CAJ | 학술논문

主波束中的车辆回波信号会污染空时自适应处理(STAP)的训练样本，导致空时自适应处理时的目标自相消，引起漏警。针对这一问题，该文提出一种基于道路信息的知识辅助(KA)空时自适应处理方法。该方法首先根据主波束中道路相对于雷达的位置估计道路上车辆相对于雷达的径向速度，然后得到可能含有主波束车辆回波信号的距离-多普勒单元，接着根据训练样本与杂波导向矢量和主波束导向矢量的匹配程度判断这些训练样本是否包含主波束车辆回波信号，最后在进行空时自适应处理估计杂波协方差矩阵时剔除被主波束车辆回波信号污染的训练样本。理论分析及实验结果表明该方法可以提高道路密集环境中空时自适应处理的信杂噪比输出，改善空时自适应处理雷达的性能。
주파속중적차량회파신호회오염공시자괄응처리(STAP)적훈련양본，도치공시자괄응처리시적목표자상소，인기루경。침대저일문제，해문제출일충기우도로신식적지식보조(KA)공시자괄응처리방법。해방법수선근거주파속중도로상대우뢰체적위치고계도로상차량상대우뢰체적경향속도，연후득도가능함유주파속차량회파신호적거리-다보륵단원，접착근거훈련양본여잡파도향시량화주파속도향시량적필배정도판단저사훈련양본시부포함주파속차량회파신호，최후재진행공시자괄응처리고계잡파협방차구진시척제피주파속차량회파신호오염적훈련양본。이론분석급실험결과표명해방법가이제고도로밀집배경중공시자괄응처리적신잡조비수출，개선공시자괄응처리뢰체적성능。
The echo of the vehicle from the main lobe may contaminate the training samples of Space Time Adaptive Processing (STAP), which results in target self nulling effect, and therefore degrades the probability of detection. To mitigate this problem, this paper proposes a Knowledge Aided (KA) STAP which is based on the road network data to select the training samples. This study firstly estimates the radial velocity of vehicle to the radar; then the range-Doppler cells which may contain vehicle echo are obtained according to the velocity; in the following, this study distinguish whether the training samples contain vehicle echo according to the matching degree of the training samples with the steering vector of the main lobe and the clutter; finally, the samples containing vehicle echo are discarded when the covariance matrix for the STAP is estimated. The theory analysis and experimental results illustrate that the proposed method advances the output of signal to clutter plus noise ratio, and improves the performance of STAP in the road network environments.