基于毫米波雷达获取料堆DEM的插值方法研究

doi:10.3969/j.issn.1000-1158.2022.12.05

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Abstract Aiming at the problems of difficulty in obtaining stack height model, poor environmental adaptability of measuring device, high cost and low model accuracy in the development process of the existing automatic stacker-reclaimer technology, the use of 77GHz millimeter wave radar, differential BeiDou and angle coding is proposed. The integrated technology of the device obtains discrete point cloud data on the surface of a large stockpile. Derive a formula for solving multi-sensor data fusion to obtain discrete point cloud data. It is proposed to use the hybrid quantized pigeon-inspired optimization algorithm to optimize the Kriging interpolation algorithm to obtain the digital elevation model(DEM)of the stockpile. The method of cross-validation is used to compare and analyze the improved ordinary Kriging, ordinary Kriging, inverse distance weighting, linear and natural neighborhood interpolation algorithms based on triangulation after selecting the parameters. The root mean square error of the improved Kriging interpolation algorithm is less than 0.37m, the mean square error is less than 0.13m, and the root mean square error is 39.9% lower than the ordinary Kriging interpolation algorithm. During the on-site test, the proposed method can obtain the DEM of the pile without the influence of weather and dust, and it is meets the requirements of accuracy in the project of automatic pile-reclaimer.

Key words： metrology;material pile DEM millimeter wave radar;point cloud data hybrid quantized pigeon-inspired optimization algorithm improved Kriging interpolation algorithm

Received: 19 July 2021 Published: 28 December 2022

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TB92

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	Articles by authors
	KONG De-ming
	CAO Shuai
	SHEN Yue
	ZHOU Yi-ren

Cite this article:

KONG De-ming,CAO Shuai,SHEN Yue, et al. Research on Interpolation Method for Obtaining DEM of Material Pile Based on Millimeter Wave Radar[J]. Acta Metrologica Sinica, 2022, 43(12): 1554-1560.

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http://jlxb.china-csm.org:81/Jwk_jlxb/EN/10.3969/j.issn.1000-1158.2022.12.05 OR http://jlxb.china-csm.org:81/Jwk_jlxb/EN/Y2022/V43/I12/1554

