基于随机投影思想的MWC亚奈奎斯特采样重构算法

doi:10.3969/j.issn.0372-2112.2014.09.004

电子学报 ›› 2014, Vol. 42 ›› Issue (9): 1686-1692.DOI: 10.3969/j.issn.0372-2112.2014.09.004

基于随机投影思想的MWC亚奈奎斯特采样重构算法

盖建新^1,2, 付平², 孙继禹¹, 林海军¹, 吴丽华¹

1. 哈尔滨理工大学测控技术与仪器黑龙江省高校重点实验室, 黑龙江哈尔滨 150080;
2. 哈尔滨工业大学自动化测试与控制系, 黑龙江哈尔滨 150001

收稿日期:2013-04-08 修回日期:2013-12-18 出版日期:2014-09-25
- 作者简介:
- 盖建新 男，博士生，哈尔滨理工大学讲师，主要研究方向为亚奈奎斯特采样、压缩感知、宽带频谱感知等. E-mail：gjx800608@126.com；付平 男，博士，哈尔滨工业大学教授、博士生导师，主要研究方向为压缩感知，图像处理，自动测试技术等. E-mail：fupinghit@126.com
- 基金资助:
- 黑龙江省教育厅科学技术研究项目 (No.12531133）

A Recovery Algorithm of MWC Sub-Nyquist Sampling Based on Random Projection Method

GAI Jian-xin^1,2, FU Ping², SUN Ji-yu¹, LIN Hai-jun¹, WU Li-hua¹

1. The Higher Educational Key Laboratory for Measuring & Control Technology and Instrumentations of Heilongjiang Province, Harbin University of Science and Technology, Harbin, Heilongjiang 150080, China;
2. Department of Automatic Test and Control, Harbin Institute of Technology, Harbin, Heilongjiang 150001, China

Received:2013-04-08 Revised:2013-12-18 Online:2014-09-25 Published:2014-09-25
- Supported by:
- Science and Technology Research Project of Education Department of Heilongjiang Province (No.12531133)

摘要/Abstract

摘要：

针对现有调制宽带转换器（Modulated Wideband Converter，MWC）亚奈奎斯特采样重构算法性能不高问题，提出了一种基于随机投影思想的重构算法.该算法首先将MWC所获得的测量值矩阵通过随机投影方法压缩成具有较少向量的新的测量值矩阵，然后利用所提出的求解器求解多测量向量问题，通过检验和重复尝试性求解过程提高MWC的重构性能.从理论和实验两个方面验证了所提出的算法的有效性.实验结果表明，与著名的ReMBo算法相比，该算法有效提高了重构成功率；当信号的频带数相同时，精确重构所需的硬件通道数更小；在相同的硬件通道数前提下，可重构的信号频带数更高.该算法与ReMBo相比运算时间并没有大幅度增加，当信号频带数较大时，不仅重构性能高，而且运算时间比ReMBo小.

关键词: 调制宽带转换器, 亚奈奎斯特采样, 压缩感知, 随机投影

Abstract:

The existing recovery algorithm of modulated wideband converter (MWC)-based sub-Nyquist sampling is far from satisfactory.Aiming at this problem,a recovery algorithm for MWC based on random projection method is proposed.This algorithm projects the measurement value matrix of MWC onto a random matrix with lower dimension to form a new measurement value matrix,and then solves a multiple measurement vector problem using a solver proposed.The recovery performance is enhanced through examining and repeating the tentative solving processes.This paper validates the effectiveness of the algorithm from both theoretical and experimental perspectives.Numerical experiments demonstrate that,compared with the popular ReMBo algorithm,the proposed algorithm significantly improves the success rate of recovery.From the same number of channels a signal with more spectral bands can be recovered by this algorithm,and a signal with the same number of bands can be recovered using fewer channels.Furthermore,the run time of this algorithm does not increase greatly.In contrast,compared with ReMBo,this algorithm can use a lower time cost to achieve a higher recovery performance when the spectral bands of the signal exceed a specific number.

Key words: modulated wideband converter, sub-Nyquist sampling, compressive sensing, random projection

中图分类号:

TN911.7

盖建新, 付平, 孙继禹, 等. 基于随机投影思想的MWC亚奈奎斯特采样重构算法[J]. 电子学报, 2014, 42(9): 1686-1692.

GAI Jian-xin, FU Ping, SUN Ji-yu, et al. A Recovery Algorithm of MWC Sub-Nyquist Sampling Based on Random Projection Method[J]. Acta Electronica Sinica, 2014, 42(9): 1686-1692.

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基于随机投影思想的MWC亚奈奎斯特采样重构算法

A Recovery Algorithm of MWC Sub-Nyquist Sampling Based on Random Projection Method

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