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强干扰环境下水声时延估计技术研究

李海鹏 孙大军 郑翠娥

李海鹏, 孙大军, 郑翠娥. 强干扰环境下水声时延估计技术研究[J]. 电子与信息学报, 2021, 43(3): 873-880. doi: 10.11999/JEIT200638
引用本文: 李海鹏, 孙大军, 郑翠娥. 强干扰环境下水声时延估计技术研究[J]. 电子与信息学报, 2021, 43(3): 873-880. doi: 10.11999/JEIT200638
Haipeng LI, Dajun SUN, Cui’e ZHENG. Time of Arrival Estimation in Presence of Strong Interference[J]. Journal of Electronics and Information Technology, 2021, 43(3): 873-880. doi: 10.11999/JEIT200638
Citation: Haipeng LI, Dajun SUN, Cui’e ZHENG. Time of Arrival Estimation in Presence of Strong Interference[J]. Journal of Electronics and Information Technology, 2021, 43(3): 873-880. doi: 10.11999/JEIT200638

强干扰环境下水声时延估计技术研究

doi: 10.11999/JEIT200638
基金项目: 国家自然科学基金(61701132),黑龙江省自然科学基金(YQ2019D003, JC2016013)
详细信息
    作者简介:

    李海鹏:男,1991年生,博士生,研究方向为水声定位与导航

    孙大军:男,1972年生,教授,研究方向为水声定位与导航、水声探测

    郑翠娥:女,1982年生,副教授,研究方向为水声定位与导航、信号处理

    通讯作者:

    孙大军 sundajunmail@163.com

  • 中图分类号: TN911.4

Time of Arrival Estimation in Presence of Strong Interference

Funds: The National Natural Science Foundation of China (61701132), The Natural Science Foundation of Heilongjiang Province (YQ2019D003, JC2016013)
  • 摘要: 水声定位系统是现代深海作业必备的高精度水下定位装备,精确的时延估计是实现高精度水声定位的基础,但由于信号远距离传输以及强干扰的影响,水声定位系统时延估计精度较低。针对此问题该文提出一种基于子空间理论的宽带强干扰抑制方法,首先通过贝叶斯信息量准则估计子空间维度,然后推导了不同信号假设下的概率密度函数,求解未知参数的最大似然估计,构造广义似然比并通过最优匹配广义似然比检测法估计与期望信号最匹配的子空间,然后以此构造空间投影算子对接收数据进行线性投影,最终抑制干扰和噪声,提高时延估计精度。仿真结果表明该方法能够有效抑制干扰和噪声的影响,提高定位系统时延估计精度。
  • 图  1  子空间及其投影关系示意图

    图  2  定位系统接收基阵阵型图

    图  3  相关时延估计随SINR的变化

    图  4  基阵1号基元接收信号

    图  5  广义似然比在角度空间内的搜索结果

    图  6  广义似然比随入射角度变化图

    图  7  时延估计误差随SINR变化图,INR=0 dB

    图  8  时延估计误差随SINR变化图,INR=20 dB

    图  9  时延估计误差随SINR变化图,INR=50 dB

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出版历程
  • 收稿日期:  2020-07-30
  • 修回日期:  2020-12-18
  • 网络出版日期:  2020-12-28
  • 刊出日期:  2021-03-22

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