retrieval algorithm was designed, which was based on the dynamic clustering niche genetic algorithm. By using some Level 2A data and the corresponding Level 2B data, the algorithm was validated. The experimental results indicate that the algorithm achieves good wind field results without using any transcendental knowledge of the objective function.