Scalable Megapixel resolution Solid-State LiDAR architecture by Dual-MEMS coarse-fine Diffractive Beam Steering with Crosstalk Mitigation

Flash LiDAR offers wide-field-of-view (FOV) imaging but suffers from short range and low spatial mapping density. Point-and-shoot LiDAR achieves longer range and higher resolution but suffers from reduced FOV and slower scanning rates. We present a hybrid solid-state LiDAR architecture that combines diffractive beam and holographic image steering using synchronized transmitter and receiver Digital Micromirror Devices (Tx-DMD and Rx-DMD) for coarse beam steering and a Phase Light Modulator (PLM) for fine holographic image steering. The Tx/Rx-DMD pair decouples the full FOV from the range by sequentially steering illumination and collection into matched diffracted sub-FOVs, while the PLM subdivides each sub-FOV into a 3×3 grid of sub-sub-FOVs. In this paper, we demonstrate a ninefold increase in sampling count from 7,168 to 64,512 points across 52.59°×7.32° FOV while achieving an angular resolution ranging from 0.153°-0.229° at 13.32 FPS. First-order optical modeling and receiver focal length optimization provide contiguous, non-overlapping illumination and imaging across DMD diffraction orders. Crosstalk from cover glass reflection and zeroth-order diffraction from both the DMD and PLM is reduced using Fourier-domain masking in the Tx-path and polarization-selective Fourier filtering in the Rx-path. The proposed architecture provides a scalable pathway from sub-megapixel LiDAR to multi-megapixel LiDAR through n^2 fold spatial sampling enhancement with reduced optical crosstalk.

Authors

Publication Details

Journal
Optics Express
Published
2026-10-08
DOI
https://doi.org/10.1364/oe.613182
Primary Topic
Advanced Optical Sensing Technologies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Scalable Megapixel resolution Solid-State LiDAR architecture by Dual-MEMS coarse-fine Diffractive Beam Steering with Crosstalk Mitigation

Yuzuru Takashima, Xianyue Deng, Emil Rajan Varghese, Yefu Zhang et al.
Optics Express
Advanced Optical Sensing Technologies
article

Scalable Megapixel resolution Solid-State LiDAR architecture by Dual-MEMS coarse-fine Diffractive Beam Steering with Crosstalk Mitigation

Yuzuru Takashima, Xianyue Deng, Emil Rajan Varghese, Yefu Zhang, Lily McKenna, Abrar Liaf, Rajesh Shrestha
article en

Abstract

Flash LiDAR offers wide-field-of-view (FOV) imaging but suffers from short range and low spatial mapping density. Point-and-shoot LiDAR achieves longer range and higher resolution but suffers from reduced FOV and slower scanning rates. We present a hybrid solid-state LiDAR architecture that combines diffractive beam and holographic image steering using synchronized transmitter and receiver Digital Micromirror Devices (Tx-DMD and Rx-DMD) for coarse beam steering and a Phase Light Modulator (PLM) for fine holographic image steering. The Tx/Rx-DMD pair decouples the full FOV from the range by sequentially steering illumination and collection into matched diffracted sub-FOVs, while the PLM subdivides each sub-FOV into a 3×3 grid of sub-sub-FOVs. In this paper, we demonstrate a ninefold increase in sampling count from 7,168 to 64,512 points across 52.59°×7.32° FOV while achieving an angular resolution ranging from 0.153°-0.229° at 13.32 FPS. First-order optical modeling and receiver focal length optimization provide contiguous, non-overlapping illumination and imaging across DMD diffraction orders. Crosstalk from cover glass reflection and zeroth-order diffraction from both the DMD and PLM is reduced using Fourier-domain masking in the Tx-path and polarization-selective Fourier filtering in the Rx-path. The proposed architecture provides a scalable pathway from sub-megapixel LiDAR to multi-megapixel LiDAR through n^2 fold spatial sampling enhancement with reduced optical crosstalk.

Optics Express
Openalex Percentile: Top 14%
Advanced Optical Sensing Technologies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.