A strict and high-accuracy time synchronization approach for consumer-grade cameras and laser scanning sensor using robust attitude feature matching in time series

Abstract Time synchronization is a key step in simultaneous localization and mapping and multi-source sensor data fusion. Current time synchronization methods rely on professional-grade devices with high-precision time synchronization interfaces, which are often unavailable in consumer-grade sensors. To address this limitation, this paper proposes a high-precision time synchronization method for camera and LiDAR based on feature matching of micro-electro-mechanical system (MEMS) gyroscope time series (series feature matching synchronization, SFM-Sync). By constructing integrated sensor units that combine MEMS gyroscopes with consumer-grade cameras or LiDARs, the method collects data in parallel, extracts peak features from gyroscope signals, and performs template matching to achieve accurate synchronization without dedicated hardware interfaces. Experimental results demonstrate that SGM-Sync effectively enables high-precision multi-sensor time synchronization, reducing both technical barriers and hardware dependency while offering a practical solution for multi-sensor fusion systems.