Adaptive Range-Gated 3D Imaging Based on Distributed Compressed Sensing

doi:10.12068/j.issn.1005-3026.2021.04.009

Abstract

Abstract: Based on the correlation between time slices of range-gated imaging， a distributed compressed sensing 3D imaging method was proposed， which solved the conflict between a large amount of data and hardware storage performance in 3D imaging. According to the correlation， a distributed compression model based on the joint sparse model was constructed to assist the reconstruction of partial time slices. An adaptive range-gated method was designed， and the gated time was adaptively adjusted according to the set threshold， without distance prior information， which increases system flexibility. The results show that when the average sampling rate is 0.15， the imaging quality of this method is 11.124dB higher than that of the traditional method， and the average error of imaging distance is reduced by 6.240. The distributed imaging method can effectively reduce the collection of time slice redundant information， providing a new idea for range-gated 3D imaging.

Key words: computational imaging; underwater three-dimensional imaging; distributed compressed sensing; adaptive range-gated imaging; joint sparse model

CLC Number:

O438

ZHANG Na， WANG Lu， CHENG Jun-na， TIAN Ji-rong. Adaptive Range-Gated 3D Imaging Based on Distributed Compressed Sensing[J]. Journal of Northeastern University(Natural Science), 2021, 42(4): 516-523.

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