韩小卫毕业论文（最终版本） - 图文

哈尔滨工业大学工学硕士学位论文

摘要

无线传感器网络，也称感知网，是一种由大量体形小、成本低，具有通信能力的传感器通过ad hoc方式形成的网络。其能够实时获取、分析、融合周边环境信息，反馈给后台用户，在环境监测、设备管理、公共安全、医疗和军事应用等方面有着广泛的用途。其中目标跟踪研究是一个很重要的应用研究分支，在野生动物追踪、智能交通、战场监控等应用中作用举足轻重。本文在改进已有单目标跟踪算法的基础上，提出了一种感知网多目标的跟踪框架。

首先针对高信噪比环境特点，提出了一种新的“距离-量测”定位算法。算法通过对先期目标信息的存储和节点感知区域的划分，对定位精度和计算复杂度以及可靠性进行折中，在满足需要的条件下，提高了定位效率。

如何节省节点能耗，是感知网目标跟踪研究的一个重点问题。本文基于目标动向预测跟踪簇算法，对动态簇簇首的产生机制进行改进，提出了“太子簇首-异常-竞争”算法。算法首先根据历史预测结果对节点进行分类，然后根据分类结果预定最合适的节点作为下一定位时刻的簇首，从而摒弃以往算法中多节点竞争或选举的簇首产生机制，减少信号发送，从而节省了能量。 多目标环境下，目标间距离由远及近，其对节点的共同影响程度将随之增大，从而产生多目标的信号关联问题。本文通过对目标间远近距离的场景分析建立多目标跟踪框架。即“远距离单目标精确跟踪-稀疏多目标类精确跟踪和密集多目标集群跟踪”。

多目标类精确跟踪针对稀疏多目标情况下问题分析，对单目标的“太子簇首-异常-竞争”跟踪算法进行修正。加入时间戳机制，根据预测信息对节点量测进行分解，从而实现目标的量测信号关联，对每个目标区分跟踪。

多目标集群跟踪将所有目标视为一个整体。本文通过对集群簇的形成、定位、持续、合并和分解的条件及具体过程的分析，描述了集群跟踪算法的整体框架以及类精确跟踪与集群跟踪的相互转换过程。

最后，设计和实现了基于Mica2平台的原型系统和仿真系统。原型系统用于目标定位算法和单目标“太子簇首-异常-竞争”跟踪算法的可行性验证；仿真系统验证多目标类精确跟踪和集群跟踪算法的有效性。

关键词 目标定位；多目标跟踪；动态簇；感知网

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哈尔滨工业大学工学硕士学位论文

Abstract

Wireless Sensor Networks is a new kind of ad hoc network platform which is composed by large number of small size, low-cost and wireless communication sensors. It can real-time acquire, analyse and integrate the information of surrounding environment, then feed back to the remote users. Consequently, it has a wide range of use in environment monitoring, equipment management, public security, medical treatment and military affairs. Target tracking is an important research branch in applied research area. It plays a pivotal role in wild-animal tracking, intelligent transportation, and battlefield surveillance and so on. In this article, we improved the single-target tracking algorithm in sensor networks， then based on it, we proposed a multi-target tracking framework.

Firstly we compared many localization algorithms and proposed a new \localization algorithm. In the new algorithm we stored the advanced information of targets and divided the perceptive region of nodes. It can improve the localization accuracy and reliability and reduce the computational complexity. The efficiency of localization has been improved.

To reduce energy consumption of nodes is a very important issue of target tracking in sensor networks. Based on dynamic prediction cluster algorithm, we proposed \classified the nodes based on the historical prediction results, and then according to the classification results to choose the most suitable node as the cluster header for next locate moment. This mechanism avoided the competition and election among the nodes, reduced the signal transmission and saved energy.

Under the circumstances of multiple targets, as the distance between the targets become nearer, the conjunct impact to nodes become larger, thus bringing signal association problems. According to the scene analysis that the distance changes continuously we proposed the multi-target tracking framework: \distance single-target precise tracking—Sparse multi-target close-precise tracking and Dense multi-target group tracking.\

Multi-target close-precise tracking modified the \Cluster Header - Abnormal-Competition\algorithm in single-target tracking. Introduced

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哈尔滨工业大学工学硕士学位论文

timestamp mechanism, based on predictions of information we decomposed the nodes? measure, thus associating the signal measures for each target and tracking each target respectively.

Multi-target group tracking regards all the targets as a whole unit. Based on the group clusters? formation, localization, sustainment, mergence and decomposition process, we described the whole framework of the group tracking algorithm and the conversion process between the close-precision tracking and the group tracking.

