欢迎访问《兵工学报》官方网站,今天是 分享到:

兵工学报 ›› 2014, Vol. 35 ›› Issue (9): 1363-1374.doi: 10.3969/j.issn.1000-1093.2014.09.006

• 论文 • 上一篇    下一篇

单通道多分量伪码复合线性调频信号分离及参数估计

朱航1,2, 张淑宁1, 赵惠昌1   

  1. (1.南京理工大学 电子工程与光电技术学院, 江苏 南京 210094;
  • 收稿日期:2013-12-16 修回日期:2013-12-16 上线日期:2014-11-03
  • 通讯作者: 朱航 E-mail:taochuhang@163.com
  • 作者简介:朱航(1987—)男博士研究生
  • 基金资助:
    国家自然科学基金项目(61301216); 国家部委预先研究项目(9140A05020212DQ0201)

Single Channel Source Separation and Parameters Estimation of Multi-component PRBC-LFM Signal

ZHU Hang1,2, ZHANG Shu-ning1, ZHAO Hui-chang1   

  1. (1.School of Electronic and Optical Engineering, Nanjing University of Science and Technology, Nanjing 210094, Jiangsu, China;2.Unit 73015 of PLA, Huzhou 313000, Zhejiang, China)
  • Received:2013-12-16 Revised:2013-12-16 Online:2014-11-03
  • Contact: ZHU Hang E-mail:taochuhang@163.com

摘要: 提出一种单通道内多分量伪码复合线性调频信号分离和参数提取方法。利用奇异值分解求得各分量重复周期,通过对信号求平方消除伪码对参数提取的影响,同时通过周期积累减小噪声及其余分量对待分离分量的干扰,对周期积累后的信号采用分数阶傅里叶变换(FRFT)和搜索方法估计信号调频率和载频。利用内积计算,估计分量信号的初始相位,利用伪码信号虚部为0的特性,估计出伪随机码序列及信号幅度。此外,还利用自相关矩阵特征值分解的方法估计了混合信号的信噪比,根据信噪比的不同,自适应地确定停止分解的阈值。在仿真与分析中,针对具体的信号说明了本方法的各步骤,并在不同信噪比条件下分析了该方法的有效性。

关键词: 兵器科学与技术, 多分量信号, 伪码复合线性调频信号, 参数提取, 信号分离, 自适应阈值

Abstract: A method of single channel source separation and parameters estimation of multi-component PRBC-LFM signal is proposed. The repetition period of each component can be estimated through singular value decomposition. The influence of the pseudo code on parameter extraction is eliminated through a square calculation of signal, and the interference of noise on the component under separation is reduced by cycle accumulating. The modulation rate and the carrier frequency are estimated by using FRFT and searching the discrete points. The initial phase of multi-component signal is determined by calculating the inner product, and then the pseudo random sequence and the signal amplitude are estimated by using the character of that the pseudo random sequence is a real signal. In addition, the proposed method is used to estimate SNR of mixed signal by using eigenvalue decomposition, and SNR can be used to determine the threshold adaptively. In simulation, the method is demonstrated by separating a specific signal. The result shows that the proposed method is effective under the condition of different SNRs.

Key words: ordnance science and technology, multi-component signal, PRBC-LFM signal, parameter extraction, source separation, adaptive threshold

中图分类号: