吉林大学学报(工学版) ›› 2019, Vol. 49 ›› Issue (5): 1696-1705.doi: 10.13229/j.cnki.jdxbgxb20180446

• • 上一篇    

基于局部方差域自适应Blanking的超低频信道噪声抑制方法

赵鹏1(),蒋宇中1(),陈斌1,李春腾1,张杨勇2   

  1. 1. 海军工程大学 电子工程学院,武汉 430033
    2. 中船重工集团公司第七二二研究所,武汉 430079
  • 收稿日期:2018-05-07 出版日期:2019-09-01 发布日期:2019-09-11
  • 通讯作者: 蒋宇中 E-mail:zhaopeng@cug.edu.cn;jiangyuzhong@tsinghua.org.cn
  • 作者简介:赵鹏(1990-),男,博士研究生.研究方向:低频通信干扰抑制.E-mail:zhaopeng@cug.edu.cn
  • 基金资助:
    国家自然科学基金项目(41631072)

SLF channel noise suppression method based on adaptive blanking in local variance domain

Peng ZHAO1(),Yu-zhong JIANG1(),Bin CHEN1,Chun-teng LI1,Yang-yong ZHANG2   

  1. 1. College of Electronic Engineering,Naval University of Engineering, Wuhan 430033, China
    2. No. 722 Research Institute of CSIC, Wuhan 430079, China
  • Received:2018-05-07 Online:2019-09-01 Published:2019-09-11
  • Contact: Yu-zhong JIANG E-mail:zhaopeng@cug.edu.cn;jiangyuzhong@tsinghua.org.cn

摘要:

针对超低频信道噪声脉冲因接收机前端暂态效应而钝化导致常规Blanking非线性抑噪性能退化的问题,在分析脉冲暂态响应波形特点以及常规Blanking性能退化机制基础上,结合局部方差域变换(LVDT)能增强脉冲性的特性,提出了一种基于LVDT的自适应Blanking处理方法,给出了恒虚警率准则下信道噪声脉冲检测门限以及Blanking门限优化准则。仿真和实测结果表明:本文方法在超低频信道噪声抑制方面具有比常规非线性处理更好的性能,考虑到该方法无需信道噪声模型假设及其参数估计,是一种盲抑制方法,因而更具工程实用意义。

关键词: 通信与信息系统, 信道噪声, 脉冲暂态效应, 局部方差, 恒虚警率

Abstract:

The Super Low Frequency (SLF, 3~300 Hz) Channel Noise (CN) impulses are usually smeared by the transient effects in the receivers’ front-end stages, which will make the Blanking Nonlinearity (BNL) lose effectiveness. To solve this problem, based on the analysis of the waveform characteristics of transient response of impulses and the mechanism of performance reduction of the BNL, in conjunction with the consideration that the Local Variance Domain Transforming (LVDT) is capable to intensify the impulsiveness, an adaptive BNL based on LVDT is proposed. The Detection Threshold (DT) for the CN impulses is formulated based on the Constant False Alarm Rate (CFAR) principle and then the DT optimizing principle for the BNL is given. Simulations and real tests show that the proposed method outperforms other common NLs in terms of SLF CN impulse suppression. Since such method needs not to assume the CN model or estimate its parameter, thus is a blind suppression method, therefore, it is more practical.

Key words: communication and information system, channel noise, transient effects of impulse, local variance, constant false alarm rate

中图分类号: 

  • TN85

图1

脉冲暂态效应及其局部方差"

图2

ε(N,S)在不同ASWNR条件下随子序列长度的变化"

图3

ε(N,S)≤10%的子序列长度下限随fc和ASWNR的变化"

图4

不同条件N下虚警率随ASWNR的变化"

图5

不同信道噪声条件下BER性能对比"

图6

不同子序列长度条件下BER性能对比"

图7

实际信号及其抑噪结果"

表1

实测条件下抑噪性能对比"

