Exploiting HF ambient noise to synchronize distributed receivers

D. Hong, J. Krolik
{"title":"Exploiting HF ambient noise to synchronize distributed receivers","authors":"D. Hong, J. Krolik","doi":"10.1109/USNC-URSI-NRSM.2013.6525144","DOIUrl":null,"url":null,"abstract":"Coherent processing of data from distributed HF receivers requires the receivers to be synchronized to an accuracy within fractions of a wavelength. The HF band extends from 3 MHz to 30 MHz and has wavelengths corresponding to time delays ranging from approximately 33 ns to 333 ns. Thus the receivers must be synchronized to within a few nanoseconds. This is typically beyond the capabilities of even GPS-disciplined oscillators. Traditional clock synchronization methods require distributing a common reference signal to all the receivers, either by cables or by using a local reference transmitter. Both these approaches introduce extra cost and complexity. In this paper, we present an approach for clock synchronization which uses the coherent component of wideband ambient HF background noise to estimate time delays between receivers. The approach exploits the flexibility of inexpensive broadband direct-conversion digital receivers in the 3 - 30 MHz band. Two techniques are presented for measuring time delays between receivers: 1) Time-domain Green's Function estimator based on an approach recently used in underwater acoustics, and 2) an optimal Maximum Likelihood (ML) estimator. Both estimators are shown to choose the maximum of particular generalized cross correlations. The Camer-Rao Lower Bound (CRLB) for time delay estimation from ambient noise is also derived and simulation results are presented that demonstrate the performance of the estimators. For low signal to noise ratio (SNR) or low time-bandwidth product (TBP), the estimators do not achieve the CRLB due to peak ambiguities in the generalized cross correlations. However, for sufficiently large SNR and TBP, we demonstrate that the ML estimator is able to overcome the peak ambiguities and achieve the CRLB. In this case, the ML estimator is able to achieve sub-nanosecond RMS delay errors using a 2.5 s observation of 2 MHz bandwidth isotropic HF ambient noise. Thus the ML estimator is the preferred method for synchronizing the distributed receivers.","PeriodicalId":123571,"journal":{"name":"2013 US National Committee of URSI National Radio Science Meeting (USNC-URSI NRSM)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 US National Committee of URSI National Radio Science Meeting (USNC-URSI NRSM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/USNC-URSI-NRSM.2013.6525144","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Coherent processing of data from distributed HF receivers requires the receivers to be synchronized to an accuracy within fractions of a wavelength. The HF band extends from 3 MHz to 30 MHz and has wavelengths corresponding to time delays ranging from approximately 33 ns to 333 ns. Thus the receivers must be synchronized to within a few nanoseconds. This is typically beyond the capabilities of even GPS-disciplined oscillators. Traditional clock synchronization methods require distributing a common reference signal to all the receivers, either by cables or by using a local reference transmitter. Both these approaches introduce extra cost and complexity. In this paper, we present an approach for clock synchronization which uses the coherent component of wideband ambient HF background noise to estimate time delays between receivers. The approach exploits the flexibility of inexpensive broadband direct-conversion digital receivers in the 3 - 30 MHz band. Two techniques are presented for measuring time delays between receivers: 1) Time-domain Green's Function estimator based on an approach recently used in underwater acoustics, and 2) an optimal Maximum Likelihood (ML) estimator. Both estimators are shown to choose the maximum of particular generalized cross correlations. The Camer-Rao Lower Bound (CRLB) for time delay estimation from ambient noise is also derived and simulation results are presented that demonstrate the performance of the estimators. For low signal to noise ratio (SNR) or low time-bandwidth product (TBP), the estimators do not achieve the CRLB due to peak ambiguities in the generalized cross correlations. However, for sufficiently large SNR and TBP, we demonstrate that the ML estimator is able to overcome the peak ambiguities and achieve the CRLB. In this case, the ML estimator is able to achieve sub-nanosecond RMS delay errors using a 2.5 s observation of 2 MHz bandwidth isotropic HF ambient noise. Thus the ML estimator is the preferred method for synchronizing the distributed receivers.
利用高频环境噪声来同步分布式接收机
对来自分布式高频接收机的数据进行相干处理,要求接收机同步到一个波长范围内的精度。高频波段从3mhz延伸到30mhz,其波长对应于大约33ns到33ns的时间延迟。因此,接收器必须在几纳秒内同步到。这通常超出了gps规范振荡器的能力。传统的时钟同步方法需要通过电缆或使用本地参考发射机向所有接收器分配一个共同的参考信号。这两种方法都引入了额外的成本和复杂性。本文提出了一种利用宽带环境高频背景噪声的相干分量估计接收机间时延的时钟同步方法。该方法利用了3 - 30mhz频段廉价宽带直接转换数字接收机的灵活性。提出了两种测量接收机之间时延的技术:1)基于最近在水下声学中使用的方法的时域格林函数估计,以及2)最优最大似然(ML)估计。这两种估计量都可以选择特定广义互相关的最大值。本文还推导了用于环境噪声下时延估计的camera - rao下界(CRLB),并给出了仿真结果,验证了该估计器的性能。对于低信噪比(SNR)或低时间带宽积(TBP),由于广义相互关联中的峰值模糊性,估计器无法实现CRLB。然而,对于足够大的信噪比和TBP,我们证明了ML估计器能够克服峰值模糊并实现CRLB。在这种情况下,ML估计器能够使用2.5 s观察2mhz带宽各向同性高频环境噪声来实现亚纳秒的RMS延迟误差。因此,ML估计器是同步分布式接收器的首选方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信