scholarly journals EFFICIENT SPARSE IMAGING RECONSTRUCTION ALGORITHM FOR THROUGH-THE-WALL RADAR

2017 ◽  
Vol 76 ◽  
pp. 33-41 ◽  
Author(s):  
Lele Qu ◽  
Xing Cheng ◽  
Tianhong Yang
Keyword(s):  
Reconstruction Algorithm ◽  
Imaging Reconstruction

scholarly journals An Industrial B-Mode Phased Array Ultrasonic Imaging Reconstruction Algorithm Based on FRI Sampling

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Guangzhi Dai ◽  
Zhiyong He ◽  
Song Lin
Keyword(s):  
Phased Array ◽  
Simulation Experiment ◽  
Ultrasonic Imaging ◽  
Reconstruction Algorithm ◽  
Imaging Method ◽  
Sampling Point ◽  
Simple Circuit ◽  
Ultrasonic Signals ◽  
Imaging Algorithm ◽  
Imaging Reconstruction

Firstly, a novel FRI sampling model has been proposed according to the characteristics of ultrasonic signals. The model has the advantages such as good stability, strong antinoise ability, simple circuit implementation, and fewer preconditions, compared to the traditional methods. Then, in order to verify the validity of the sampling model, the method is applied to B-type ultrasonic imaging, and a B-type phased array ultrasonic imaging algorithm based on FRI sampling model is proposed. Finally, the algorithm simulation experiment is designed, and the results show that the sampling point required by the proposed FRI sampling model is only 0.1% of the traditional B-type phased array ultrasonic imaging method, and the sampling frequency of the proposed ultrasonic imaging algorithm is only 0.0077% of the traditional B-type ultrasonic imaging method. Additionally, the experiment result indicates that this algorithm is more applicable to phased array ultrasonic imaging than the SOS filter is.

scholarly journals Group Sparse Basis Pursuit Denoising Reconstruction Algorithm for Polarimetric Through-the-Wall Radar Imaging

2018 ◽  
Vol 2018 ◽  
pp. 1-8 ◽  
Author(s):  
Lele Qu ◽  
Shimiao An ◽  
Tianhong Yang ◽  
Yanpeng Sun
Keyword(s):  
Reconstruction Algorithm ◽  
Spectral Projection ◽  
Radar Imaging ◽  
Basis Pursuit ◽  
Imaging Method ◽  
L1 Norm ◽  
Reconstruction Performance ◽  
Imaging Reconstruction ◽  
Imaging Algorithms

Polarimetric through-the-wall radar imaging (TWRI) system has the enhancing performance in the detection, imaging, and classification of concealed targets behind the wall. We propose a group sparse basis pursuit denoising- (BPDN-) based imaging approach for polarimetric TWRI system in this paper. The proposed imaging method combines the spectral projection gradient L1-norm (SPGL1) algorithm with the nonuniform fast Fourier transform (NUFFT) technique to implement the imaging reconstruction of observed scene. The experimental results have demonstrated that compared to the existing compressive sensing- (CS-) based imaging algorithms, the proposed NUFFT-based SPGL1 algorithm can significantly reduce the required computer memory and achieve the improved imaging reconstruction performance with the high computational efficiency.

Study of NIR imaging reconstruction algorithm

1994 ◽  
Author(s):  
Kai Zhang ◽  
Peter J. Rolfe ◽  
Yappa A. Wickramasinghe
Keyword(s):  
Reconstruction Algorithm ◽  
Nir Imaging ◽  
Imaging Reconstruction
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