The variational model inversion (VAR) method for synthetic aperture radar (SAR) wind retrieval based on the Bayesian theory can overcome the limitations of the traditional wind streak algorithm by introducing background wind and considering all sources of error, but its optimal solution is unstable and the time latency is long. In this article, we propose a new wind retrieval method by applying the optimal interpolation (OI) theory to construct a formula that considers the SAR information, background information coming from the numerical prediction model, and their associated well-characterized errors. The retrieved wind vector can be acquired by the analytic solution of the OI formula. The results from the simulation data show that the error of the OI-retrieved wind is smaller than that of background wind in all considered cases; in particular, the accuracy of the OI-retrieved wind speed is significantly improved. Experiments on the Sentinel-1 SAR data show that the root mean square error of the OI-retrieved wind speed and direction are 1.4 m/s and 35°, respectively. Compared with other methods, the retrieved wind speed accuracy of the OI method is similar to that of the VAR method but higher than that of the direct wind retrieval method. The time latency of the OI method is the shortest, and the calculation efficiency is much higher than that of the VAR method. The results indicate that the OI method can be effectively applied to SAR wind retrieval.

基于贝叶斯理论的合成孔径雷达（SAR）风检索的变分模型反演（VAR）方法可以通过引入背景风并考虑所有误差源来克服传统风条纹算法的局限性，但其最优解不稳定且时间延迟很长。在本文中，我们通过应用最佳插值（OI）理论提出一种新的风速检索方法，该公式将考虑SAR信息，来自数值预测模型的背景信息及其相关的特征明确的误差。可以通过OI公式的解析解来获取检索到的风矢量。模拟数据结果表明，在所有考虑的情况下，OI引回风的误差均小于背景风的误差。尤其是，OI回收风速的准确性大大提高。对Sentinel-1 SAR数据进行的实验表明，OI提取的风速和风向的均方根误差分别为1.4 m / s和35°。与其他方法相比，OI方法的风速精度与VAR方法相似，但高于直接风速方法。OI方法的时间延迟最短，并且计算效率比VAR方法高得多。结果表明，OI方法可以有效地应用于SAR风的反演。与其他方法相比，OI方法的风速精度与VAR方法相似，但高于直接风速方法。OI方法的时间延迟最短，并且计算效率比VAR方法高得多。结果表明，OI方法可以有效地应用于SAR风的反演。与其他方法相比，OI方法的风速精度与VAR方法相似，但高于直接风速方法。OI方法的时间延迟最短，并且计算效率比VAR方法高得多。结果表明，OI方法可以有效地应用于SAR风的反演。