摘要
本文提出一种基于压缩感知的探地雷达数据压缩采集方法,实现实时的采样数据压缩,无需采集完所有数据后再压缩,采样与压缩同时进行,从而大大减小了实时采样的存储压力.探地雷达的采样信号被压缩投影到由Mersenne Twister算法生成随机矩阵,实现压缩.该方法实现了小计算量的实时压缩,并且硬件实现简单.本文使用half-quadric的方法求解感知压缩模型中的l1凸优化,快速实现数据重构.实验表明,本文方法能将探地雷达数据压缩把到原来的1/15,大大减小实时采样存储压力.
This paper presents a novel data acquisition for ground penetrating radars （GPR） based on compressive sensing （CS） by exploiting sparseness in two dimensional FFT of B-scan data. Linear projections of the returned signal with random vectors generated by Mersenne Twister algorithm are taken as measurements. Half-quadric is used to solve 11 minimization. Using experimental GPR data, it is shown that the number of acquisition data is only the 1/15 of the number usually considered necessary.
出处
《电子学报》
EI
CAS
CSCD
北大核心
2011年第9期2204-2206,共3页
Acta Electronica Sinica
基金
国家863高技术研究发展计划(No.2008AA121702-3)
国家自然基金(No.40976114)
关键词
探地雷达
感知压缩
数据采集
ground penetrating radars
compressive sensing
data acquisition
