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

doi:10.11999/JEIT200638

强干扰环境下水声时延估计技术研究

doi: 10.11999/JEIT200638

1.
哈尔滨工程大学水声技术重点实验室哈尔滨 150001
2.
海洋信息获取与安全工信部重点实验室(哈尔滨工程大学) 哈尔滨 150001
3.
哈尔滨工程大学水声工程学院哈尔滨 150001

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
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- 被引次数: 0
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

Time of Arrival Estimation in Presence of Strong Interference

1.
Acoustic Science and Technology Laboratory, Harbin Engineering University, Harbin 150001, China
2.
Key Laboratory of Marine Information Acquisition and Security (Harbin Engineering University), Ministry of Industry and Information Technology, Harbin 150001, China
3.
College of Underwater Acoustic Engineering, Harbin Engineering University, Harbin 150001, China

Funds: The National Natural Science Foundation of China (61701132), The Natural Science Foundation of Heilongjiang Province (YQ2019D003, JC2016013)

摘要

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。
- 水声时延估计 /
- 子空间 /
- 最大似然估计 /
- 广义似然比
Abstract: The underwater positioning system is the essential and necessary equipment for modern deep-sea operations. Accurate time delay estimation is the basis for achieving high-precision localization. However, the performance of time delay estimation will decrease due to the long-distance transmission and strong clutter. To solve this problem, a novel interference suppression method based on the subspace theory is proposed. The dimension of the subspace is estimated using Bayesian information criterion at first, and the probability density function under different assumptions are then derived by estimating the unknown parameters to construct the generalized likelihood ratio. Finally, the most suitable subspace may be estimated using the optimal matching generalized likelihood ratio detection method. The projection operator is constructed to linearly project the received data, suppressing the interference and noise as a result of improving the accuracy of time delay estimation. The simulation results show that the proposed method can effectively suppress the influence of the clutter and improve the estimation accuracy of the time-delay.
- Underwater acoustic time of arrival estimation /
- Subspace /
- Maximum likelihood estimation /
- General likelihood radio

HTML全文

图 1 子空间及其投影关系示意图

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图 2 定位系统接收基阵阵型图

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图 3 相关时延估计随SINR的变化

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图 4 基阵1号基元接收信号

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图 5 广义似然比在角度空间内的搜索结果

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图 6 广义似然比随入射角度变化图

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图 7 时延估计误差随SINR变化图，INR=0 dB

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图 8 时延估计误差随SINR变化图，INR=20 dB

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图 9 时延估计误差随SINR变化图，INR=50 dB

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