Microsystems & Nanoengineering (Jul 2022)

A wide-field and high-resolution lensless compound eye microsystem for real-time target motion perception

  • Li Zhang,
  • Haiyang Zhan,
  • Xinyuan Liu,
  • Fei Xing,
  • Zheng You

DOI
https://doi.org/10.1038/s41378-022-00388-w
Journal volume & issue
Vol. 8, no. 1
pp. 1 – 9

Abstract

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Abstract Optical measurement systems suffer from a fundamental tradeoff between the field of view (FOV), the resolution and the update rate. A compound eye has the advantages of a wide FOV, high update rate and high sensitivity to motion, providing inspiration for breaking through the constraint and realizing high-performance optical systems. However, most existing studies on artificial compound eyes are limited by complex structure and low resolution, and they focus on imaging instead of precise measurement. Here, a high-performance lensless compound eye microsystem is developed to realize target motion perception through precise and fast orientation measurement. The microsystem splices multiple sub-FOVs formed by long-focal subeyes, images targets distributed in a panoramic range into a single multiplexing image sensor, and codes the subeye aperture array for distinguishing the targets from different sub-FOVs. A wide-field and high resolution are simultaneously realized in a simple and easy-to-manufacture microelectromechanical system (MEMS) aperture array. Moreover, based on the electronic rolling shutter technique of the image sensor, a hyperframe update rate is achieved by the precise measurement of multiple time-shifted spots of one target. The microsystem achieves an orientation measurement accuracy of 0.0023° (3σ) in the x direction and 0.0028° (3σ) in the y direction in a cone FOV of 120° with an update rate ~20 times higher than the frame rate. This study provides a promising approach for achieving optical measurements with comprehensive high performance and may have great significance in various applications, such as vision-controlled directional navigation and high-dynamic target tracking, formation and obstacle avoidance of unmanned aerial vehicles.