Radar active blanket jamming sorting based on resemblance coefficient cluster
Zhu Tang, Bing Zhang, Guangqiang Li, Chenlong Zhang · 2013
A sorting method based on resemblance coefficient cluster is put forward to effectively improve the sorting accuracy of radar active blanket jamming. In the method, resemblance coefficient of blanket jamming is used to replace traditional Euclidean distance; resemblance entropy index is deemed as the symbol for whether iteration comes to an end or not. Besides, K-means classifier is improved accordingly. Improved clustering classifier is used for sorting of radar blanket jamming signals. Simulation experiment proves that the method can improve identification rate of types of radar blanket jamming signals in an efficient way and it is characterized by excellent universality.