参 数本文算法LOTNLFCP-BNL
N=8N=64N=128N=1024
SCNRG/dB7.4210.129.988.969.926.08
BERI/%304847434720
1 EvansJ, GriffithsA S. Design of a sanguine noise processor based upon world-wide extremely low frequency (ELF) recordings[J]. IEEE Transactions on Communications, 1974, 22(4): 528-539.
2 IngramR. Performance of the locally optimum threshold receiver and several suboptimal nonlinear receivers for ELF noise[J]. IEEE Journal of Oceanic Engineering, 1984, 9(3): 202-208.
3 MiddletonD. Statistical-physical models of electromagnetic interference[J]. IEEE Transactions on Electromagnetic Compatibility, 1977, 19(3): 106-127.
4 蒋宇中, 应文威, 张曙霞, 等. 超低频非高斯噪声模型及应用[M]. 北京: 国防工业出版社, 2014.
5 OhH, NamH, ParkS. Adaptive threshold blanker in an impulsive noise environment[J]. IEEE Transactions on Electromagnetic Compatibility, 2014, 56(5): 1045-1052.
6 OhH, NamH. Design and performance analysis of nonlinearity preprocessors in an impulsive noise environment[J]. IEEE Transactions on Vehicular Technology, 2017, 66(1): 364-376.
7 应文威, 欧勇恒, 蒋宇中, 等. 新型自适应非高斯接收机设计[J]. 吉林大学学报: 工学版, 2013, 43(6): 1685-1689.
YingWen-wei, Yong-hengOu, JiangYu-zhong, et al. New adaptive receiver for channels with non-gaussian noise[J]. Journal of Jilin University (Engineering and Technology Edition), 2013, 43(6): 1685-1689.
8 SaaifanK A, HenkelW. Decision boundary evaluation of optimum and suboptimum detectors in class-a interference[J]. IEEE Transactions on Communications, 2013, 61(1): 197-205.
9 AlsusaE, RabieK M. Dynamic peak-based threshold estimation method for mitigating impulsive noise in power-line communication systems[J]. IEEE Transactions on Power Delivery, 2013, 28(4): 2201-2208.
10 EppleU, SchnellM. Advanced blanking nonlinearity for mitigating impulsive interference in OFDM systems[J]. IEEE Transactions on Vehicular Technology, 2017, 66(1): 146-158.
11 BernsteinS L, BurrowsM L, EvansJ E, et al. Long-range communications at extremely low frequencies[J]. Proceedings of the IEEE, 1974, 62(3): 292-312.
12 VartiainenJ, LehtomakiJ, SaarnisaariH, et al. Interference suppression in several transform domains[C]∥IEEE Military Communications Conference, Atlantic City, NJ, USA, 2005: 2294-2300.
13 AromaaS, HenttuP, JunttiM. Transform-selective interference suppression algorithm for spread-spectrum communications[J]. IEEE Signal Processing Letters, 2005, 12(1): 49-51.
14 WangS, AnJ P, WangA H, et al. A minimum value based threshold setting strategy for frequency domain interference excision[J]. IEEE Signal Processing Letters, 2010, 17(5): 501-504.
15 JiaQ, LiB, MaS, et al. Local variance detection for multi-antenna spectrum sensing[J]. IEEE Communications Letters, 2015, 19(12): 2142-2145.
16 SaarnisaariH, HenttuP, JunttiM. Iterative multidimensional impulse detectors for communications based on the classical diagnostic methods[J]. IEEE Transactions on Communications, 2005, 53(3): 395-398.
17 ChenY. Improved energy detector for random signals in gaussian noise[J]. IEEE Transactions on Wireless Communications, 2010, 9(2): 558-563.
18 AndrásS, BariczA, SunY. The generalized Marcum Q-Function: an orthogonal polynomial approach[J]. Acta Universitatis Sapientiae Mathematica, 2011, 3(1): 60-76.
19 RuderS. An overview of gradient descent optimization algorithms[J/OL]. [2016-05-12]. https:∥
No related articles found!
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!