SNR estimation algorithm of LFM signal based on FRFT for long range and shallow underwater acoustic communication systems | |
Ren, Huan ; Hu, Xiaoyi ; Xu, Fang ; Jun, Xieyong ; Qing, Wangde ; Zhan, Chaowu ; Chen, Yanglong ; Hu XY(胡晓毅) ; Xu F(许芳) | |
2014 | |
关键词 | Acoustic noise Algorithms Computer simulation Experiments Fourier transforms Gaussian noise (electronic) Multipath fading Underwater acoustics White noise |
英文摘要 | Conference Name:OCEANS 2014 - Taipei. Conference Address: Taipei, Taiwan. Time:April 7, 2014 - April 10, 2014.; It is very important to estimate the signal to noise ratio (SNR) of receive signal accurately because this parameter will play an important role in the equalization and detection modules. LFM signal is often used as a synchronization signal due to its good autocorrelation property and Doppler tolerance in underwater acoustic (UWA) channels. A new SNR estimation algorithm making use of the LFM signal is proposed in this paper which works in the fractional Fourier transformation (FRFT) domain. Since the characteristics of the LFM signal and the Gaussian white noise are different in the FRFT domain, it is much easier to separate the LFM signal and the Gaussian noise and estimate the power of them, respectively. Computer simulation results show that the proposed algorithm is more accurate than the traditional spectrum-based algorithm in AWGN channel though the estimation accuracy reducing slightly when employed in multipath fading channels. The results of pool experiments and outfield experiments show that this algorithm is more accurate and more robust than the spectrum-base algorithm even in the UWA channels. |
语种 | 英语 |
出处 | http://dx.doi.org/10.1109/OCEANS-TAIPEI.2014.6964468 |
出版者 | Institute of Electrical and Electronics Engineers Inc. |
内容类型 | 其他 |
源URL | [http://dspace.xmu.edu.cn/handle/2288/86920] ![]() |
专题 | 信息技术-会议论文 |
推荐引用方式 GB/T 7714 | Ren, Huan,Hu, Xiaoyi,Xu, Fang,et al. SNR estimation algorithm of LFM signal based on FRFT for long range and shallow underwater acoustic communication systems. 2014-01-01. |
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