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计算机科学 ›› 2015, Vol. 42 ›› Issue (12): 76-81.

• 第十三届全国软件与应用学术会议 • 上一篇    下一篇

结合运动方程与卡尔曼滤波的动态目标追踪预测算法

王妍,邓庆绪,刘赓浩,银 彪   

  1. 东北大学信息与工程学院 沈阳110819;辽宁大学信息科学与技术学院 沈阳110036,东北大学信息与工程学院 沈阳110819,辽宁大学信息科学与技术学院 沈阳110036,辽宁大学信息科学与技术学院 沈阳110036
  • 出版日期:2018-11-14 发布日期:2018-11-14
  • 基金资助:
    本文受国家自然科学基金(61472072),国家科技支撑计划(2012BAF13B08),国家“九七三”重点基础研究发展计划前期研究专项(2014CB360509),辽宁省科学事业公益研究基金项目(2015003003)资助

Dynamic Target Tracking and Predicting Algorithm Based on Combination of Motion Equation and Kalman Filter

WANG Yan, DENG Qing-xu, LIU Geng-hao and YIN Biao   

  • Online:2018-11-14 Published:2018-11-14

摘要: 针对传统定位技术误差较大且无法预测目标位置等问题,提出了一种结合运动方程与卡尔曼滤波的动态目标追踪预测算法ME-KF。通过运动方程模拟动态目标运动特性,利用卡尔曼滤波来减小干扰噪声对测量结果的影响,并预测下一时刻的目标位置。该算法在辽宁排山楼矿井的人员定位系统中得到了实际应用,并取得了显著成果。实验结果表明,该方法提高了定位精度,能够对人员位置进行预测以及对危险区域进行预警,并且成功地分析判断了障碍物的分布状况。

关键词: 无线定位,运动方程,卡尔曼滤波,动态目标

Abstract: In the view of problem that the traditional location technology is erroneous greatly,and can not predict the position of the target,this paper presented a dynamic target tracking and predicting algorithm ME-KF combining motion equation and Kalman filter,which simulates the motion characteristics of dynamic target by motion equation,reduces the influence of noise on the measurement results and predicts the position of the target in the next moment.This algorithm has been practically applied to personnel location system of Liaoning Paishanlou mine and has made remarkable achievements.The experimental results show that this method improves the precision of location,predicts people positions,makes early warning of possibly dangerous areas,and can also successfully analyze the distribution of obstacles.

Key words: Wireless location,Motion equation,Kalman filter,Dynamic target

[1] Guo Z W,Guo Y,Hong F,et al.Perpendicular intersection:Locating wireless sensors with mobile beacon[J].IEEE Trans.on Vehicular Technology,2010,59(7):3501-3509
[2] Han G J,Xu H H,Duong T,et al.Localization algorithms ofwireless sensor networks:A survey[J].Telecommunication Systems,2013,52(4):2419-2436
[3] Nekooei S M,Manzuri-Shalmani M T.Location finding in wireless sensor network based on soft computing methods[C]∥Proc.of the 2011 Int’l Conf.on Control,Automation and Systems Engineering (CASE).Singapore,2011:1-5
[4] Kulkarni R V,Frster A,Venayagamoorthy GK.Computational intelligence in wireless sensor networks:A survey[J].Communications Surveys & Tutorials,2011,13(1):68-96
[5] 叶苗,王宇平.基于变方差概率模型和进化计算的WSN定位算法[J].软件学报,2013,4(4):859-872 Ye M,Wang Y P.Location estimation in wireless sensor networks based on probabilistic model with variant variance and evolutionary algorithm[J].Journal of Software,2013,4(4):859-872
[6] C Hong-yang,D Ping,X Yong-jun,et al.A robust location algorithm with biased extended Kalman filtering of TDOA data for wireless sensor networks[C]∥Proceedings.2005 International Conference on Wireless Communications,Networking and Mobile Computing,2005.IEEE,2005,2:883-886
[7] Chung W C,Ha D S.An accurate ultra wideband (UWB) ranging for precision asset location[C]∥2003 IEEE Conference on Ultra Wideband Systems and Technologies.IEEE,2003:389-393
[8] 崔逊学,卢松升,陈云飞,等.基于短基线传感器网络的远场声源TDOA定位组合算法[J].计算机研究与发展,2014,1(3):465-478 Cui X X,Lu S S,Chen Y F,et al.Combination TDOA Localization Algorithms for Far-Field Sound Source Based on Short Base-Line Sensor Network[J].Journal of Computer Research and Development,2014,1(3):465-478
[9] 肖竹,谭光华,李仁发,等.无线传感器网络中基于超宽带的TOA/AOA联合定位研究[J].计算机研究与发展,2013,0(3):453-460 Xiao Z,Tan G H,Li R F,et al.Joint TOA/AOA Localization Based on UWB for Wireless Sensor Networks[J].Journal of Computer Research and Development,2013,0(3):453-460
[10] 牛建伟,刘洋,卢邦辉,等.一种基于Wi-Fi信号指纹的楼字内定位算法[J].计算机研究与发展,2013,0(3):568-577 Niu J W,Liu Y,Lu B H,et al.An In-Buliding Localization Algorithm Based on Wi-Fi Signal Fingerprint[J].Journal of Computer Research and Development,2013,0(3):568-577
[11] Bulusu N,Heidemann J,Estrin D.GPS-less low-cost outdoor localization for very small devices[J].Personal Communications,IEEE,2000,7(5):28-34
[12] 王新生,赵衍静,李海涛.基于DV-Hop定位算法的改进研究[J].计算机科学,2011,8(2):76-78 Wang X S,Zhao Y J,Li H T.Improved Study Based on DV-Hop Localization Algoritnm[J].Computer Science,2011,8(2):76-78
[13] Kalman R E.A new approach to linear filtering and prediction problems[J].Journal of Fluids Engineering,1960,82(1):35-45

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