Abstract
The NASA Scatterometer was a satellite radar system launched in August 1996 on Japan's Advanced Earth Observing System ADEOS to remotely sense ocean surface wind vectors. This radar measures backscattered power from the ocean at three azimuths and uses a non-linear wind retrieval algorithm to infer surface wind vectors. This paper presents a new approach to the wind retrieval process to estimate ocean-surface wind vectors. This new approach employs a genetic algorithm (GA) to find the wind vector solutions that minimize the likelihood function. The likelihood function is generated by summing the errors of the theoretical backscatter (normalized radar cross section, sigma-0) vs measured sigma-0 divided by standard deviation of the measurements in every wind vector cell. Currently, the NSCAT Project algorithm implements a 'special brute force' approach to finding the wind vector solutions that minimize the likelihood function (or maximize the inverse of the function). The paper also presents comparisons of the results of using the GA approach vs the current NSCAT algorithm. The GA approach is shown to be more robust and immune to reaching sub-optimal solutions by avoiding local minima. (Author)