期刊文献+

WSN目标定位动态预测方法研究 被引量:3

Study on the Method of Adaptable Target Tracking Prediction in WSN
在线阅读 下载PDF
导出
摘要 针对固定预测时间间隔下目标机动对无线传感器网络目标定位预测效果影响较大的问题,分析目标预测误差产生机理及主要影响因素,提出WSN目标定位动态预测方法。该方法根据目标预测模型构造预测时间增量函数,通过固定预测时间增量函数取距离自变量值动态调节目标预测时间间隔,实现目标运动状态自适应动态目标预测。仿真平台分别应用运动学预测、粒子滤波预测方法建立预测模型,并进行目标预测实验;结果表明,目标机动情况下,目标动态预测方法误差相比固定预测时间时间间隔方法分别减小18.5%、12.8%,动态目标预测方法能较好改善机动性目标预测效果,增强预测方法对目标运动变化的自适应能力。 Aiming at the problem of target tracking in wireless sensor networks (WSN) based on fixed prediction time interval, a method of target tracking dynamic prediction in WSN is proposed. Error mechanism of target tracking and the major factors which influence the prediction error are researched. Increment function of prediction time is built based on target prediction model. Using different value for distance independent variable of increment function of prediction time, adjusting prediction time interval dynamically and achieving target dynamic pre- diction based on target motion state adaptively. Prediction models are built using quadratic polynomial motion modeling method and particle filter method individually. Experimental results show that prediction effect and adaptive ability of prediction method for maneuvering target are improved using dynamic prediction method. When target maneuvers, prediction error of dynamic method decreased by 18. 5% and 12.8% respectively in compare with fixing prediction time interval method.
出处 《计算机测量与控制》 CSCD 北大核心 2012年第3期645-647,共3页 Computer Measurement &Control
基金 国家自然科学基金项目(50764005) 广东省自然科学基金项目(9151052101000013)
关键词 无线传感器网络 目标定位 动态预测 预测误差 wireless sensor network (WSN) target localization adaptable prediction prediction error
  • 相关文献

参考文献10

  • 1Xiao W D,Xie L H,Lin J Y,et al.Multi-sensor scheduling for reliable target tracking in wireless sensor networks[A].Proc.of 6th International Conference on ITS Telecommunications[C].2007:996-1000.
  • 2焦竹青,熊伟丽,张林,徐保国.基于曲线拟合的无线传感器网络目标定位算法[J].东南大学学报(自然科学版),2008,38(A01):249-252. 被引量:13
  • 3Liu X Q,Zhao G,Ma X L.Target localization and tracking in noisy binary sensor networks with known spatial topology[J].Wireless Communications and Mobile Computing,2009,9(8):1028-1039.
  • 4Wang X,Ding L,Wang S.Multi-step optimized measurement in hierarchically clustered wireless sensor networks[J].Jixie Gongcheng Xuebao,2009,45(4):1-7.
  • 5Yick J,Mukherjee B,Ghosal D.Analysis of a prediction-based mobility adaptive tracking algorithm[A].Proc.of2nd Internation-al Conference on Broadband Networks(Broadnets)(IEEE Cat.No.05EX1116)[C].Boston,MA USA,2005.
  • 6Majdi M R,Cuello A.C.Variations in excitatory and inhibitory posts-ynaptic protein content in rat cerebral cortex with respect to aging and cognitive status[J].neuoscience,2009;159:896-907.
  • 7Gu Y,Zhang W,Liu H C,et al.Energy-efficient target localiza-tion based on a prediction model[A].Proc.of EUC2005Work-shops:UISW,NCUS,SecUbiq,USN,and TAUES[C].Nagasa-ki,Japan,2005,3823(LNCS):1178-1190.
  • 8张晓平,刘桂雄.基于二次多项式运动建模的WSN目标跟踪预测[J].暨南大学学报(自然科学与医学版),2009,30(5):474-478. 被引量:6
  • 9刘桂雄.一种基于自适应预测的无线传感器网络目标跟踪方法[P].CN:ZL200910076212.7.
  • 10黄奕微,张晓平,刘桂雄,何学文.粒子滤波实现无线传感器网络目标跟踪预测[J].计算机测量与控制,2010,18(4):930-932. 被引量:6

