电子与控制

一种用于深空自主无线电的码速率估计算法

  • 宋青平 ,
  • 刘荣科
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  • 北京航空航天大学 电子信息工程学院, 北京 100191
宋青平 男, 博士研究生。主要研究方向: 深空通信, 自主无线电。 Tel: 010-82339715 E-mail: robert_nwpu@126.com

收稿日期: 2014-07-21

  修回日期: 2014-10-13

  网络出版日期: 2014-10-27

基金资助

国家"863"计划 (2012AA7014065); 新世纪优秀人才支持计划 (NCET-12-0030); 航天支撑技术基金

A symbol rate estimation algorithm for autonomous radio in deep space

  • SONG Qingping ,
  • LIU Rongke
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  • School of Electronic and Information Engineering, Beihang University, Beijing 100191, China

Received date: 2014-07-21

  Revised date: 2014-10-13

  Online published: 2014-10-27

Supported by

National High-tech Research and Development Program of China (2012AA7014065); Program for New Century Excellent Talents in University (NCET-12-0030); Astronautic Supporting Technology Foundation of China

摘要

针对深空自主无线电的码速率盲估计问题,在码元起始位置未知的情况下,通过对估计误差的理论分析,提出一种改进的基于分离符号矩估计(SSME)的码速率估计算法,设计分区估计信噪比(SNR)并进行比较选大的方法,以保证码速率估计的精度。同时对该算法的计算复杂度进行定量分析,并与传统单次延迟相乘法、改进的多次累加延迟相乘法进行比较。仿真结果表明,本文算法能够有效完成低SNR条件下的码速率估计,其误估计概率明显优于单次延迟相乘法,与多次累加延迟相乘法相当,但计算复杂度不到多次累加延迟相乘法的10%。

本文引用格式

宋青平 , 刘荣科 . 一种用于深空自主无线电的码速率估计算法[J]. 航空学报, 2015 , 36(7) : 2301 -2309 . DOI: 10.7527/S1000-6893.2014.0288

Abstract

The blind symbol rate estimation algorithms for autonomous radio in deep space are presented. In view of the unknown symbol starting point, an improved symbol rate estimation algorithm based on split-symbol moments estimator (SSME) is proposed according to the theoretical analysis of the estimation error. This new algorithm estimates the signal-to-noise ratio (SNR) in different ranges and selects the maximum value, which ensures the symbol rate estimation accuracy. In addition, the computational complexity of the new algorithm is compared with the conventional delay and multiply algorithm, improved delay and multiply algorithm with accumulations. The simulation results show that the proposed algorithm can effectively complete the task of symbol rate estimation at low SNR. Its symbol rate error estimation probability is lower than that of delay and multiply algorithm, and is close to that of delay and multiply algorithm with accumulations. However, the computational complexity of the new algorithm is less than 10% of that of delay and multiply algorithm with accumulations.

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