Micro-motion Feature Extraction of Ballistic Targets Based on Narrowband Radar Network
XU Dan
TIAN Bo
FENG Cunqian
GENG Zhiyuan
Abstract：Targets' micro-motion feature is one of the effective features used for recognition at the middle section of the ballistic curve.Aimed at the problem that a single radar is rather limited in extracting micromotion information,this paper proposes a novel algorithm based on the narrowband radar network to extract precession features.First,a cone-shaped target model and a narrowband signal model are established.Then,each scattering point in different perspective is matched by frequency analysis based on transforming non-ideal scattering point into ideal scattering point.Finally,by using the micro-Doppler of conic node to compensate the bottom micro-Doppler of cone,compensation coefficient is solved when the radar aspect variance is minimal.Furthermore,parameters are obtained by combining the micro-Doppler of two radars.The simulation results show that the algorithm can extract micro-motion parameters and structured parameters accuracy.
Keywords：narrowband radar networkballistic targetsfrequency analysismicro-motionfeature extraction
Publication Date：2017-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：5( 47-51 )