Radar signal sorting algorithm of k-means clustering based on data field

Radar signal sorting is one of the essential technologies in radar countermeasures reconnaissance system. Non-cooperative radar signal sorting without prior information has been a great challenge for radar countermeasures. This paper presents a k-means clustering radar signal sorting algorithm based on data field by introducing data field theory. Firstly potential value of all the data samples is calculated with the algorithm based on data field theory, and noise is eliminated by comparison of the calculated values, to find local maximum potential value. Then the sample data of the closest value to maximum is selected as the initial cluster center and the number of local maximum potential value as cluster number. Finally, the conventional k-means clustering algorithm is applied for clustering. The proposed method can eliminate noise points and automatically obtain initial cluster center and cluster number, which is suitable for non-cooperative radar without prior information. Simulation results verify the feasibility and effectiveness of the method.