多传感器自主跟踪中的数据融合方法

单海蛟; 刘伟宁; 王嘉成; 刘培勋; 李治根; 邓耀华

doi:10.3788/YJYXS20163108.0801

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多传感器自主跟踪中的数据融合方法

驱动与控制 | 更新时间：2020-07-07

- 多传感器自主跟踪中的数据融合方法
- Data fusion method in multi-sensors autonomous tracking
- 液晶与显示 2016年31卷第8期页码：801-809
- 作者机构：
  
  1.中国科学院长春光学精密机械与物理研究所, 吉林长春 130033
  2.中国科学院大学, 北京 100049
  3.广东工业大学, 广东广州 510006
- 作者简介：
  
  [ "单海蛟(1990-), 女, 河北张家口人, 硕士研究生, 2014年于东北大学获得学士学位, 现为中国科学院长春光学精密机械与物理研究所硕士研究生, 主要从事数字图像处理, 目标跟踪, 数据融合方面的研究。E-mail:shanhaijiao_go@163.com" ]
  刘伟宁, E-mail:liuweing2003@126.com
- 基金信息：
  
  国家自然科学基金(61401425);广东省中科院全面战略合作专项资金竞争性分配资助项目(2013B091500046);National Natural Science Foundation of China(61401425);Comprehensive Strategic Cooperation Fund of Guangdong Province and Chinese Academy of Sciences(2013B091500046)
- DOI：10.3788/YJYXS20163108.0801
  中图分类号： V557.5;TP274.2
- 收稿日期：2016-04-01，
  
  录用日期：2016-5-19，
  
  纸质出版日期：2016-08
- 稿件说明：
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单海蛟, 刘伟宁, 王嘉成, 等. 多传感器自主跟踪中的数据融合方法[J]. 液晶与显示, 2016,31(8):801-809.

Hai-jiao SHAN, Wei-ning LIU, Jia-cheng WANG, et al. Data fusion method in multi-sensors autonomous tracking[J]. Chinese journal of liquid crystals and displays, 2016, 31(8): 801-809.
单海蛟, 刘伟宁, 王嘉成, 等. 多传感器自主跟踪中的数据融合方法[J]. 液晶与显示, 2016,31(8):801-809. DOI： 10.3788/YJYXS20163108.0801.

Hai-jiao SHAN, Wei-ning LIU, Jia-cheng WANG, et al. Data fusion method in multi-sensors autonomous tracking[J]. Chinese journal of liquid crystals and displays, 2016, 31(8): 801-809. DOI： 10.3788/YJYXS20163108.0801.

摘要

为了提高光电跟踪系统的稳定性和自主跟踪能力，对多传感器数据融合算法和数据的有效性估计进行研究，提出一种多传感器自主跟踪算法。首先按照统计学方法，实时估计各传感器数据的误差协方差。然后按照均方误差最小准则，对各路数据进行融合。将最小二乘多项式拟合法和记忆衰减因子应用到误差协方差估计中，提高了融合结果的可信度。最后，提出一种多传感器跟踪数据切换策略，自动选择有效传感器数据中置信度最高、跟踪效果最优的一路数据，从而实现自主稳定跟踪的目的。实验结果表明，使用改进后的数据融合算法比原始方法的最终传感器选择结果正确率提高37.5%左右。在几种典型的传感器数据异常情况下，该数据融合算法和多路数据切换策略能够完成自主跟踪的目的。

Abstract

In order to improve the stability and the ability of autonomous tracking of electro-optical tracking system

multi-sensor data fusion algorithm and estimate of the availability of sensor data is researched. In this paper a multi-sensor data fusion algorithm for autonomous tracking was put forward. First

the variance was estimated according to the statistics data real timely. Secondly

the fusion of the sensor data was made based on the rule of least mean square error. Then an improved estimation formula of the variance based on least square polynomial fit and memory attenuation factor was put forward which can improve the confidence interval of the fusion result. Finally

a multi-sensor switch-over strategy was put forward which can choose the sensor data that has the highest confidence interval and optimal tracking result from the valid ones autonomously. By this way we can achieve the aim of autonomous and stable tracking. Experiments results prove that the accuracy of sensor choice using the improved formula was improved 37.5% than the previous algorithm. This algorithm of data fusion and choice strategy can realize autonomous track in several typical scene of sensor-invalid.

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references

KALMAN R E. A new approach to linear filtering and prediction problems[J]. Journal of Basic Engineering , 1960, 82(1): 35-45.

SORENSON H W. Kalman Filtering: Theory and Application [M]. New York: IEEE Press, 1985.

UHLMANN J K. Algorithm for multiple target tracking[J]. American Science , 1992, 80(2): 128-141.

