电子与控制

一种解决时频不确定问题的长码捕获算法

  • 刘芳 ,
  • 冯永新
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  • 沈阳理工大学 信息科学与工程学院, 辽宁 沈阳 110159
刘芳 女,博士,副教授,硕士生导师。主要研究方向:扩频通信、信号处理。Tel:024-24682229 E-mail:zhqing1019@163.com;冯永新 女,博士,教授,博士生导师。主要研究方向:电子对抗,空间通信。Tel:024-24682018 E-mail:fengyongxin@263.net

收稿日期: 2012-10-02

  修回日期: 2013-04-13

  网络出版日期: 2013-05-27

基金资助

沈阳理工大学重点实验室开放基金;辽宁省高校创新团队计划(LT2011005);新世纪优秀人才支持计划(NCET-11-1013)

A Long Code Acquisition Algorithm on Resolve Time-frequency Uncertainty Problem

  • LIU Fang ,
  • FENG Yongxin
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  • School of Information Science and Engineering Shenyang Ligong University, Shenyang 110159, China

Received date: 2012-10-02

  Revised date: 2013-04-13

  Online published: 2013-05-27

Supported by

The Open Foundation of Key Laboratory of Shenyang Ligong University;Program for Liaoning Innovative Research Team in University (LT2011005);New Century Program for Excellent Talents of Ministry of Education of China (NCET-11-1013)

摘要

针对长周期伪码信号捕获中时频域的不确定问题,在理论模型分析的基础上,提出了一种长周期伪码捕获算法。该算法对接收信号进行时域混频及叠加处理,并转换到频域进行多次圆周移动,从而克服频偏引发的相关峰不确定问题;同时,通过连续积累和批处理手段克服了收发钟差引发的伪码时间不确定问题和信息翻转引发的相关峰不确定问题。理论分析和仿真结果表明:该算法在信噪比大于-25 dB的条件下,可以克服时频域的不解定问题;进一步,该算法与传统算法进行了比较,处理精度及处理复杂度都优于传统算法。

本文引用格式

刘芳 , 冯永新 . 一种解决时频不确定问题的长码捕获算法[J]. 航空学报, 2013 , 34(8) : 1924 -1933 . DOI: 10.7527/S1000-6893.2013.0218

Abstract

A long code acquisition algorithm was proposed to solve the uncertainty problems of long code signal acquisition in time-frequency domain, based on the theoretical model analysis. The technologies of time domain mixing and add were applied, and the technology of frequency domain circular moving was applied to overcome the correlation peak uncertainty problems caused by frequency deviation. At the same time, the technologies of continuous accumulating and batch processing were applied to resolve the pseudo-code time uncertainty problems caused by the transceiver clock error and the correlation peak uncertainty problems caused by data inversion. Theoretical analysis and simulation results show that the proposed algorithm can overcome the time-frequency domain uncertainty problem under the condition of larger than -25 dB. Further, the processing precision and complexity of the algorithm is better than the traditional algorithm.

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