Research on ELoran Demodulation Algorithm Based on Multiclass Support Vector Machine

被引:2
作者
Liu, Shiyao [1 ,2 ]
Yan, Baorong [1 ,2 ]
Guo, Wei [1 ,2 ]
Hua, Yu [1 ,2 ]
Zhang, Shougang [1 ,3 ,4 ]
Lu, Jun [5 ]
Xu, Lu [5 ]
Yang, Dong [6 ]
机构
[1] Chinese Acad Sci, Natl Time Serv Ctr, Xian 710600, Peoples R China
[2] Chinese Acad Sci, Key Lab Precise Positioning & Timing Technol, Xian 710600, Peoples R China
[3] Univ Chinese Acad Sci, Beijing 100039, Peoples R China
[4] Chinese Acad Sci, Key Lab Time & Frequency Stand, Xian 710600, Peoples R China
[5] Chengdu Univ Informat Technol, Sch Software Engn, Chengdu 610225, Peoples R China
[6] Sichuan Meteorol Serv Ctr, Chengdu 610072, Peoples R China
关键词
eLoran; demodulation; multiclass support vector machine; machine learning; RANDOM FOREST CLASSIFIER; LORAN DATA MODULATION;
D O I
10.3390/rs16173349
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Demodulation and decoding are pivotal for the eLoran system's timing and information transmission capabilities. This paper proposes a novel demodulation algorithm leveraging a multiclass support vector machine (MSVM) for pulse position modulation (PPM) of eLoran signals. Firstly, the existing demodulation method based on envelope phase detection (EPD) technology is reviewed, highlighting its limitations. Secondly, a detailed exposition of the MSVM algorithm is presented, demonstrating its theoretical foundations and comparative advantages over the traditional method and several other methods proposed in this study. Subsequently, through comprehensive experiments, the algorithm parameters are optimized, and the parallel comparison of different demodulation methods is carried out in various complex environments. The test results show that the MSVM algorithm is significantly superior to traditional methods and other kinds of machine learning algorithms in demodulation accuracy and stability, particularly in high-noise and -interference scenarios. This innovative algorithm not only broadens the design approach for eLoran receivers but also fully meets the high-precision timing service requirements of the eLoran system.
引用
收藏
页数:20
相关论文
共 50 条
  • [41] A feedforward method based on support vector machine
    Mao, Yao
    He, Qiunong
    Zhou, Xi
    Li, Zhijun
    Liu, Qiong
    Zhang, Chao
    2018 CHINESE AUTOMATION CONGRESS (CAC), 2018, : 2259 - 2264
  • [42] Development of machine vision-based ore classification model using support vector machine (SVM) algorithm
    Ashok Kumar Patel
    Snehamoy Chatterjee
    Amit Kumar Gorai
    Arabian Journal of Geosciences, 2017, 10
  • [43] Odor detecting algorithm with boundary compensation support vector machine
    Ogawa, Keishiro
    Inoue, Katsufumi
    Yoshioka, Michifumi
    Yanagimoto, Hidekazu
    IEEJ Transactions on Electronics, Information and Systems, 2015, 135 (07) : 920 - 926
  • [44] Development of machine vision-based ore classification model using support vector machine (SVM) algorithm
    Patel, Ashok Kumar
    Chatterjee, Snehamoy
    Gorai, Amit Kumar
    ARABIAN JOURNAL OF GEOSCIENCES, 2017, 10 (05)
  • [45] LEARNING DAGS USING MULTICLASS SUPPORT VECTOR MACHINES
    Nikolay, Fabio
    Pesavento, Marius
    2018 IEEE STATISTICAL SIGNAL PROCESSING WORKSHOP (SSP), 2018, : 75 - 79
  • [46] Support vector machine parallelized remote sensing image classification algorithm based on big data
    Liao, Li
    JOURNAL OF ELECTRONIC IMAGING, 2022, 31 (06) : 62005
  • [47] An Optimization Algorithm for Computer-Aided Diagnosis of Breast Cancer Based on Support Vector Machine
    Dou, Yifeng
    Meng, Wentao
    FRONTIERS IN BIOENGINEERING AND BIOTECHNOLOGY, 2021, 9
  • [48] Mutation probability of cytochrome P450 based on a genetic algorithm and support vector machine
    Yao, Yu
    Zhang, Tao
    Xiong, Yi
    Li, Li
    Huo, Juan
    Wei, Dong-Qing
    BIOTECHNOLOGY JOURNAL, 2011, 6 (11) : 1367 - 1376
  • [49] A Novel Support-Vector-Machine-Based Grasshopper Optimization Algorithm for Structural Reliability Analysis
    Yang, Yutai
    Sun, Weizhe
    Su, Guoshao
    BUILDINGS, 2022, 12 (06)
  • [50] Misalignment Detection of a Rotating Machine Shaft Using a Support Vector Machine Learning Algorithm
    Lee, Yong Eun
    Kim, Bok-Kyung
    Bae, Jun-Hee
    Kim, Kyung Chun
    INTERNATIONAL JOURNAL OF PRECISION ENGINEERING AND MANUFACTURING, 2021, 22 (03) : 409 - 416