Onboard identification of plasma waves based on large-data clustering and its feature aggregation

Onboard identification of plasma waves would play an important role in their observations in future spacecraft projects. Akebono satellite has observed plasma waves for these 25 years and has acquired a huge data set of them. The data set is of great value as a catalog of various plasma waves. We applied a clustering method to the data set of Akebono and classified the observed waves into several categories according to their spectrum features. The statistical features of the classified waves can be used to identify observed waves quickly.