基于马尔可夫链模型的井下目标轨迹预测算法

计算机科学 ›› 2014, Vol. 41 ›› Issue (Z6): 321-323.

基于马尔可夫链模型的井下目标轨迹预测算法

孟凡振,吴杰,卜旭松,冯锋

宁夏大学数学计算机学院银川750021;宁夏大学数学计算机学院银川750021;宁夏大学数学计算机学院银川750021;宁夏大学数学计算机学院银川750021

出版日期:2018-11-14 发布日期:2018-11-14
基金资助:
本文受宁夏自然科学基金重点项目(NZ13004)资助

Underground Target Track Prediction Algorithm Based on Markov Chain Model

MENG Fan-zhen,WU Jie,BU Xu-song and FENG Feng

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

摘要/Abstract

摘要： 针对井下环境恶劣,信标节点失效时会存在大量盲区,提出了一种基于马尔可夫链模型的井下目标轨迹预测算法,利用现有的无线传感器网络和无线射频识别技术,结合马尔可夫链模型对目标运动轨迹进行预测,并对传统的质心定位算法加以改进,使其适应预测模型,同时减少定位误差,提高定位覆盖率。实验证明:所提算法在百米范围内误差较小,可实现准确定位预测。

关键词: 目标轨迹预测,马尔可夫链,无线传感器网络,无线射频识别,质心定位算法中图法分类号TP393.08文献标识码A

Abstract: In view of the downhole conditions,the beacon node failure will exist a large number of blind area,this paper proposes a underground target track prediction algorithm based on markov chain model,the use of the existing wireless sensor networks and wireless radio frequency identification technology,combined with markov chain model to estimate target motion track,and the traditional centroid localization algorithm is improved,and adapt it to the prediction model,at the same time reduce the positioning error,improve the positioning coverage．Experimental results show:in hundreds of meters range error is smaller,which can realize accurate positioning.

Key words: Target track prediction,Markov chain,Wireless sensor network,Radio frequency identification,Centroid localization algorithm

孟凡振,吴杰,卜旭松,冯锋. 基于马尔可夫链模型的井下目标轨迹预测算法[J]. 计算机科学, 2014, 41(Z6): 321-323. https://doi.org/

MENG Fan-zhen,WU Jie,BU Xu-song and FENG Feng. Underground Target Track Prediction Algorithm Based on Markov Chain Model[J]. Computer Science, 2014, 41(Z6): 321-323. https://doi.org/

参考文献

[1] Wang Yang,Huang Liu-sheng,Xiao Ming-jun,et al．Localization algorithm for wireless sensor network based on RSSI-verify[J]．Journal of Chinese Computer Systems,2009,30(1):59-62
[2] Chen Kai,Zhou Yi,He Jian-hua．A localization scheme for un-derwater wireless sensor networks [J]．International Journal of Advanced Science and Technology,2009,4:9-16
[3] 李万高,赵雪梅,孙德厂.基于改进贝叶斯方法的轨迹预测算法研究[J].计算机应用,2013,33(7):1960-1963
[4] Savvides A C,Han M,Srivastava B.Dynamic Finegrained Loca-lization In Ad-Hoc Networks of Sensors[C]∥Proc.of the 7th Annual ACM/IEEE International Conferece on Mobile Computing and Networking(MobiCom’ 01)．New York,2001(7):166-167
[5] Bahl P,Padmanabhan V.RADAR:an In-building 'RF-based User Location and Tracking System [C]∥Proc.of IEEE INFOCOM’02．Tel Aviv,Israel,2000(2):775-784
[6] Bulusu N,Heidemann J,Estrin D.GPS-less low Cost Outdoor Localization for Very Small Devices[J]．IEEE Personal Communications,2000,7(5):28-34
[7] Niculescu D,Nath B.DV-based Positioning in Ad Hoc Networks[J].Kluwer Journal of Telecommunications Systems,2003,2(1-4):267-280
[8] He T,et al.Range-free Localization Schemes in Large Scale Sen-sor NetWorks[C]∥Proc.of the 9th Annual ACM/IEEE International Conference on Mobile Computing and Networking(Mobicom’ 03)．New York,2003(9):81-95
[9] Ss K-F,Ou C-H,Jiau H C.Location with Mobile Anchor Pointsin Wireless Sensor Networks [J].IEEE Transations on Vehicular Technology,2005,4(3):1187-1197
[10] Carbunar B,Ramathan M K,Mehmet Koyuturk,et al．Efficient tag detection in RFID systems[J]．J．Parallel Distrib．Comput.,2009,69:180-195
[11] 彭曲,丁治明,郭黎敏.基于马尔可夫链的轨迹预测[J]．计算机科学,2010,37(8):189-193
[12] 丁恩杰,乔欣,常飞.基于RSSI的WSNs加权质心定位算法的改进[J].传感器与微系统,2013,32(7):53-56
[13] 韩东升,杨维,刘洋．煤矿井下基于RSSI的加权质心定位算法[J]．煤炭学报,2013,38(3):522-528
[14] 田丰,秦涛,刘华艳.煤矿井下无线型无线传感器网络节点定位算法[J].煤炭学报,2010,35(10):1760-1764

Metrics

Viewed

Full text

Abstract

Cited

Shared

Discussed