CAJ | 학술논문

在使用低频超宽带合成孔径雷达（UWB-SAR）对地雷进行探测的过程中，根据目标电磁散射随方位角和入射角的变化特性，提出一种利用双峰间距和频率凹点特征沿方位向变化的隐马尔科夫模型（HMM）鉴别算法。该算法首先针对目标感兴趣区域（ROI）图像估计其各方位回波响应，然后利用时频原子提取时域双峰间距和频率凹点，进而得到随方位角变化的特征序列，再通过 SAR 工作时方位角和入射角的变化特点以及训练样本确定 HMM参数，并在此基础上计算疑似目标新的特征矢量，采用马氏距离进行判别。实验结果表明了本文所提方法在目标鉴别方面的有效性。
재사용저빈초관대합성공경뢰체（UWB-SAR）대지뢰진행탐측적과정중，근거목표전자산사수방위각화입사각적변화특성，제출일충이용쌍봉간거화빈솔요점특정연방위향변화적은마이과부모형（HMM）감별산법。해산법수선침대목표감흥취구역（ROI）도상고계기각방위회파향응，연후이용시빈원자제취시역쌍봉간거화빈솔요점，진이득도수방위각변화적특정서렬，재통과 SAR 공작시방위각화입사각적변화특점이급훈련양본학정 HMM삼수，병재차기출상계산의사목표신적특정시량，채용마씨거리진행판별。실험결과표명료본문소제방법재목표감별방면적유효성。
Low-frequency ultra-wideband synthetic aperture radar (UWB-SAR)is a promising technology for landmine detection.According to the scattering characteristics of body-of-revolution (BOR)targets along with azimuth angles and incident angles,a Hidden Markov model (HMM)discrimination algorithm is proposed,using such sequential features as double-hump distance and notch frequency.First,the algorithm estimated the target scatterings in all azimuths based on regions of interest (ROI).Second,sequential aspect features were extracted by sparse time-frequency representation.Then the HMMparameters were trained with the labeled samples and the probability of occurrence was computed to discriminate suspicions targets.The experimental results indicate that the proposed algorithm is effective in BOR target discrimination.