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广义Pareto分布海杂波模型参数的组合双分位点估计方法

于涵 水鹏朗 施赛楠 杨春娇

引用本文: 于涵, 水鹏朗, 施赛楠, 杨春娇. 广义Pareto分布海杂波模型参数的组合双分位点估计方法[J]. 电子与信息学报, 2019, 41(12): 2836-2843. doi: 10.11999/JEIT190148 shu
Citation:  Han YU, Penglang SHUI, Sainan SHI, Chunjiao YANG. Combined Bipercentile Parameter Estimation of Generalized Pareto Distributed Sea Clutter Model[J]. Journal of Electronics and Information Technology, 2019, 41(12): 2836-2843. doi: 10.11999/JEIT190148 shu

广义Pareto分布海杂波模型参数的组合双分位点估计方法

    作者简介: 于涵: 女,1993年生,博士生,研究方向为海杂波特性分析等;
    水鹏朗: 男,1967年生,博士,教授,研究方向为多速率滤波器理论及应用、图像处理和雷达目标检测;
    施赛楠: 女,1990年生,博士,讲师,研究方向为雷达信号处理和微弱目标检测;
    杨春娇: 女,1993年生,硕士,研究方向为雷达目标检测等
    通讯作者: 于涵,hyu_5@stu.xidian.edu.cn
  • 基金项目: 国家自然科学基金(61871303)

摘要: 广义Pareto分布的复合高斯模型可以很好地描述高分辨低擦地角对海探测场景中海杂波的重拖尾特性,实现该杂波模型下双参数的有效估计对雷达检测性能具有重要意义。对此,该文提出一种双参数的组合双分位点(CBiP)估计方法。该估计方法基于低阶多项式方程的显式求根表达式,充分组合利用回波中的样本信息,旨在实现高精度的双参数估计过程。此外,考虑到实际雷达工作中存在岛礁、渔船等造成的功率异常大的野点样本时,不同于传统的矩估计、最大似然(ML)估计等方法,组合双分位点估计方法仍可保持估计性能的鲁棒性。仿真及实测数据实验表明,在纯杂波环境中,组合双分位点估计方法可以实现与最大似然估计方法近似的估计精度,若存在异常样本,组合双分位点估计方法的估计性能优于上述几种传统估计方法。

English

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  • 图 1  不同q值下CBiP方法估计误差与样本数N的关系

    图 2  5种估计方法的RRMSE及KSD值随着形状参数的变化曲线

    图 3  包含野点时5种估计方法的RRMSE及KSD值随着形状参数的变化曲线

    图 4  IPIX实测数据中5种估计方法的性能比较

    图 5  CSIR实测数据中5种估计方法的性能比较

    表 1  IPIX实测数据(19980206_195948_ANTSTEP)中5种估计方法的估计结果比较

    估计区域区域A纯杂波区域B 含野点区域C
    估计方法 MLCBiPFMoMMoMMLBiPCBiPFMoMMoMMLBiP
    形状参数9.12098.99679.61009.74439.41069.87348.48741.34002.02602.13858.0111
    尺度参数(×10–4)2.66492.60622.42522.38802.48242.36013.305031.00006.757916.00003.5223
    K-S距离2.6131×10–60.01340.01380.01410.01330.01650.01350.09990.24620.07560.0485
    下载: 导出CSV

    表 2  CSIR实测数据(TFA10_004.02)中5种估计方法的估计结果比较

    估计区域区域A纯杂波区域B 含野点区域C
    估计方法 MLCBiPFMoMMoMMLBiPCBiPFMoMMoMMLBiP
    形状参数4.57466.25656.29005.05494.70486.46374.20171.29002.02231.83143.8543
    尺度参数(×10–4)9.28776.43836.27298.07528.83596.243013.430160.085512.451236.923114.9068
    K-S距离3.6008×10–60.01110.01740.01050.00640.01260.09070.12130.20600.10600.0144
    下载: 导出CSV
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文章相关
  • 通讯作者:  于涵, hyu_5@stu.xidian.edu.cn
  • 收稿日期:  2019-03-14
  • 录用日期:  2019-08-12
  • 网络出版日期:  2019-09-03
  • 刊出日期:  2019-12-01
通讯作者: 陈斌, bchen63@163.com
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