【作者】 冯颖；

【导师】 赵欢；

【作者基本信息】 湖南大学 ， 计算机应用技术， 2007， 硕士

【摘要】 传感器网络是计算机技术、通信技术中一个新的研究领域,它采用无线通信技术,由微小的传感器组成,节点具备感应能力、信息处理能力和无线通信能力,无线传感器网络可广泛用于军事、环境、医疗保健、空间探索、减灾救灾及各种商业领域。定位和目标跟踪是无线传感器网络研究的重点,研究热点主要包括:降低无线传感器网络的功耗,尽量延长整个无线传感器网络的寿命;提高节点定位精度;增加目标运动轨迹的真实性。本文首先详细介绍了无线传感器网络的定位算法和目标跟踪算法国内外研究现状,并对各种不同的定位算法进行了分类总结。针对目前应用的实际情况,本文建立了一个目标跟踪模型,增加了移动节点与信标节点结合定位的功能。本模型详细描述了信标节点坐标预配置过程,模型工作采用移动节点主动请求获得信标节点提供定位服务的方式。本文利用物体运动的连续性,将运动规律预测与距离测量相结合提出运动预测定位算法,该算法不需要额外的硬件支持,并且适应能力非常强,尤其在信标节点密度比较低的时候,获得了比较大的定位成功率和较高的精度。本文分析了Velocity Adaptive Target Tracking(VATT)算法的优点和不足,把加速度和运动方向作为新的目标跟踪预测条件来改进VATT算法,提高了轨迹描述的真实性。最后,本文根据通用的算法性能评价标准,在仿真实验的基础上,采集了大量数据,与同类型算法进行比较,实验结论显示运动预测定位算法和改进后的VATT算法性能都有明显的提升。更多还原

【Abstract】 Sensor network is a new research area of computer science and technology,which consisting of many tiny sensors using wireless communication technologies. The wireless sensor network node has the ability of sensing, data processing and wireless communication. The wireless sensor network has a wide range of application prospects and can be used in military, environmental, health, space exploration and many other kinds of commercial applications.Localization and target tracking are fundamental and crucial issues for wireless network operation and management. Target tracking aims to be greater energy efficiency and more tracking accuracy.This can prolong the lifetime of the wireless sensor network.Firstly,we have present the state of research around the world of localization and target tracking.And we classify those localization arithmetic with their property.Secondly,we have built a model of wireless sensor network for application,in which we use mobile node as anchor node to lacalization.Then the model describe the process of how to configure the coordinate of anchor node.Mobile node will be active while the model is tracking target.After receiving messages from mobile nodes,anchor nodes provide localization service for mobile nodes.Using the continuity of object’s motorial, this paper combines prediction of movement with distance measure and bring forward localization arithmetic with prediction of movement.This arithmetic doesn’t need any additional hardware, and has wonderful adaptation capability. Especially in the moment when the density of beaconing node is little, it can obain larger correct odds and higher precision. We analyze the advantage and disadvantage of velocity adaptive target tracking(VATT) later. When tracking the target, we use acceleration and movment direction which are taken as the condition of prediction of movement to improve VATT. So we get more veritable track description.Finally,We provide some more intuitionistic criterions,which are evolved from universal criterions.Then we experiment to get a lot of useful data.Using these data,We compare the performance of similar arithmetics roundly.更多还原