12 January 2019 Research on the high pixels ladar imaging system based on compressive sensing
Jingya Cao, Shaokun Han, Fei Liu, Yu Zhai, Wenze Xia
Author Affiliations +
Abstract
As a signal processing theory, compressive sensing (CS) breaks through the limitations of the traditional Nyquist sampling theorem and provides the possibility to solve the high sampling rate, large data volume, and real-time processing difficulties of traditional high-resolution radar. Based on the theory of single-pixel cameras, an array detection imaging system is built, and main structural parameters are analyzed. The simulation experiment of a simple target is organized to show that the number of measurements can be reduced by achieving the parallel operation through increasing the number of detectors. When the target changes, it is found that the sparsity problem has a great influence on the number of measurements. Therefore, an improved method is proposed using the structure flexibility of fiber array and detectors, which can reduce the number of measurements simultaneously while decreasing the number of detectors, which is superior to the original method.
© 2019 Society of Photo-Optical Instrumentation Engineers (SPIE) 0091-3286/2019/$25.00 © 2019 SPIE
Jingya Cao, Shaokun Han, Fei Liu, Yu Zhai, and Wenze Xia "Research on the high pixels ladar imaging system based on compressive sensing," Optical Engineering 58(1), 013103 (12 January 2019). https://doi.org/10.1117/1.OE.58.1.013103
Received: 4 September 2018; Accepted: 13 December 2018; Published: 12 January 2019
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CITATIONS
Cited by 1 scholarly publication.
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KEYWORDS
Sensors

Imaging systems

Compressed sensing

Digital micromirror devices

Cameras

LIDAR

Reconstruction algorithms

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