激光雷达目标三维姿态估计

郭裕兰; 万建伟; 鲁敏; 谭志国

doi:10.3788/OPE.20122004.0843

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激光雷达目标三维姿态估计

信息科学 | 更新时间：2020-08-12

- 激光雷达目标三维姿态估计
- Three dimensional orientation estimation for ladar target
- 光学精密工程 2012年20卷第4期页码：843-850
- 作者机构：
  
  国防科技大学电子科学与工程学院,湖南长沙,410073
- 作者简介：
- 基金信息：
  
  国家自然科学基金资助项目(No.60972114)();国家博士后科学基金资助项目(No.20100481511)();国家留学基金委CSC奖学金资助项目(No.201
- DOI：10.3788/OPE.20122004.0843
  中图分类号： TN958.98
- 收稿日期：2011-09-27，
  
  修回日期：2012-01-18，
  
  网络出版日期：2012-04-22，
  
  纸质出版日期：2012-04-22
- 稿件说明：
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郭裕兰, 万建伟, 鲁敏, 谭志国. 激光雷达目标三维姿态估计[J]. 光学精密工程, 2012,20(4): 843-850

GUO Yu-lan, WAN Jian-wei, LU Min, TAN Zhi-guo. Three dimensional orientation estimation for ladar target[J]. Editorial Office of Optics and Precision Engineering, 2012,20(4): 843-850
郭裕兰, 万建伟, 鲁敏, 谭志国. 激光雷达目标三维姿态估计[J]. 光学精密工程, 2012,20(4): 843-850 DOI： 10.3788/OPE.20122004.0843.

GUO Yu-lan, WAN Jian-wei, LU Min, TAN Zhi-guo. Three dimensional orientation estimation for ladar target[J]. Editorial Office of Optics and Precision Engineering, 2012,20(4): 843-850 DOI： 10.3788/OPE.20122004.0843.

摘要

针对现有激光雷达目标姿态估计算法对遮挡较为敏感的问题

提出了一种新的三维姿态估计算法。分析了现有算法的内在本质和地面装甲目标固有的表面结构特性

提出了投影点云密度熵(PDE)特征

研究了PDE特征与目标姿态的内在关系

给出了对目标点云迭代地进行旋转投影并寻找PDE最小值以实现三维姿态估计的方法。采用25类地面装甲目标的激光雷达点云数据进行仿真实验

分析了自遮挡、遮挡以及噪声下的估计性能

讨论了参数选择对估算结果的影响。实验结果表明

本文方法在自遮挡下的估计误差小于3

在遮挡率达到80%时的估计误差小于10。实验显示

本文方法对遮挡和噪声具有很强的稳健性

且收敛迅速

能很好地实现激光雷达目标三维姿态估计。

Abstract

Since the existing target orientation estimation methods for laser radars are not robust to the occlusion

a novel 3D orientation estimation method was proposed. The principles of the existing methods and the intrinsic characters of the surface structures for ground targets were analyzed carefully

then the feature of Projection Density Entropy (PDE) was introduced

and the relationship between PDE and target orientation was analyzed. Finally

a 3D orientation estimation method was formulated by iteratively rotating and projecting the target point cloud onto the coordinate planes together with PDE calculation. Comparative experiments were performed on the dataset containing point clouds of 25 ground targets

the performance in self-occlusion

occlusion and the noise were investigated

and the parameter tuning was discussed. The results show that the estimation error of this method is below 3 in self-occlusion

and also no more than 10 even in 80% occlusion. It is clear that the proposed method is robust to occlusion and converges quickly

thus is capable of estimating the 3D orientation of ladar targets in complex scenes.

关键词

Keywords

references

TAN Z G, WANG H, LU M, et al.. Range gated LADAR imaging data simulation. SPIE 7th International Symposium on Multispectral Image Processing and Pattern Recognition, 2011.[2] XIN Z, DEVORE M D. Analysis of data and model accuracy requirements for target classification using ladar data[J]. IEEE Transactions on Aerospace and Electronic Systems, 2008,44(4):1416-1432.[3] 胡峰, 胡春生, 王省书,等. 成像激光雷达与摄像机外部位置关系的标定[J]. 光学精密工程, 2011,19(4):938-943. HU F, HU CH SH, WANG X SH, et al.. Calibration of external relation between imaging laser radar and camera[J]. Opt. Precision Eng., 2011,19(4):938-943. (in Chinese)[4] VASILE A N, MARINO R M. Pose-independent automatic target detection and recognition using 3D laser radar imagery[J]. Lincoln Laboratory Journal, 2005,15(1):61-78.[5] 马超杰, 杨华, 李晓霞,等. 复杂场景下应用成像Ladar 的自动目标识别[J]. 光学精密工程, 2009, 17(7):1714-1721. MA CH J, YANG H, LI X X, et al.. Implementation of automatic target recognition by imaging Ladar in complex scenes[J]. Opt. Precision Eng., 2009,17(7):1714-1721.(in Chinese)[6] ZHU D Q, CHU C C. Characterization of irregularly shaped bodies. Proc.of SPIE, 1995, 2466:17-22.[7] GRONWALL C, GUSTAFSSON F, MILLNERT M,et al.. Ground target recognition using rectangle estimation[J]. IEEE Transactions on Image Processing, 2006,15(11):3401-3409.[8] GRONWALL C. Ground object recognition using laser radar data-geometric fitting, performance analysis, and applications. Linkping: Linkping University, 2006.[9] FELIP R L, FERRADANS S, DIAZ-CARO J, et al.. Target detection in LADAR data using robust statistics. Proc. of SPIE on Electro-Optical Remote Sensing, 2005,5988:1-11.[10] FELIP R L, BINEFA X, DIAZ-CARO J. Discerning objects from ground and target pose estimation in ladar data using robust statistics. 2006 IEEE International Conference on Image Processing, 2006,4244:2109-2112.[11] YANG Y, LIN H, ZHANG Y. Content-based 3-D model retrieval: a survey[J]. IEEE Transaction on Systems, Man and Cybernetics-Part C: Applications and Reviews, 2007,37(6):1081-1099.[12] TANGELDER J W H, VELTKAMP R C. A survey of content based 3D shape retrieval methods. Proc. of Shape Modeling Application 2004, 2004:145-456.[13] 郭裕兰, 鲁敏, 谭志国,等. 一种新的激光雷达目标姿态估计算法[J]. 中国激光, 2011,38(4):242-248. GUO Y L, LU M, TAN ZH G, et al.. A novel method for ladar target orientation estimation[J]. Chinese Journal of Lasers, 2011,38(4):242-248. (in Chinese)

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