罗兰C周期识别的 Wigner-Vill 变换分析

朱银兵; 许江宁; 曹可劲; 崔国恒

doi:10.15892/j.cnki.djzdxb.2010.02.056

2010 , Vol. 30 >Issue 2: 211 - 214

DOI: https://doi.org/10.15892/j.cnki.djzdxb.2010.02.056

摘要

为了改善时域或频域分析的局限性,提高罗兰C的周期识别能力,在分析罗兰C信号的Wigner-Vill变换特征基础上,仿真分析了样本长度、天线输入端信噪比、天地波幅值比及天地波相位差等对罗兰C周期识别的影响。结果表明,罗兰C信号的Wigner-Vill变换峰值稳定､抗噪声性能强,利用不同天地波相位差下罗兰C信号的Wigner-Vill变换最小峰值对应的频率点不同,能够有效的实现罗兰C信号的周期识别。

关键词： 罗兰C; 周期识别; Wigner-Vill 变换

本文引用格式

朱银兵 , 许江宁 , 曹可劲 , 崔国恒 . 罗兰C周期识别的 Wigner-Vill 变换分析[J]. 弹箭与制导学报, 2010 , 30(2) : 211 -214 . DOI: 10.15892/j.cnki.djzdxb.2010.02.056

Abstract

For improving the limit of time domain or frequency domain analysis and the cycle identification capability for Loran-C, the effect of swatch's length, signal-to-noise ratio(SNR) at the antenna input, sky-wave to ground-wave ratio(SGR) and phase difference of sky wave to ground-wave on cycle identification of Loran-C were analyzed and simulated based on the analysis of Loran-C signal's Wigner-Vill transformation(WVT) characters. The results show that positive peak values of Loran-C signal's WVT are steady, the transformation has good anti-noise performance, and cycle identification can be realized successfully and effectively because the frequency points corresponding to the negative peak values of Loran-C signal's WVT are different at different phase difference.

Key words： Loran-C; cycle identification; Wigner-Vill transformation

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参考文献

[1]	Radio Technical Commission for Marine Services, U.S. Federal Communication Commission. Minimum performance standards (MPS)-Marine Loran C receiving equipment[R]. Report of Special Committee No. 70, December 1977. 1977.
[2]	吴从伟, 宁民. 数字信号处理技术应用及研究[J]. 导航, 2003. (2): 93- 99.
[3]	曹正文, 罗锐, 朱晖, 等. 对罗兰C 信号处理方法的探讨[J]. 导航, 2003. (2): 78- 80.
[4]	张田仓, 罗锐. FIR数字滤波优化设计及在罗兰C信号处理中的应用[J]. 导航, 2004. (2): 83- 88.
[5]	Mohammed A, Chemnitzer H, Last D. Full performance analysis of IFFT spectral-division technique for skywave identification in Loran-C receivers[C]. Proc. 31st Annual Convention and Technical Symposium, International Loran Association (ILA31), Washington, DC, 2002: 1- 10.
[6]	Mohammed A, Last D. IFFT technique for skywave detection in Loran-C receivers[J]. Electronic Letters, 2001, 37(6): 398- 400.
[7]	Mohammed A. Effect of Loran C signal parameters on skywave delay estimation of IFFT technique[J]. Electronic Letters, 2003, 39(14): 1091- 1093.
[8]	张田仓, 罗锐. IFFT 频谱相除技术在罗兰C接收机中的应用[J]. 导航, 2004. (3): 102- 107.
[9]	杨迎春, 杨新峰. 一种高分辨率的罗兰C接收机天波延迟估计技术[J]. 计算机仿真, 2006, 23(7): 295- 298.
[10]	胡东亮, 杨迎春, 范晓菊. 基于 MUSIC 算法的罗兰C接收机天地波自动识别方法研究[J]. 海军工程大学学报, 2006, 18(3): 7- 9.
[11]	A F Mohammed, J D Last. Loran C skywave delay detection using rational modeling techniques[C]. Sixth International Conferenceor Radio Receivers and Associated Systems, 1995. 100- 104.
[12]	Yi Bian, D. Last. Eigen-decomposition techniques for Loran-C skywave estimation[J]. IEEE Transactions on Aerospace and Electronic Systems, 1997, 33(1): 117- 125.
[13]	A Mohammed, D Last. Loran C skywave delay detection using ARMA algorithm[J]. Electronic Letters, 1998, 34(17): 1654- 1655.
[14]	陈秋月, 杨会成, 江太辉. 基于匹配相关法的罗兰C信号周期识别[J]. 无线电工程, 2007, 37(12): 27- 29.
[15]	林慧贞, 罗斌风, 胡东亮, 等. 波形匹配法识别罗兰-C信号周期[J]. 舰船电子工程, 2008, 28(5): 81- 84.
[16]	邹红星, 周小波, 李衍达. 时频分析:回溯与前瞻[J]. 电子学报, 2000, 28(9): 78- 84.
[17]	Jian-Da Wu, Peng-Hsin Chiang. Application of Wigner-Ville distribution and probability neural network for scooter engine fault diagnosis[J]. Expert Systems with Applications, 2009, 36: 2187- 2199.
[18]	王忠仁, 林君, 李文伟. 基于Wigner-Ville 分布的复杂时变信号的时频分析[J]. 电子学报, 2005, 33(12): 2239- 2241.

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