引用本文: | 赵宜楠,王军,尹彬.使用极化知识的非均匀杂波数据选择器[J].哈尔滨工业大学学报,2013,45(3):28.DOI:10.11918/j.issn.0367-6234.2013.03.005 |
| ZHAO Yinan,WANG Jun,YIN Bin
.A data selector in nonhomogeneous clutter using polarization knowledge[J].Journal of Harbin Institute of Technology,2013,45(3):28.DOI:10.11918/j.issn.0367-6234.2013.03.005 |
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摘要: |
为了解决雷达自适应处理中由于杂波的非均匀所带来的性能恶化问题,提出了一种基于极化特征知识的非均匀复合高斯杂波训练数据选择方法.该方法对训练数据单元进行极化散射矩阵的最大似然估计,然后计算每个估计值与先验极化知识的误差,以此作为区分野值的特征,从非均匀杂波中去除野值得到均匀的训练数据.仿真结果表明,该方法在野值杂波比较低时仍能够有效地去除野值,改善了杂波协方差矩阵的估计性能. |
关键词: 极化 数据选择 最大似然估计 先验知识 |
DOI:10.11918/j.issn.0367-6234.2013.03.005 |
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基金项目:山东省自然科学基金资助项目(ZR2012FQ007);哈尔滨工业大学创新基金资助项目(HIT.NSRIF.2011118). |
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A data selector in nonhomogeneous clutter using polarization knowledge |
ZHAO Yinan, WANG Jun, YIN Bin
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(School of Electronics and Information Engineering, Harbin Institute of Technology, 150001 Harbin, China)
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Abstract: |
To solve the problem of performance degradation due to nonhomogeneous clutter in adaptive radar processing, a new training data selector in non-homogeneous compound-Gaussian clutter based on polarization knowledge was proposed. The polarization scatting matrix of every training sample was estimated using maximum likelihood estimation (MLE) method, and then the error between the estimation and prior polarization knowledge was used to remove outliers from training data. The performance of the knowledge-based algorithm was analyzed on simulated radar data. The results show that the new data selector removes outliers effectively when outlier-clutter ratio is low and achieves a satisfactory performance level for the estimation of clutter covariance matrix. |
Key words: polarization data selection maximum likelihood estimation prior knowledge
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