极低信噪比无线通信信号随机共振检测理论与方法研究

项目名称： 极低信噪比无线通信信号随机共振检测理论与方法研究

项目编号： No.61471099

项目类型： 面上项目

立项/批准年度： 2015

项目学科： 无线电电子学、电信技术

项目作者： 王军

作者单位： 电子科技大学

项目金额： 80万元

中文摘要： 随着探测距离与下潜深度的增加，深空和远洋水下潜器通信系统接收信噪比（SNR）越来越低，需要研究高效的极低SNR无线通信信号检测方法。本项目利用非线性动力学系统的随机共振（SR）理论在微弱信号检测中的独特优势，研究极低SNR通信信号SR检测的理论和方法，利用信号、噪声和非线性系统间的协同提高检测性能。项目首先建立非线性系统参数和噪声与通信信号检测性能的关系模型，从SNR、波形相关性和互信息的角度，揭示通信信号SR检测的机理。以此为基础，项目提出极低SNR通信信号SR预处理方法，将接收信号通过特别设计的参数自适应非线性系统，利用SR改变噪声的时间、频率特性及其统计分布，在增强有用信号的同时抑制带内噪声；进一步，项目通过可以有效区分信号和噪声、估计信号参数的非线性方法，实现对极低SNR通信信号的判决解调。项目还将针对深空和远洋水下潜器通信的典型场景，通过半实物仿真对提出的理论和方法进行评估验证。

中文关键词： 随机共振；通信信号处理；信号检测；低信噪比

英文摘要： For deep-space and deep-ocean submarines wireless communication systems, the received signal-to-noise ratio (SNR) becomes increasingly lower as the distance of space exploration and diving depth constantly increases. In order to well perform the task of communication, some novel and effective signal detection methods are required under very low SNR region. In this proposal, the theory of stochastic resonance (SR) from the field of nonlinear kinetic systems is proposed to be applied for wireless communication signal detection under very low SNR scenarios, by virtue of its unique advantage in weak signal detection. The detection performance is improved by the cooperation among signal, noise and the nonlinear system. The relationship model between the parameters of nonlinear system and the performance of signal detection under very low SNR is first established. Then, the principle and mechanism of SR aided signal detection is explained in terms of SNR, mutual information and the correlation between input and output waveforms. Based this mechanism, the SR processing method of communication signal with very low SNR is further proposed. By feeding the received signals with very low SNR into a nonlinear system with specific parameters, the characteristics in time and frequency domains and the statistical distribution of noise are changed. As a result, the desired communication signal can be enhanced and the in-band noise can be suppressed at the same time. Moreover, the concerned communication signal is then demodulated by a nonlinear system, which can effectively distinguish signal and noise and estimate the signal parameters. With these manipulatoins, desired detection performance can be achieved. Finally, half hardware-in-loop simulations will be applied to verify the proposed SR aided communication signal detection under typical scenarios of deep-space and deep-ocean submarines wireless communication systems.

英文关键词： Stochastic Resonance;Signal Processing for Communications Signals;Signal Detection;Low SNR