高动态卫星DSSS信号Turbo迭代捕获算法

姜春晓; 王佳蔚

doi:10.11959/j.issn.1000-436x.2021153

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高动态卫星DSSS信号Turbo迭代捕获算法

专题：卫星通信技术 | 更新时间：2024-06-05

- 高动态卫星DSSS信号Turbo迭代捕获算法
- Turbo iterative acquisition algorithm for satellite high-mobility DSSS signal
- 通信学报 2021年42卷第8期页码：15-24
- 作者机构：
  
  1. 清华大学国家信息与科学技术研究中心，北京 100084
  2. 清华大学宇航中心，北京 100084
  3. 清华大学电子工程系，北京 100084
- 作者简介：
  
  [ "姜春晓（1987- ），男，河北邢台人，博士，清华大学副研究员，主要研究方向为卫星通信、空间通信网络等" ]
  [ "王佳蔚（1997- ），男，山东济南人，清华大学博士生，主要研究方向为信号处理、卫星通信、高动态通信等" ]
- 基金信息：
  
  国家重点研发计划基金资助项目(2020YFB1804800);国家自然科学基金资助项目(61922050)
- DOI：10.11959/j.issn.1000-436x.2021153
  中图分类号： TN914
- 网络首发：2021-08，
  
  纸质出版：2021-08-25
- 稿件说明：
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姜春晓, 王佳蔚. 高动态卫星DSSS信号Turbo迭代捕获算法[J]. 通信学报, 2021,42(8):15-24.

Chunxiao JIANG, Jiawei WANG. Turbo iterative acquisition algorithm for satellite high-mobility DSSS signal[J]. Journal on Communications, 2021, 42(8): 15-24.
姜春晓, 王佳蔚. 高动态卫星DSSS信号Turbo迭代捕获算法[J]. 通信学报, 2021,42(8):15-24. DOI： 10.11959/j.issn.1000-436x.2021153.

Chunxiao JIANG, Jiawei WANG. Turbo iterative acquisition algorithm for satellite high-mobility DSSS signal[J]. Journal on Communications, 2021, 42(8): 15-24. DOI： 10.11959/j.issn.1000-436x.2021153.

摘要

针对高动态卫星通信中捕获概率受限且计算复杂度大的问题，提出了高动态信号捕获的因子图模型，在模型中将时变多普勒变化率建模为随机游走模型，并进一步提出了Turbo双环迭代捕获算法。在多普勒消除环路中，通过消息传递的方式进行多普勒频偏和多普勒变化率的补偿以消除时变多普勒频偏的影响，同时在码字判决环路中，利用扩频序列码片间的约束关系从接收序列中恢复出发送序列，从而进行迭代判决。仿真结果表明，所提算法相比于传统算法在高动态环境下至少有1.3 dB的捕获性能提升，同时复杂度相对较低。

Abstract

To solve the problems of the low acquisition probability and high computational complexity in satellite high-mobility communications

a new factor graph was designed for acquisition of the high-mobility direct sequence spread spectrum (DSSS) signal

where time-varying Doppler rates were modeled by the random walk model.Based on the proposed factor graph

the turbo iterative DSSS signal acquisition algorithm was proposed.In the Doppler-estimation loop

the negative influence of Doppler frequency offsets and Doppler rates could be eliminated effectively.Then in the code-detection loop

constraints of each chip was used to recover the received signal

to achieve DSSS signal acquisition.Simulation results show that the proposed algorithm is capable of improving the acquisition performance at less 1.3 dB with low computational complexity.

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references

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