# Open-Source LiDAR Time Synchronization System by Mimicking GNSS-clock

arXiv: https://arxiv.org/abs/2107.02625 · HTML: https://mlsanity.com/paper/2107.02625/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 6 Jul 2021.

## Built on by (most cited first, 4 of 4)

- [Multiparticle Kalman filter for object localization in symmetric environments](https://mlsanity.com/paper/2303.07897/) (2023)
- [AsyncBEV: Cross-modal Flow Alignment in Asynchronous 3D Object Detection](https://mlsanity.com/paper/2601.12994/) (2026)
- [Cooperative Visual-LiDAR Extrinsic Calibration Technology for Intersection Vehicle-Infrastructure: A review](https://mlsanity.com/paper/2405.10132/) (2024)
- [SmartDepthSync: Open Source Synchronized Video Recording System of Smartphone RGB and Depth Camera Range Image Frames with Sub-millisecond Precision](https://mlsanity.com/paper/2111.03552/) (2021)

## Abstract (arXiv)

Data fusion algorithms that employ LiDAR measurements, such as Visual-LiDAR, LiDAR-Inertial, or Multiple LiDAR Odometry and simultaneous localization and mapping (SLAM) rely on precise timestamping schemes that grant synchronicity to data from LiDAR and other sensors. Poor synchronization performance, due to incorrect timestamping procedure, may negatively affect the algorithms' state estimation results. To provide highly accurate and precise synchronization between the sensors, we introduce an open-source hardware-software LiDAR to other sensors time synchronization system that exploits a dedicated hardware LiDAR time synchronization interface by providing emulated GNSS-clock to this interface, no physical GNSS-receiver is needed. The emulator is based on a general-purpose microcontroller and, due to concise hardware and software architecture, can be easily modified or extended for synchronization of sets of different sensors such as cameras, inertial measurement units (IMUs), wheel encoders, other LiDARs, etc. In the paper, we provide an example of such a system with synchronized LiDAR and IMU sensors. We conducted an evaluation of the sensors synchronization accuracy and precision, and state 1 microsecond performance. We compared our results with timestamping provided by ROS software and by a LiDAR inner clocking scheme to underline clear advantages over these two baseline methods.