Demodulation Method for Starlink Signals Based on Correlation and Clustering

WU Chao; LI Li; LI Yafeng; JIANG Cheng; CAO Yan; HU Miao; ZHAO Yinan

doi:10.12263/DZXB.20250796

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Demodulation Method for Starlink Signals Based on Correlation and Clustering

PAPERS | 更新时间：2026-07-30

- Demodulation Method for Starlink Signals Based on Correlation and Clustering
- ACTA ELECTRONICA SINICA Vol. 54, Issue 4, Pages: 1857-1871(2026)
- 作者机构：
  
  1.杭州电子科技大学通信工程学院，浙江杭州 310018
  2.北京信息科技大学自动化学院，北京 100192
  3.北京邮电大学信息与通信工程学院，北京 100876
  4.北京中天飞创电子技术有限公司，北京 100080
- 作者简介：
- 基金信息：
  
  National Natural Science Foundation of China(61901154);Natural Science Foundation of Zhejiang Province, China(LQ19F010006);Open Fund Project of National Key Laboratory of Inertial Measurement(KFJI2024005)
- DOI：10.12263/DZXB.20250796
  CLC： TN911.72;TN967.1
- Received：12 September 2025，
  
  Accepted：01 April 2026，
  
  Online First：22 May 2026，
  
  Published：25 April 2026
- 稿件说明：
移动端阅览
吴超, 李力, 李亚峰, 等. 基于相关-聚类的星链信号解调方法[J]. 电子学报, 2026, 54(04): 1857-1871.

WU Chao, LI Li, LI Yafeng, et al. Demodulation Method for Starlink Signals Based on Correlation and Clustering[J]. Acta Electronica Sinica, 2026, 54(04): 1857-1871.
吴超, 李力, 李亚峰, 等. 基于相关-聚类的星链信号解调方法[J]. 电子学报, 2026, 54(04): 1857-1871. DOI：10.12263/DZXB.20250796

WU Chao, LI Li, LI Yafeng, et al. Demodulation Method for Starlink Signals Based on Correlation and Clustering[J]. Acta Electronica Sinica, 2026, 54(04): 1857-1871. DOI：10.12263/DZXB.20250796

摘要

随着巨型低轨卫星（Low Earth Orbit，LEO）星座的迅速发展，大量星基机会信号为全球导航卫星系统（Global Navigation Satellite System，GNSS）拒止条件下的辅助与替代性导航需求提供了潜在解决方案。以星链信号为例，对其进行时频估计并完成有效解调，是实现辅助导航的必要前提。然而，星链卫星的高速运动引起显著的多普勒效应，为信号时频估计精度与可靠解调带来技术挑战。针对现有的时频估计算法在低信噪比（Signal-to-Noise Ratio，SNR）条件下鲁棒性不足，传统算法在高动态环境下难以实现稳定解调的问题，本文提出了一种基于相关-聚类的星链信号解调方法，并在仿真与实测数据上进行实验验证。利用星链下行信号特殊的同步序列结构，设计相关性增强的延迟自相关定时算法与改进的符号内相位差频偏估计算法，实现同步序列定时与多普勒系数的粗估计。提出基于K-means聚类的逐符号时频精估计方法，在无数据符号先验的条件下提取星座聚类统计量，并以经验信噪比（Empirical Signal-to-Noise Ratio，ESNR）最大化为准则完成残余时频误差精估计。构建仿真场景，分析所提方法的收敛性与估计精度，并基于实测星链下行信号，以解调误比特率（Bit Error Rate，BER）为指标评估所提算法的性能。实验结果表明，所提方法在高动态条件下具有良好的收敛性与估计精度，且在7.3 dB SNR实测数据下，解调BER为0.88%，相较对比算法降低55.10%，在高动态环境下显著提升了时频估计与解调的精度，为星链机会信号导航提供了技术支撑。

Abstract

With the rapid development of mega low earth orbit (LEO) satellite constellations

an abundance of signals of opportunity have emerged as potential solutions for assisting global navigation satellite system (GNSS) navigation in GNSS-denied environments. Taking Starlink signals as a representative example

accurate time-frequency estimation and reliable demodulation are essential prerequisites for navigation applications. However

the high dynamics of LEO satellites introduce severe Doppler effects

which challenge the accuracy and robustness of time-frequency estimation and the reliability of demodulation. To address the lack of robustness of existing time-frequency estimation algorithms under low signal-to-noise ratio (SNR) conditions and the instability of traditional methods in high-dynamic environments

this paper proposes a demodulation method for Starlink signals based on correlation and clustering

and validates it through both simulation analysis and real captured downlink signals. By exploiting the unique synchronization sequence structure of Starlink signals

a delayed autocorrelation method with enhanced correlation structure and an improved intra-symbol phase difference algorithm are designed to achieve synchronization sequence detection and coarse Doppler estimation. A symbol-by-symbol fine time-frequency estimation method based on K-means clustering is proposed. Under a non-data-aided condition

constellation clustering statistics are extracted

and the residual time-frequency errors are estimated by maximizing the empirical signal-to-noise ratio (ESNR). Simulation scenarios are constructed to analyze the convergence behavior and estimation accuracy of the proposed method. Furthermore

real captured Starlink downlink signals are employed to evaluate the algorithm performance in terms of bit error rate (BER). Experimental results demonstrate robust convergence and improved estimation accuracy under high-dynamic conditions. For real captured downlink data at 7.3 dB SNR

the proposed method reduces BER by 55.10% compared with baseline methods

enabling more reliable demodulation and supporting Starlink-based assisted navigation.

关键词

Keywords

references

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