CAJ | 학술논문

空时自适应处理是强杂波背景下动目标检测的有效途径，实际检测环境中训练样本与待检测单元背景统计特性的不一致将恶化处理器的输出信杂噪比，需要结合样本挑选技术来改善非均匀场景的处理器性能。在建立机载多通道信号模型基础上，提出一种利用极化信息辅助的空时自适应处理方法，该方法通过极化分类和功率分组指导训练样本选择，利用同类样本估计待检测单元的统计特性并计算自适应权矢量，具有杂波相关矩阵估计准确度高的特点，可显著改善动目标检测的性能。最后结合国外NASA JPL AIRSAR实测数据的多通道仿真实验验证了所提方法的有效性。
공시자괄응처리시강잡파배경하동목표검측적유효도경，실제검측배경중훈련양본여대검측단원배경통계특성적불일치장악화처리기적수출신잡조비，수요결합양본도선기술래개선비균균장경적처리기성능。재건립궤재다통도신호모형기출상，제출일충이용겁화신식보조적공시자괄응처리방법，해방법통과겁화분류화공솔분조지도훈련양본선택，이용동류양본고계대검측단원적통계특성병계산자괄응권시량，구유잡파상관구진고계준학도고적특점，가현저개선동목표검측적성능。최후결합국외NASA JPL AIRSAR실측수거적다통도방진실험험증료소제방법적유효성。
Space-time adaptive processing is an effective method to detect ground moving targets embedded in clutter envi-ronment ,and the estimation of clutter covariance matrix with training samples is required to perform the adaptive processing com-monly .In realistic environment ,the characteristics of clutter in the cell under test may be different with the training samples in other range cells ,which would reduce the precision of the estimated clutter covariance matrix .To improve the performance of target detec-tion ,a training sample selecting method based on polarized classification and power grouping is proposed in this paper ,which would improve the precision of the clutter covariance matrix .The simulation results demonstrate the effectiveness of the proposed method .