Finally, we designed and implemented the prototype system based on Mica2 Platform and the simulation system. The prototype system was used for valida- ting the feasibility of the target location algorithm and the \- Abnormal-Competition\-tem validated the multi-target close-precise tracking algorithm and the multi-tar- get group tracking algorithm.

Keywords Target Localization; Multiple-Target Tracking; Dynamic Cluster;

Sensor Networks

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哈尔滨工业大学工学硕士学位论文

目录

摘要 ............................................................................................................................... I Abstract ....................................................................................................................... II 第1章 绪论 ................................................................................................................ 1 1.1 课题背景 ........................................................................................................... 1 1.1.1 课题来源 .................................................................................................... 1 1.1.2 课题研究目的及意义 ................................................................................ 1 1.2 与课题相关的国内外研究综述 ....................................................................... 2 1.2.1 国内外关于感知网的研究现状 ................................................................ 2 1.2.2 感知网目标定位与跟踪技术的研究现状 ................................................ 3 1.3 本文的主要研究内容 ....................................................................................... 5 1.3.1 感知网单目标定位与跟踪算法研究 ........................................................ 6 1.3.2 感知网多目标跟踪算法的研究 ................................................................ 6 1.3.3 论文结构 .................................................................................................... 7 第2章 感知网单目标定位跟踪算法研究 ................................................................ 8 2.1 距离-量测定位算法 ......................................................................................... 8 2.1.1 基于感知能量的定位算法 ........................................................................ 8 2.1.2 距离-量测定位算法 ................................................................................ 11 2.1.3 仿真验证 .................................................................................................. 19 2.2 “太子簇首-异常-竞争”单目标跟踪算法 .................................................. 21 2.2.1 节点分类机制 .......................................................................................... 21 2.2.2 “太子簇首-异常-竞争”算法 ............................................................... 22 2.2.3 仿真验证 .................................................................................................. 27 2.3 本章小结 ......................................................................................................... 29 第3章 感知网多目标跟踪算法研究 ...................................................................... 30 3.1 多目标场景分析及跟踪框架 ......................................................................... 30 3.2 稀疏多目标类精确跟踪算法 ......................................................................... 31 3.2.1 问题分析 .................................................................................................. 31 3.2.2 时间戳机制 .............................................................................................. 32 3.2.3 基于预测信息的信号分解 ...................................................................... 34 3.2.4 动态簇协议的修正 .................................................................................. 36

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哈尔滨工业大学工学硕士学位论文

3.2.5 节点触发机制 .......................................................................................... 38 3.2.6 算法仿真结果 .......................................................................................... 41 3.3 多目标集群跟踪算法 ..................................................................................... 42 3.3.1 算法思想描述 .......................................................................................... 42 3.3.2 集群簇的形成 .......................................................................................... 43 3.3.3 多目标定位方法及集群簇的维持 .......................................................... 45 3.3.4 集群簇的合并与分解 .............................................................................. 51 3.3.5 算法实验仿真 .......................................................................................... 57 3.4 本章小结 ......................................................................................................... 58 第4章 感知网多目标跟踪系统设计与实现 .......................................................... 59 4.1 系统总体设计 ................................................................................................. 59 4.2 基于MICA2平台的原型系统设计与实现 .................................................. 60 4.2.1 原型系统总体设计 .................................................................................. 60 4.2.2 节点端系统设计与实现 .......................................................................... 61 4.2.3 基站端跟踪平台设计与实现 .................................................................. 68 4.2.4 跟踪的实现 .............................................................................................. 70 4.3 多目标跟踪仿真系统设计与实现 ................................................................. 72 4.3.1 场景配置功能模块 .................................................................................. 72 4.3.2 模拟系统框架 .......................................................................................... 73 4.3.3 类精确跟踪算法的实现 .......................................................................... 75 4.3.4 集群跟踪算法的实现 .............................................................................. 78 4.4 系统测试案例 ................................................................................................. 80 4.4.1 Mica2平台原型子系统测试 .................................................................... 80 4.4.2 仿真系统测试 .......................................................................................... 82 4.5 本章小结 ......................................................................................................... 82 结论 ............................................................................................................................ 83 参考文献 .................................................................................................................... 85 攻读学位期间发表的学术论文 ................................................................................ 90 哈尔滨工业大学硕士学位论文原创性声明 ............................................................ 91 哈尔滨工业大学硕士学位论文使用授权书 ............................................................ 92 哈尔滨工业大学硕士学位涉密论文管理 ................................................................ 93 致谢 ............................................................................................................................ 94

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