Low-Complexity Architecture of Orthogonal Matching Pursuit Based on QR Decomposition
Low-Complexity Architecture of Orthogonal Matching Pursuit Based on QR Decomposition
复制标题
基于QR分解的低复杂度正交匹配追踪体系结构
DOI：
10.1109/tvlsi.2019.2909754
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发表时间：
2019
影响因子：
2.8
通讯作者：
A. Sahoo
中科院分区：
文献类型：
--
作者：
Shirshendu Roy;D. P. Acharya;A. Sahoo
提出了一种新的正交匹配追踪（OMP）硬件结构，并在现场可编程门阵列（FPGA）上实现了测试。性能评估采取雷达脉冲压缩采样综合使用随机调制预积分器（RMPI）。基本的测试信号，如高斯脉冲及其变化作为输入到RMPI。OMP算法的输出乘以Gabor时频字典，以获得重建的雷达信号。文中还提出了一种实现Gabor时频字典的新方法。对于<inline-formula><tex-math notation="LaTeX">$M$</tex-math></inline-formula>-稀疏信号，OMP算法在<inline-formula><tex-math notation="LaTeX">$m~（\geq M）$次</tex-math></inline-formula>迭代中产生信号的估计。所提出的设计在Artix 7 FPGA器件上实现，<inline-formula><tex-math notation="LaTeX">$K=80$</tex-math></inline-formula>，<inline-formula><tex-math notation="LaTeX">$N=1024$</tex-math></inline-formula>，$<inline-formula><tex-math notation="LaTeX">m=16$</tex-math></inline-formula>，其中<inline-formula><tex-math notation="LaTeX">$N$</tex-math></inline-formula>是样本数，<inline-formula><tex-math notation="LaTeX">$K$</tex-math></inline-formula>是测量向量长度。该设计还实现了<inline-formula><tex-math notation="LaTeX">$K=256$</tex-math></inline-formula>，<inline-formula><tex-math notation="LaTeX">$N=1024$</tex-math></inline-formula>，和<inline-formula><tex-math notation="LaTeX">$m=36$</tex-math></inline-formula>使用Virtex 6 FPGA器件与其他现有的设计进行比较。该技术实现了18.336 dB的恢复信噪比（RSNR）。所提出的设计利用<inline-formula><tex-math notation="LaTeX">$（3 M-1）$</tex-math></inline-formula>较少的乘法器和消耗27%的动态功耗相比，以前公布的FPGA实现的OMP。所提出的设计是硬件有效的，即使对于更高的值<inline-formula><tex-math notation="LaTeX">$m/K$</tex-math></inline-formula>。
A novel hardware architecture of orthogonal matching pursuit (OMP) is presented here, and the test is implemented on a field-programmable gate array (FPGA). The performance is evaluated by taking RADAR pulses that are compressively sampled synthetically using the random modulation preintegrator (RMPI). Basic test signals such as Gaussian pulse and its variations are taken as input to the RMPI. The output of the OMP algorithm is multiplied by the Gabor time-frequency dictionary to obtain the reconstructed RADAR signal. A novel method to implement the Gabor time-frequency dictionary is also presented. The OMP algorithm generates an estimate of a signal in <inline-formula> <tex-math notation="LaTeX">$m~(\geq M)$ </tex-math></inline-formula> iterations for an <inline-formula> <tex-math notation="LaTeX">$M$ </tex-math></inline-formula>-sparse signal. The proposed design is implemented on the Artix7 FPGA device for <inline-formula> <tex-math notation="LaTeX">$K=80$ </tex-math></inline-formula>, <inline-formula> <tex-math notation="LaTeX">$N=1024$ </tex-math></inline-formula>, and <inline-formula> <tex-math notation="LaTeX">$m=16$ </tex-math></inline-formula>, where <inline-formula> <tex-math notation="LaTeX">$N$ </tex-math></inline-formula> is the number of samples and <inline-formula> <tex-math notation="LaTeX">$K$ </tex-math></inline-formula> is the measurement vector length. The design is also implemented for <inline-formula> <tex-math notation="LaTeX">$K=256$ </tex-math></inline-formula>, <inline-formula> <tex-math notation="LaTeX">$N=1024$ </tex-math></inline-formula>, and <inline-formula> <tex-math notation="LaTeX">$m=36$ </tex-math></inline-formula> using the Virtex6 FPGA device for comparison with other existing designs. The recovery signal-to-noise ratio (RSNR) of 18.336 dB is achieved with this technique. The proposed design utilizes <inline-formula> <tex-math notation="LaTeX">$(3m-1)$ </tex-math></inline-formula> fewer multipliers and consumes 27% less dynamic power compared to previously published FPGA implementation of OMP. The proposed design is hardware efficient even for the higher value of <inline-formula> <tex-math notation="LaTeX">$m/K$ </tex-math></inline-formula>.