［1］王鹏, 史瑞泽, 钟小峰, 等. 基于双线投影与线面约束的3D扫描测量系统研究［J］. 红外与激光工程, 2017, 46(4): 133-139.
Wang P, Shi R Z, Zhong X F, et al. 3D scanning measurement system based on double-line projection and the line-plane constraint［J］. Infrared and Laser Engineering, 2017, 46(4): 133-139.
［2］张旭, 陈爱军, 沈小燕, 等. 基于线激光传感器的工件尺寸测量系统的误差补偿方法［J］. 计量学报, 2020, 41(12): 1449-1455.
Zhang X, Chen A J, Shen X Y, et al. Error Compensation Method for Workpiece Size Measurement System Based on Line Laser Sensor［J］. Acta Metrologica Sinica, 2020, 41(12): 1449-1455.
［3］邵晴, 徐涛. 基于三维激光扫描技术的粮食储量监测系统的设计与试验［J］. 农业工程学报, 2015, 31(20): 262-267.
Shao Q, Xu T. Design and experiment for grain storage monitoring system based on 3-D laser scanning technology［J］. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2015, 31(20): 262-267.
［4］赵建虎, 吴敬文, 赵兴磊, 等. 一种改进的机载激光测深深度偏差模型［J］. 武汉大学学报·信息科学版, 2019, 44(3): 328-333.
Zhao J H, Wu J W, Zhao X L, et al. A Correction Model for Depth Bias in Airborne LiDAR Bathymetry Systems［J］. Geomatics and Information Science of Wuhan University, 2019, 44(3): 328-333.
［5］张竟月, 孙斌, 谢玄达, 等. 基于激光和机器视觉的微量液体容量计量方法［J］. 计量学报, 2018, 39(4): 504-509.
Zhang J Y, Sun B, Xie X D, et al. Volume Metrology Method for Micro Liquid Based on Laser and Machine Vision［J］. Acta Metrologica Sinica, 2018, 39(4): 504-509.
［6］贺杰, 王桂梅, 刘杰辉, 等. 基于图像处理的皮带机上煤量体积计量［J］. 计量学报, 2020, 41(12): 1516-1520.
He J, Wang G M, Liu J H, et al. Volume Measurement of Coal Volume on Belt Conveyor Based on Image Processing［J］. Acta Metrologica Sinica, 2020, 41(12): 1516-1520.
［7］曹文意, 陈继民, 袁艳萍, 等. 基于多视图的三维模型采集系统的研制［J］. 计量学报, 2019, 40(6): 1000-1005.
Cao W Y, Chen J M, Yuan Y P, et al. Research on 3D Model Acquisition System Based on Multiple View［J］. Acta Metrologica Sinica, 2019, 40(6): 1000-1005.
［8］杨德山, 董丽丽, 梁倩倩, 等. 大型散货堆体积的快速测量［J］. 光学精密工程, 2016, 24(9): 2126-2133.
Yang D S, Dong L L, Liang Q Q, et al. Rapid volume measurement for large bulk cargo［J］. Optics and Precision Engineering, 2016, 24(9): 2126-2133.
［9］张望, 李瑛, 杨德山. 基于三维激光扫描的散货堆快速建模［J］. 应用激光, 2019, 39(2): 340-345.
Zhang W, Li Y, Yang D S. Rapid Modeling of Stockpile Based on 3D Laser Scanning［J］. Applied Laser, 2019, 39(2): 340-345.
［10］吕小宁, 刘晓丽, 段云岭, 等. 地下能源储库群容积激光测量方法及现场实验［J］. 中国激光, 2016, 43(10): 1004002.
Lü X N, Liu X L, Duan Y L, et al. Laser Measurement Method and in-situ Experiment of Underground Energy Storage Caverns Volume［J］. Chinese Journal of Lasers, 2016, 43(10): 1004002.
［11］赵其杰, 孟庆栩. 基于激光传感的料堆体积测量在线标定方法［J］. 中国激光, 2015, 42(12): 1208004.
Zhao Q J, Meng Q X. On-Line Calibration Method of Stockpile Volume Measurement Based on Laser Sensors［J］. Chinese Journal of Lasers, 2015, 42(12): 1208004.
［12］洪伟, 余超, 陈继新, 等. 毫米波与太赫兹技术［J］. 中国科学:信息科学, 2016, 46(8): 1086-1107.
Hong W, Yu C, Chen J X, et al. Millimeter wave and terahertz technology［J］. Scientia Sinica Informationis, 2016, 46(8): 1086-1107.
［13］Li L, Nearing M A, Nichols M H, et al. The effects of DEM interpolation on quantifying soil surface roughness using terrestrial LiDAR［J］. Soil and Tillage Research, 2020, 198: 104520.
［14］杨秋丽, 魏建新, 郑江华, 等. 离散点云构建数字高程模型的插值方法研究［J］. 测绘科学, 2019, 44(7): 16-23.
Yang Q L, Wei J X, Zheng J H, et al. Comparison of interpolation methods of digital elevation model using discrete point cloud data［J］. Science of Surveying and Mapping, 2019, 44(7): 16-23.
［15］Gaikwad N, Sawant R. Analyzing Kriging method and creating an application using Kriging［C］//IEEE. 2016 IEEE International Conference on Cloud Computing and Big Data Analysis (ICCCBDA). Chengdu, China, 2016.
［16］陈洪芳, 张爽, 梁超伟, 等. 一种基于反距离权重法修正CMM体积误差的方法［J］. 中国激光, 2020, 47(12): 1204001.
Chen H F, Zhang S, Liang C W, et al. Method for Volume Error Calibration of CMM Based on Inverse-Distance Weighting Algorithm［J］. Chinese Journal of Lasers, 2020, 47(12): 1204001.
［17］Ikechukwu M N, Ebinne E, Idorenyin U, et al. Accuracy Assessment and Comparative Analysis of IDW, Spline and Kriging in Spatial Interpolation of Landform (Topography): An Experimental Study［J］. Journal of Geographic Information System, 2017, 9(3):354-371.
［18］张靖. 基于克里金算法的点云数据插值研究［D］. 西安: 长安大学, 2014: 25-27.
［19］Chen B Y, Lei H, Shen H D, et al. A hybrid quantum-based PIO algorithm for global numerical optimization［J］. Science China Information Sciences, 2019, 62(7): 70203.
［20］Zhang B, Duan H B. Three-Dimensional Path Planning for Uninhabited Combat Aerial Vehicle Based on Predator-Prey Pigeon-Inspired Optimization in Dynamic Environment［J］. IEEE/ACM Transactions on Computational Biology & Bioinformatics, 2017, 14(1): 97-107.