基于网格模型简化算法的多传感测距误差自动修复研究  

Research on Automatic Repair of Multi-Sensor Ranging Error Based on Grid Model Simplification Algorithm

作　　者：轩春青 XUAN Chunqing(College of Information and Electrical Engineering,Zhengzhou Business University,Gongyi He'nan 451200,China)

机构地区：[1]郑州商学院信息与机电工程学院,河南巩义451200

出　　处：《传感技术学报》2021年第11期1537-1540,共4页Chinese Journal of Sensors and Actuators

基　　金：河南省科技厅科技攻关项目(182102210540);河南省教育厅项目(2020YB0403)。

摘　　要：采用当前方法修复测距误差时,无法准确地在短时间内获得测距数据和信息,不能全面地检测测距误差,增加了修复测距误差所用的时间,修复后的测距精度较低。为此,提出基于网格模型简化算法的多传感测距误差自动修复方法。规整化处理网格模型属性,计算顶点的二次误差和属性显著度,通过待折叠边的颜色属性误差和几何属性误差计算待折叠边的折叠代价,通过折叠操作实现网格模型的简化处理,获得测距数据。在网格模型的基础上采用基于Huber损失函数最小化的Kalman滤波方法平滑处理测距结果并重构,通过Huber回归方法实现测距误差的自动修复。仿真分析结果表明,所提方法的测距误差检测概率高、修复效率高、修复精度高。When the current method is used to repair the ranging error, the ranging data and information cannot be accurately obtained in a short time, and the ranging error cannot be comprehensively detected, which increases the time for repairing the ranging error, and the repaired ranging accuracy is low. Therefore, an automatic repair method of multi-sensor ranging error based on simplified algorithm of grid model is proposed. Regularize the grid model attributes, calculate the quadratic error and attribute saliency of vertices, calculate the folding cost of the edge to be folded by the color attribute error and geometric attribute error of the edge to be folded, simplify the grid model by folding operation, and obtain the ranging data. On the basis of grid model, Kalman filtering method based on minimizing Huber loss function is used to smooth the ranging results and reconstruct them, and Huber regression method is used to automatically repair the ranging errors. Simulation results show that the proposed method has high detection probability, high repair efficiency and high repair accuracy.

关 键 词：网格模型简化算法 测距误差 误差修复 Huber损失函数 Kalman滤波方法 

分 类 号：TD712.6[矿业工程—矿井通风与安全]