Research on the high pixels ladar imaging system based on compressive sensing

Jingya Cao, Shaokun Han*, Fei Liu, Yu Zhai, Wenze Xia

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

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.

Original languageEnglish
Article number013103
JournalOptical Engineering
Volume58
Issue number1
DOIs
Publication statusPublished - 1 Jan 2019

Keywords

  • compressive sensing
  • fiber array
  • high pixels
  • imaging system

Fingerprint

Dive into the research topics of 'Research on the high pixels ladar imaging system based on compressive sensing'. Together they form a unique fingerprint.

Cite this