基于智能学习的机载海杂波谱参数估计方法

TN957.51; 传统机载雷达海杂波的抑制方法在估计杂波功率谱时存在人工参与度高、误差大等问题,导致环境适应性较差.为此,提出一种基于智能学习的机载海杂波谱参数估计方法,建立基于一维LeNet-5的海杂波训练模型,并将仿真和实测海杂波数据输入训练好的模型后对功率谱的中心和宽度进行估计,进而实现海杂波谱特性的直接感知.实验结果表明,与传统方法相比,文中所提方法具有更高的估计精度以及更好的鲁棒性....

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Published in西北工业大学学报 Vol. 42; no. 3; pp. 446 - 452
Main Authors 范一飞, 王心宝, 粟嘉, 陶明亮, 陈明, 王伶
Format Journal Article
LanguageChinese
Published 西北工业大学电子信息学院,陕西西安 710072%杭州海康威视数字技术股份有限公司,浙江杭州 310051 01.06.2024
Subjects
海杂波
deep learning
参数估计
深度学习
doppler characteristics
parameters estimation
多普勒谱特性
sea clutter
Online AccessGet full text
ISSN1000-2758
DOI10.1051/jnwpu/20244230446

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Abstract TN957.51; 传统机载雷达海杂波的抑制方法在估计杂波功率谱时存在人工参与度高、误差大等问题,导致环境适应性较差.为此,提出一种基于智能学习的机载海杂波谱参数估计方法,建立基于一维LeNet-5的海杂波训练模型,并将仿真和实测海杂波数据输入训练好的模型后对功率谱的中心和宽度进行估计,进而实现海杂波谱特性的直接感知.实验结果表明,与传统方法相比,文中所提方法具有更高的估计精度以及更好的鲁棒性.
AbstractList TN957.51; 传统机载雷达海杂波的抑制方法在估计杂波功率谱时存在人工参与度高、误差大等问题,导致环境适应性较差.为此,提出一种基于智能学习的机载海杂波谱参数估计方法,建立基于一维LeNet-5的海杂波训练模型,并将仿真和实测海杂波数据输入训练好的模型后对功率谱的中心和宽度进行估计,进而实现海杂波谱特性的直接感知.实验结果表明,与传统方法相比,文中所提方法具有更高的估计精度以及更好的鲁棒性.
Abstract_FL Traditional airborne radar sea clutter suppression methods have a high degree of human participation and large errors in estimating the clutter power spectrum.With the development of modern signal processing and artificial intelligence,deep learning methods are used to study the sea clutter more quickly and intelligently.This paper proposes an airborne radar sea clutter spectrum parameter estimation method based on intelligent learning.It establishes a sea clutter training model based on the one-dimensional LeNet-5.Then the simulated and measured sea clutter data are input into the trained model to estimate the center and width of the power spectrum,thus realizing the direct perception of the sea clutter spectrum characteristics.The experimental results show that the proposed method has a higher estimation accuracy and better robustness than the traditional methods.
Author 王心宝
范一飞
陈明
粟嘉
王伶
陶明亮
AuthorAffiliation 西北工业大学电子信息学院,陕西西安 710072%杭州海康威视数字技术股份有限公司,浙江杭州 310051
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Author_FL WANG Ling
WANG Xinbao
CHEN Ming
SU Jia
TAO Mingliang
FAN Yifei
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Copyright Copyright © Wanfang Data Co. Ltd. All Rights Reserved.
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DocumentTitle_FL An airborne radar sea clutter spectrum parameters estimation method based on intelligent learning
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Keywords 海杂波
deep learning
参数估计
深度学习
doppler characteristics
parameters estimation
多普勒谱特性
sea clutter
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PublicationTitle 西北工业大学学报
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Publisher 西北工业大学电子信息学院,陕西西安 710072%杭州海康威视数字技术股份有限公司,浙江杭州 310051
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Snippet TN957.51; 传统机载雷达海杂波的抑制方法在估计杂波功率谱时存在人工参与度高、误差大等问题,导致环境适应性较差.为此,提出一种基于智能学习的机载海杂波谱参数估计方法,建...
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