JULIER S, UHLMANN J, DURRANT-WHYTE H F. A new method for the nonlinear transformation of means and covariances in filters and estimators[J]. IEEE Transactions on Automatic Control , 2000, 45(3): 477-482.

ARULAMPALAMM S, MASKELL S, GORDON N, et al . A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking[J]. IEEE Transactions on Signal Processing , 2002, 50(2): 174-188.

DJURICP M, KOTECHA J H, ZHANG J Q, et al . Particle filtering[J]. IEEE Signal Processing Magazine , 2003, 20(5): 19-38.

高青.多传感器数据融合算法研究[D].西安:西安电子科技大学, 2008:14-15.

GAO Q.Study of multisensor data fusion algorithms[D]. Xi'an: Xi'an University of Electronical Technology , 2008: 14-15. (in Chinese)

何友, 陆大(丝金), 彭应宁, 等.带反馈信息的分布多传感器航迹融合算法[J].电子科学学刊, 2000, 22(5):705.

HE Y, LU D J, PENG Y N, et al . Distributed multi-sensor track fusion algorithm with feedback information[J]. J. Electronis , 2000, 22(5): 705. (in Chinese)

程国英, 张淑梅, 蔡盛, 等.实时特征级数据融合系统在光电经纬仪上的应用[J].光学精密工程, 2008, 16(11):2151-2157.

CHENG G Y, ZHANG S M, CAI S, et al . Application of real-time feature level multi-sensor data fusion system to photoelectric theodolite[J]. Optics and Precision Engineering , 2008, 16(11): 2151-2157. (in Chinese)

苏秀琴, 郝伟, 李哲.一种基于光电经纬仪的数据预测跟踪技术[J].光子学报, 2008, 37(7):1464-1467.

SU X Q, HAO W, LI Z. A tracking technique based on data forecast of photoelectric theodolite[J]. Acta Photonica Sinica , 2008, 37(7): 1464-1467. (in Chinese)

LI S Q, ZHANG S X. A congeneric multi-sensor data fusion algorithm and its fault-tolerance[C]. Proceedings of the 2010 International Conference on Computer Application and System Modeling (ICCASM 2010) , Taiyuan: IEEE, 2010: 339-340.

ZHAO J, HU S Q. A new adaptive weighted fusion algorithm for multi-sensor tracking[C]. Proceedings of the 2002 International Conference on Machine Learning and Cybernetics , Beijing: IEEE, 2002: 285-287.

石章松, 刘忠, 王航宇, 等.目标跟踪与数据融合理论及方法[M].北京:国防工业出版社, 2010:54-57.

SHI S Z, LIU Z, WANG H Y, et al . Method and Theory of Target Tracking and Data Fusion [M]. Beijing: National Defend Industry Press , 2010: 54-57. (in Chinese)

杜超, 刘伟宁, 刘恋.一种基于卡尔曼滤波及粒子滤波的目标跟踪算法[J].液晶与显示, 2011, 26(3):384-389.

DU C, LIU W N, LIU L. Target tracking algorithm based on Kalman filter and particle filter[J]. Chinese Journal of Liquid Crystals and Displays , 2011, 26(3): 384-389. (in Chinese)

张品, 董为浩, 高大冬.一种优化的贝叶斯估计多传感器数据融合方法[J].传感技术学报, 2014, 27(5):643-648.

ZHANG P, DONG W H, GAO D D.AN optimal method of data fusion for multi-sensors based on Bayesian estimation[J]. Chinese Journal of Sensors and Actuators , 2014, 27(5): 643-648. (in Chinese)

龙辉平, 习胜丰, 侯新华.实验数据的最小二乘拟合算法与分析[J].计算技术与自动化, 2008, 27(3):20-23.

LONG H P, XI S F, HOU X H. The algorithm and analysis from experiment data by means of minimum double multiplication[J]. Computing Technology and Automation , 2008, 27(3): 20-23. (in Chinese)

王威立, 郭劲, 曹立华, 等.基于神经网络极限学习机数据融合的共轴跟踪[J].光学精密工程, 2013, 21(3):751-758.

WANG W L, GUO J, CAO L H, et al . On-axis tracking based on ELM data fusion[J]. Optics and Precision Engineering , 2013, 21(3): 751-758. (in Chinese)

陈大庆, 韩九强, 于志坚.融合距离信息的红外自适应相关跟踪[J].光学精密工程, 2010, 18(8):1862-1868.

CHEN D Q, HAN J Q, YU Z J. Infrared adaptive correlation tracking of fusing distance information[J]. Optics and Precision Engineering , 2010, 18(8): 1862-1868. (in Chinese)

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