基于随机解调的频谱稀疏模拟信号压缩采样与处理算法研究

项目名称： 基于随机解调的频谱稀疏模拟信号压缩采样与处理算法研究

项目编号： No.61301264

项目类型： 青年科学基金项目

立项/批准年度： 2014

项目学科： 无线电电子学、电信技术

项目作者： 赵贻玖

作者单位： 电子科技大学

项目金额： 25万元

中文摘要： 压缩感知在理论上突破了采样定理对稀疏信号采样的限制，但在模拟信号采样的应用中却受到电路非理想工作特性的影响，仅有的少量相关研究也在压缩采样系统建模方面存在不足。本项目将围绕基于随机解调技术的频谱稀疏模拟信号压缩采样模型与信号处理算法，重点研究电路可实现压缩采样系统建模与随机解调压缩采样信号重构、检测与估计算法，解决模拟信号压缩采样实用化、压缩采样值直接检测与估计等关键性问题。主要内容包括：符合电路实际工作特性的补偿模型构造、随机序列多通道复用相关性与压缩采样值信息熵的定量关系、系统采样行为频域数学建模、稀疏表示基失配影响、信号与系统参数关系模型、采样系统的检测与估计模型、随机解调压缩采样信号检测与估计算法等。在此基础上设计基于随机解调技术的压缩采样实验平台，实现频谱稀疏模拟信号的压缩采样与信号处理。预期成果将会推进压缩感知理论在模拟信号采样中的实用化，并促进压缩采样信号处理技术的发展。

中文关键词： 压缩采样；随机触发；随机解调；频谱感知；频带稀疏

英文摘要： The compressed sensing theoretically breaks through the limitation of the sampling theorem for sparse signal. However, considering the implementation of analog signal compressive sampling, the nonideal properties of the circuit significantly degrade the performance of system. And a few existing models for analog signal sampling still remain problems and need to be improved. In this project, we will study random demodulation technique based spectral sparse analog signal compressive sampling model and signal processing algorithms. The project will focus on models of circuit realizable compressive sampling system and reconstruction, detection, and estimation agorithms of compressive samples. And the project also hopes to solve the key issues of anaolog signal compressive sampling and compressive samples detection and estimation. The main contants include: the compensation model for practical circuits, the quantitative relationship between information entropy of compressive samples and correlation coefficient introduced by the random sequence sharing in channels, the mathematical behavior model of sampling system in frequency domain, the impact of sparse representation basis mismatch, the relation model of signal and system parameters, the detection and estimation model for sampling system, detection and estimation

英文关键词： Compressive sampling；Random triggering；Random demodulation；Spectrum sensing；Sparse multiband