Research on 3D Point Cloud Discretization Data Processing and Laser Intrusion Detection System
To enhance the spatial perception accuracy and anti-interference capability of intrusion detection systems in nuclear security scenarios, this study proposes a laser intrusion detection system based on 3D point cloud discretization data processing. By independently developing a high-precision 3D laser scanning device (scanning angular resolution ≤ 0.03°, divergence angle ≤ 0.5 mrad), a spatial field detector array is constructed. Innovatively, a multilevel discretization processing algorithm is employed to achieve dynamic reconstruction of 3D defense zones, supporting intelligent vertical spatial segmentation (0-50m/50-100m) and horizontal resolution optimization (≤4.8 cm within a hundred-meter range). The system integrates parametric modeling technology for target geometric features, enabling real-time extraction of 3D attributes such as distance, height, and width of intrusion targets (minimum detectable target size: 30cm × 30cm). Combined with a machine learning classifier, it achieves precise identification of targets such as personnel and vehicles (recognition accuracy ≥ 98.5%). Tailored to the characteristics of nuclear security scenarios, a domestically developed management system with multi-level alarm strategies (Level 1/Level 2), real-time video linkage, and redundant fault-tolerant mechanisms is developed, fully compatible with Hygon CPUs, Kylin V10 operating system, and GBASE8 database. Test results demonstrate that the system achieves a detection accuracy of 98.2% for weak targets (reflectivity ≤ 3%) within a 200-meter range, with a false alarm rate ≤ 1.8%, an average response time of 1.3 seconds, and supports blind-spot-free 3D spatial monitoring (blind zone ≤ 1.3m). Seamless integration with the nuclear security integrated platform via standardized HTTP protocols validates the system's stability and anti-interference capability in complex electromagnetic environments, providing innovative technical support for the active defense system of full-space intrusion detection in nuclear facilities.
Authors
- S. Q. Hou (ORCID: https://orcid.org/0000-0001-9182-0853)
- Jianbiao Ye
- Chunguang Zong
- Qiang Liu (ORCID: https://orcid.org/0000-0002-8402-029X)
- Jian Zhang (ORCID: https://orcid.org/0000-0002-7240-3541)
- Yunfei Yang
Institutions
- Zhejiang Energy Group (China) (CN)
- Shanghai Tongji Urban Planning and Design Institute (CN)
- Nuctech (China) (CN)
- Zhejiang Medicine (China) (CN)
Publication Details
- Published
- 2025-08-08
- DOI
- https://doi.org/10.1109/iaeac65194.2025.11166611
- Primary Topic
- Remote Sensing and LiDAR Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00