国产欧美精品一区二区,中文字幕专区在线亚洲,国产精品美女网站在线观看,艾秋果冻传媒2021精品,在线免费一区二区,久久久久久青草大香综合精品,日韩美aaa特级毛片,欧美成人精品午夜免费影视

基于深度學(xué)習的智能化高精度測向方法
DOI:
CSTR:
作者:
作者單位:

中國電子科技集團公司第五十四研究所

作者簡(jiǎn)介:

通訊作者:

中圖分類(lèi)號:

TN959

基金項目:

國家自然科學(xué)基金(U19B2028)


Intelligent high accuracy direction finding method based on deep learning
Author:
Affiliation:

Fund Project:

  • 摘要
  • |
  • 圖/表
  • |
  • 訪(fǎng)問(wèn)統計
  • |
  • 參考文獻
  • |
  • 相似文獻
  • |
  • 引證文獻
  • |
  • 資源附件
  • |
  • 文章評論
    摘要:

    提出了一種基于深度學(xué)習的智能化高精度快速波達方向(DOA)估計算法,根據神經(jīng)網(wǎng)絡(luò )通過(guò)數據驅動(dòng)而不依賴(lài)陣列流型的特點(diǎn),設計了基于卷積神經(jīng)網(wǎng)絡(luò )的PhaseDOA-Net回歸網(wǎng)絡(luò )模型實(shí)現估計算法,引入特定模塊對輸入信號進(jìn)行特征提取和處理,提高網(wǎng)絡(luò )模型的擬合效果,用所提網(wǎng)絡(luò )模型自主學(xué)習相位差矩陣與DOA之間的映射關(guān)系;引入殘差網(wǎng)絡(luò )結構,解決了卷積神經(jīng)網(wǎng)絡(luò )層數加深導致網(wǎng)絡(luò )退化的問(wèn)題;仿真生成了具有噪聲與幅相誤差的信號數據集,并構建信號相位差矩陣作為輸入;仿真結果表明,本算法可以提供更高精度的估計性能,大幅減小了估計時(shí)間,解決了現有方法在陣列模型誤差條件下無(wú)法準確得到DOA結果的問(wèn)題;通過(guò)基于實(shí)際信號環(huán)境中采集數據的訓練與測試,驗證了系統對不同噪聲、幅相誤差的魯棒性以及對不同信號頻率更好的適應能力。

    Abstract:

    An intelligent high accuracy fast direction of arrival(DOA)estimation algorithm based on deep learning is proposed. According to the characteristics of neural network driven by data and independent of array flow pattern,the PhaseDOA-Net regression network model based on convolutional neural network(CNN)is designed, and the residual network structure is introduced to solve the problem of network degradation caused by layer deepening of CNN.Specific modules are designed to extract and process the festures of the input signals,which improves the fitting effect of the networt model.The proposed network model is used to autonomously learn the mapping relationship between the phase difference matrix and DOA.The residual network structure is introduced to solve the problem of network degradation caused by layer deepening of CNN.The data sets with noise and amplitued-phase errors is generated by simulation,and the signal phase difference matrix is constructed as network input.The simulation results show that the algorithm can provide higher accuracy estimation performance, greatly reduce the estimation time, and solve the problems of the existing methods which cannot accurately obtain DOA results under the condition of array model error.Through the training and testing based on the collected data in the actual signal environment,the robustness of the system to different noises,amplitude-phase errors and the great adaptability to different signal frequencies are verified.

    參考文獻
    相似文獻
    引證文獻
引用本文

趙偉豪,張君毅,李淳.基于深度學(xué)習的智能化高精度測向方法計算機測量與控制[J].,2023,31(1):15-21.

復制
分享
文章指標
  • 點(diǎn)擊次數:
  • 下載次數:
  • HTML閱讀次數:
  • 引用次數:
歷史
  • 收稿日期:2022-10-13
  • 最后修改日期:2022-10-26
  • 錄用日期:2022-10-26
  • 在線(xiàn)發(fā)布日期: 2023-01-16
  • 出版日期:
文章二維碼
隆林| 鹤壁市| 台北市| 杭州市| 万载县| 阜康市| 大新县| 余姚市| 南溪县| 遂平县| 读书| 中宁县| 枣强县| 徐闻县| 图木舒克市| 武宣县| 彩票| 湄潭县| 潼关县| 靖江市| 建始县| 淳安县| 巩义市| 四会市| 吉隆县| 冕宁县| 华阴市| 宁南县| 林州市| 浦江县| 元江| 霍邱县| 贡觉县| 蒙阴县| 方山县| 洱源县| 台安县| 成武县| 泗洪县| 湟源县| 望谟县|