Research on ELoran Demodulation Algorithm Based on Multiclass Support Vector Machine

IF 4.2 2区 地球科学 Q2 ENVIRONMENTAL SCIENCES Remote Sensing Pub Date : 2024-09-09 DOI:10.3390/rs16173349
Shiyao Liu, Baorong Yan, Wei Guo, Yu Hua, Shougang Zhang, Jun Lu, Lu Xu, Dong Yang
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Abstract

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.
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基于多类支持向量机的 ELoran 解调算法研究
解调和解码对 eLoran 系统的定时和信息传输能力至关重要。本文针对 eLoran 信号的脉冲位置调制(PPM),提出了一种利用多类支持向量机(MSVM)的新型解调算法。首先,回顾了基于包络相位检测(EPD)技术的现有解调方法,强调了其局限性。其次,详细阐述了 MSVM 算法,展示了其理论基础以及与传统方法和本研究提出的其他几种方法相比的优势。随后,通过综合实验,对算法参数进行了优化,并在各种复杂环境下对不同的解调方法进行了并行比较。测试结果表明,MSVM 算法在解调精度和稳定性方面明显优于传统方法和其他类型的机器学习算法,尤其是在高噪声和高干扰场景下。这一创新算法不仅拓宽了 eLoran 接收机的设计思路,而且完全满足了 eLoran 系统对高精度授时服务的要求。
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来源期刊
Remote Sensing
Remote Sensing REMOTE SENSING-
CiteScore
8.30
自引率
24.00%
发文量
5435
审稿时长
20.66 days
期刊介绍: Remote Sensing (ISSN 2072-4292) publishes regular research papers, reviews, letters and communications covering all aspects of the remote sensing process, from instrument design and signal processing to the retrieval of geophysical parameters and their application in geosciences. Our aim is to encourage scientists to publish experimental, theoretical and computational results in as much detail as possible so that results can be easily reproduced. There is no restriction on the length of the papers. The full experimental details must be provided so that the results can be reproduced.
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