论文总字数：23833字

摘 要

近年来，随着通信网络的不断发展，各种移动终端的普及，人们对于定位服务提出的要求越来越高。而GPS等全球卫星导航系统很难在城市、室内等场景中提供优质的定位服务，因此，越来越多的研究者将研究方向投在了其他定位技术上。随着无线传感器网络的不断普及，基于无限传感器网络的定位技术受到广大研究者的青睐，为定位技术提供了新的方向。

RSS目标定位技术是比较简单的无线传感器网络定位技术，可使用位置指纹法和距离法定位，而这两种方法需要消耗大量硬件资源和网络资源，且定位精度有待提升。针对RSS目标定位技术的目标位置信息具有稀疏性，提出了基于压缩感知的两阶段定位算法，该算法将目标定位问题转换为网格选择问题，分为粗定位与精定位两阶段。在粗定位阶段，通过观测矩阵得到观测向量，然后利用最优化问题重构出稀疏信号，得到目标所在候选网格；精定位阶段，通过不断将候选网格四等分划分，并且更新观测矩阵，接收到新的观测向量，根据最小残差准则得到目标所在的小网格，小网格中心即为目标所在位置。通过仿真实验验证，这种改进的两阶段目标定位算法比传统的OMP与GMP算法有着更优异的定位性能，不仅能提升定位精度、降低定位系统成本，还具备一定的抗干扰能力。

关键字：无线传感器网络 目标定位 压缩感知 稀疏重构

Design of Target Location Algorithm Based on RSS

ABSTRACT

In recent years, with the continuous development of communication network and the popularity of various mobile terminals, people put forward higher and higher requirements for location service. However, it is difficult for GPS and other global satellite navigation systems to provide high-quality positioning services in urban and indoor scenes. Therefore, more and more researchers are focusing on other positioning technologies. With the continuous popularization of wireless sensor network, the location technology based on wireless sensor network is favored by the majority of researchers, which provides a new direction for the location technology.

RSS target location technology is a relatively simple location technology for wireless sensor network, which can use location fingerprinting method and distance method, but these two methods need to consume a lot of sensor node resources and network resources, and the positioning accuracy needs to be improved. According to the sparsity of RSS-based target location technology, a two-stage location algorithm based on compressed sensing is proposed. In the coarse location stage, the measurement vector is obtained by applying the measurement matrix, and then optimization problem is used to reconstruct the sparse signal, whose the locations of nonzero elements correspond to the candidate grid the targets located. In the fine location stage, the candidate grid is divided into four sections continuously, and the measurement matrix is updated to receive the new measurement vector. The small grid the target located is obtained by applying the minimum residual criterion, and the center of the small grid is the location of a target. Simulation experiments show that the improved two-stage target location algorithm has better location performance than the traditional OMP and GMP algorithms. The proposed algorithm cannot only improve the positioning accuracy, but also has the ability of anti-interference.

Key words: Wireless sensor network; target location; compressed sensing; sparsity reconstructio

目录

摘 要 I

ABSTRACT II

第一章 绪论 1

1.1 课题研究的背景 1

1.2 课题研究的价值 2

1.3 国内外研究现状 3

1.3.1 测距定位法 3

1.3.2 RSS目标定位法 4

1.3.3 CS目标定位法 5

1.4 课题研究的内容 6

1.5 论文组织结构 7

第二章 基于RSS的目标定位系统 8

2.1 RSS目标定位模型 8

2.2 CS目标定位系统 10

2.2.1 CS原理 10

2.2.2 CS目标定位模型 11

2.3 本章小结 12

第三章 基于RSS的两阶段目标定位算法 13

3.1 传统目标定位算法分析 13

3.2 两阶段目标定位算法 13

3.2.1 粗定位阶段 13

3.2.2 细定位阶段 15

3.3 计算复杂度分析 18

3.4 本章小结 19

第四章 仿真结果与分析 20

4.1 仿真设置 20

4.2 定位性能分析 20

4.2.1目标数量的影响 20

4.2.2信噪比的影响 23

4.2.3观测次数的影响 25

4.3 本章小结 26

第五章 总结与展望 27

5.1 总结 27

5.2 展望 27

参考文献 29

致 谢 31

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