Research on Positioning Error Correction Method Based on LiDAR and RTK Module

This paper investigates a high-precision localization and re-photography technique based on LiDAR and RTK modules. To address the limitations of existing methods in terms of accuracy and precision, an optimized approach is proposed. By deeply integrating LiDAR and RTK data and incorporating advanced data processing algorithms, the proposed method significantly enhances the localization and re-photography performance of unmanned systems. To mitigate the impact of environmental interference on localization accuracy, an innovative real-time field calibration algorithm is developed. This algorithm employs a differential value constraint method to accurately identify zero-velocity intervals and integrates the Beetle Antennae Search (BAS) algorithm to achieve rapid and precise calibration, thereby improving system robustness. Experimental results demonstrate that the proposed technique effectively reduces localization errors, constraining the error fluctuation range within 0.2 m, which is superior to the 0.4 m range of conventional methods. Additionally, the fluctuations in gyroscope and accelerometer data remain within a controllable range, ensuring the reliability of the system.