一种测绘信息数据智能分析方法及系统

By recording the local density, energy attenuation, and interlayer variance of the point cloud dataset in real time, calculating the self-organized fracture index, and adjusting the parameters of the lidar system, the problem of parameter coupling imbalance in lidar system parameter adjustment is solved, thereby improving the mapping accuracy and point cloud quality.

CN121784767BActive Publication Date: 2026-07-17安徽省第一测绘院

Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
安徽省第一测绘院
Filing Date
2025-12-31
Publication Date
2026-07-17

AI Technical Summary

Technical Problem

Existing lidar systems lack a mechanism to identify imbalances in parameter coupling when adjusting pulse repetition frequency and scanning angle range, resulting in significant fluctuations in mapping accuracy and an inability to accurately reflect the true terrain.

Method used

By recording the local point cloud density, energy attenuation coefficient, and interlayer variance during the generation of the point cloud dataset in real time as a real-time state vector, the self-organized fracture index is calculated, and the parameters of the lidar system are judged and adjusted to ensure point cloud quality and measurement accuracy.

Benefits of technology

It has improved the stability of lidar mapping accuracy, and the generated point cloud dataset has a more reasonable density and measurement accuracy, which can accurately reflect the real terrain.

✦ Generated by Eureka AI based on patent content.

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Abstract

本发明公开了一种测绘信息数据智能分析方法及系统,涉及数据分析技术领域,通过实时记录点云数据的局部点云密度、能量衰减系数和层间方差,计算自组织破裂度指数来判断是否需要更改激光雷达系统的扫描角范围或脉冲重复频率。若需要更改,基于实时状态向量判断是调整扫描角范围还是脉冲重复频率,并确定调整方向。根据调整后的参数,更新激光雷达系统并继续测绘地表数据。这样,系统能够灵活确定是调整扫描角范围、脉冲重复频率,还是同时调整二者,避免盲目调节,减少测绘精度波动,确保点云质量稳定。最终生成的点云数据集具有更合理的密度和精度,从而准确反映地表真实地形,确保测绘结果精准。
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