CAJ | 학술논문

SAR微动信息能够反映出目标的属性信息，其微动图像可作为雷达目标识别的一种重要手段。基于SAR微动目标回波的稀疏特性，建立了在过完备词典下的稀疏表示模型，提出一种新的稀疏贝叶斯重构方法———方差成分扩张压缩，该方法仅赋予有重要意义的信号元素不同的方差分量，拥有更少的参数。仿真结果表明，方差成分扩张压缩方法能较精确地估计出SAR目标微动参数，同时能够获得低信噪比条件下较好的微动目标像。
SAR미동신식능구반영출목표적속성신식，기미동도상가작위뢰체목표식별적일충중요수단。기우SAR미동목표회파적희소특성，건립료재과완비사전하적희소표시모형，제출일충신적희소패협사중구방법———방차성분확장압축，해방법부부여유중요의의적신호원소불동적방차분량，옹유경소적삼수。방진결과표명，방차성분확장압축방법능교정학지고계출SAR목표미동삼수，동시능구획득저신조비조건하교호적미동목표상。
The micro motion target image of SAR can be used in radar target recognition since it can reflect the attribute of target information. Based on the fact that the SAR echo of the micro motion target is sparse,the sparse signal representation was established under an over-complete dictionary.A new sparse Bayesian learning named expansion-compression variance-component based method was employed,which only assigns the distinct variance components to the significant signal elements.In addition,the expansion-compression variance-component based method has much less parameters.The imaging results of SAR micro motion target can estimate the micro motion parameter better,and achieve the fine SAR micro motion image under the low signal to noise ratio.