CAJ | 학술논문

　　以旋转周期估计为核心的微动特征提取技术是对空间自旋目标、空间碎片和弹头等目标进行成像和识别的基础，转速估计的精度直接影响成像和识别的结果。从旋转目标的窄带雷达散射机理出发，建立了旋转散射点的基频回波模型。针对旋转运动导致窄带回波是多分量SFM信号的特征，对多分量SFM信号的频谱进行了分析，根据其周期特征，提出了基于信号功率谱AMSF的微动特征提取算法。通过仿真验证了该算法在较低的信噪比下有较高的精度和稳定性。该方法有较强的应用前景。
　　이선전주기고계위핵심적미동특정제취기술시대공간자선목표、공간쇄편화탄두등목표진행성상화식별적기출，전속고계적정도직접영향성상화식별적결과。종선전목표적착대뢰체산사궤리출발，건립료선전산사점적기빈회파모형。침대선전운동도치착대회파시다분량SFM신호적특정，대다분량SFM신호적빈보진행료분석，근거기주기특정，제출료기우신호공솔보AMSF적미동특정제취산법。통과방진험증료해산법재교저적신조비하유교고적정도화은정성。해방법유교강적응용전경。
The technique of micro-motion characteristics extraction with the core of estimation of rotation period is a base for imaging and identification of spinning target, chips, warhead and other targets in space, the accuracy of rotating speed estimation would affect directly the results of imaging and identification. Starting from the narrow band radar scattering mechanism of rotating target, this paper brings forward a model for the fundamental frequency echo of rotation scattering points. In terms of the features that rotating motion results in narrow band echo being SFM signals with multiple components, the spectrum of SFM signals is analyzed, and the extraction algorithm of micro-motion characteristics based on signal power spectrum is proposed, on the basis of its period features. By simulation, it is proved that this proposed algorithm has a higher precision and stability, thus possessing a better application prospect.