TY  - JOUR
AU  - WANG, Meng
AU  - WANG, Yufeng
AU  - YAN, Qing
AU  - WANG, Li
AU  - LIU, Jingjing
PY  - 2026
TI  - Construction of a virtual simulation experiment for meteorological observation lidar
JO  - Experimental Technology and Management
SN  - 1002-4956
SP  - 139
EP  - 145
VL  - 43
IS  - 6
AB  - ObjectiveIn response to the strategic demands of national ecological civilization, meteorological observation lidar, as a key technology for atmospheric environmental monitoring, has become a core support for promoting the high-quality development of the meteorological industry. To address the challenges of high cost, high risk, and difficulty in reproducing experimental phenomena in traditional practical teaching, this study aims to develop a virtual simulation experimental system for meteorological observation lidar, thereby compensating for the shortcomings of existing virtual simulation systems in meteorological remote sensing. The system is developed based on a national first-class course and the Lidar Remote Sensing Research Center at the Xi’an University of Technology. It is designed to enhance students’ comprehensive design and innovation capabilities and to provide core teaching support for cultivating high-level interdisciplinary meteorological talents in the new era.MethodsThis study adopts an experimental approach based on “modular design and progressive training” and constructs a three-tiered experimental framework comprising “cognition, design, and exploration,” corresponding to three core modules: lidar system cognition, multispectral spectroscopic system design, and detection and data processing. (1) At the cognitive level, students master the structure and principles of lidar systems via immersive navigation and interactive model demonstrations. (2) At the design level, a task-driven mode is adopted to enable students to independently select detection targets and complete the design of a multispectral spectroscopic system. (3) At the exploration level, students assemble a functional lidar system and undergo a comprehensive training in data acquisition, inversion, and systematic error analysis. Throughout the experiment, scientific methods—including observation, modeling, comparison, and induction—are seamlessly integrated, with theoretical knowledge embedded into interactive tasks, thereby effectively enhancing the students’ capabilities from basic cognition to comprehensive innovation.ResultsThis study has achieved substantial teaching effectiveness through an innovative design that integrates science and education, virtual reality, and learning with assessment. The system employs high-fidelity modeling to authentically reproduce lidar structures and detection processes, effectively addressing the challenges of high cost, safety risks, and limited repeatability in traditional experimental teaching. Within the simulated environment, students engage in a complete workflow, including system cognition, optical design, data acquisition, and inversion analysis. Their operational behaviors are recorded in real time and automatically evaluated, generating comprehensive multidimensional assessment reports. The experiment thus achieves a deep integration of theoretical knowledge acquisition, practical skill training, and process-oriented evaluation.ConclusionThe implementation of this study has not only advanced the systematization and practical application of virtual simulation experiments for meteorological observation lidar, but has also explored an innovative talent development pathway characterized by “virtual augmentation of real practice and the integration of science and education.” This experimental framework significantly enhances students’ capabilities in system design, data processing, and scientific inquiry in complex meteorological detection scenarios. It provides robust support for cultivating high-quality talents in emerging engineering majors such as instrumentation, optoelectronics, and meteorology, thereby offering an important teaching and practical platform for the independent development of meteorological detection equipment and technologies in China.
UR  - https://doi.org/10.16791/j.cnki.sjg.2026.06.017
DO  - 10.16791/j.cnki.sjg.2026.06.017