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Characterization of SiN Integrated Optical Phased Arrays on a Wafer-Scale Test Station

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Optical system design for GM-APD lidar based on multi-angle micro-nano polarization array.

Zhuoyan Xiao, Haodong Shi, Haoran Li

|May 4, 2026

Summary

This summary is machine-generated.

A new LiDAR imaging method enhances contrast and signal-to-noise ratio using a multi-angle micro-nano polarization array. This system captures polarization and distance images simultaneously, improving multi-dimensional sensing of dynamic targets.

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Area of Science:

Optics and Photonics
Remote Sensing Technology
Image Processing

Background:

LiDAR systems using Geiger-mode avalanche photodiode (GM-APD) arrays suffer from low imaging contrast and poor signal-to-noise ratio.
Acquiring multi-dimensional information (intensity, polarization, distance) from dynamic targets is challenging.

Purpose of the Study:

To propose a novel LiDAR imaging method that overcomes limitations of existing GM-APD systems.
To enable simultaneous acquisition and fusion of polarization and distance images for enhanced target sensing.

Main Methods:

A multi-angle micro-nano polarization array is integrated into the LiDAR system's optical path.
A secondary imaging path projects the polarization array onto the APD detector for real-time acquisition of four polarization images (0°, 45°, 90°, 135°) and a 3D distance image.
Pixel-level fusion of polarization and distance images is performed.

Main Results:

The proposed method significantly increases polarization image contrast by 92.3% compared to traditional LiDAR intensity images.
Measurement error for polarization angles is less than 2.45%.
The system achieves high-precision registration and real-time multi-dimensional image acquisition.

Conclusions:

The novel LiDAR imaging method effectively addresses low contrast and signal-to-noise ratio issues in GM-APD systems.
Simultaneous acquisition and fusion of polarization and distance data enhance the ability to sense multi-dimensional information from long-range dynamic targets.
This approach offers improved performance for advanced remote sensing applications.