二级参考文献30

  • 1邓小龙,谢剑英,郭为忠.用于状态估计的自适应粒子滤波[J].华南理工大学学报(自然科学版),2006,34(1):57-61. 被引量:10
  • 2黄仑,徐昌庆.无线传感器网络目标跟踪机制的研究与改进[J].计算机工程与应用,2006,42(16):140-142. 被引量:6
  • 3Perillo M, Heinzelman W. Wireless sensor network[M]. Netherlands: Kluwer Academic Publishers, 2004.
  • 4Sheng Xiaohong, Yu Henhu. Sequential acoustic energy based source localization using particle filter in a distributed sensor network[C]// IEEE International Conference on Acoustics, Speech, and Signal Processing. Piscataway, USA: IEEE, 2004: 961-972.
  • 5Mechitov K, Sundresh S, Kwon Y, et al. Cooperative tracking with binary detection sensor networks[C]//Proceedings of the 1st International Conference on Embedded Networked Sensor Systems. New York: ACM Press, 2003: 332-333.
  • 6Kim W Y, Mechitov K. On target tracking with binary proximity sensors[C]//4th International Conference on Information Processing Sensor Networks. Piscataway, USA: IEEE, 2005: 125-129.
  • 7Chen Weipeng, Hou J C, Liu Sha. Dynamic clustering for acoustic target tracking in wireless sensor networks[C]//Proceedings of IEEE International Conference on Network Protocols. Piscataway, USA: IEEE, 2003: 284-294.
  • 8Kiasi F. An interpolative fuzzy inference using least square principle by means of β2function and high order polynomials[C]// Proceedings of the IEEE International Conference on Mechatronics & Automation Niagara Falls. Toronto, Canada, 2005: 829-836.
  • 9Zhang W, Cao G. DCTC: dynamic convoy tree-based collaboration for target tracking in sensor networks [J]. IEEE Transactions on Wireless Communication, 2004, 3 (5): 1689-1701.
  • 10Shin J, Guibas L, Feng Zhao. A distributed algorithm for managing multitarget identities in wireless ad hoc sensor networks[C]//Proceedings of 2nd Workshop on Information Processing in Sensor Networks. Palo Alto, USA: Springer Press, 2003: 223-238.

共引文献20

同被引文献31

  • 1蒋翠清,杨善林,黄梯云,梁昌勇.基于Agent的动态负载均衡技术及仿真实现[J].微电子学与计算机,2005,22(10):47-50. 被引量:9
  • 2陈维克,李文锋,首珩,袁兵,魏兰.基于卡尔曼滤波的WSNs节点定位研究[J].武汉理工大学学报,2007,29(8):112-116. 被引量:16
  • 3Dimitris. E Manolakis Efficient Solution and Performance Analysis of 3--D position Estimation by Trilateration [J]. IEEE Trans on AES, 1996, 32 (4): 1239-1248.
  • 4Farina A. Target Tracking with Bearings Only Measurements [J]. Signal Proeessing, 1999, 78: 61-78.
  • 5Tichvasky P, Muravchik C H, Nehorai A. Posterior Cram6r Rao Bounds for Discrete--Time Nonlinear Filtering [J]. IEEE Trans on Signal Processing, 1999, 46 (5) : 1386 - 1395.
  • 6Yang H C, All D, Hsiao R L, et al. Map reduce-merge: sim- plified relational data processing on large clusters [A]. proceedings of the Proceedings of the 2007 ACM SIGMOD international confer- enee on Management of data [C]. 2007:1029 - 1040.
  • 7Barker K, et al. A load balancing framework for adaptive and asyn- chronous applications [J]. Parallel and Distributed Systems, IEEE Transactions on, 2004, 15 (2)7 183 -192.
  • 8Renard H, Robert Y, Vivien F. Static load balancing techniques for iterative computations on heterogeneous clusters [J]. Euro- Par2003 ParallelProeessing, 2003, 2790. 148-159.
  • 9Willebeek-lemair Marc H, Reeves Anthony P. Strategies for dy- namic load balancing on highly parallel computers[J]. Parallel and Distributed Systems, IEEE Transactions on, 1993, 4 (9): 979 -993.
  • 10Zhang X Y, Yu Y Q, Chen B X, et al. An extension-based dy- namic load balancing model of heterogeneous server cluster [A]. proceedings of the Proceedings 2007 IEEE International Conference on Granular Computing [C]. F, 2007: 675.

引证文献3

二级引证文献12

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部