半分布式TOA-DOA多点协同定位算法研究与仿真

发布时间：2019-03-19 15:37

【摘要】：随着无线网络技术的普及和发展,无线局域网的定位服务引起越来越多的关注,在车辆导航与避险、消防救灾、海洋救援、无人机导航与通信等领域显示出了巨大活力,开拓并推动了无线局域网定位技术的发展应用。无线局域网定位技术也引起了各国和各研究机构的重视,其中移动Ad hoc网络(Mobile Ad hoc Network,简称MANET)是其中研究的热点。目前对MANET网络的研究,大多基于GPS定位来获取网络节点的位置。本文研究在不使用GPS和其它外部定位系统情况下,MANET在视距环境下的定位算法以及非视距环境下的定位算法两部分。本论文结合MANET移动性和无中心基站的特点,本文将介绍一种视距二维环境下的定位算法——半分布式TOA-DOA多点协同定位算法。该算法是一种多数据融合的TOA-DOA定位算法,基于单基站获得的位置信息,以数据融合思想为核心,利用多个基站点对同一目标测得的位置信息进行数据融合。算法包括选择参考点、定位基站点、定位目标点3个步骤。基于以上的基本理论算法,本文将对参考点选择、坐标系同向以及利用中间节点定位等问题进行了讨论和研究。卡尔曼滤波器、扩展卡尔曼滤波器以及联邦滤波器对定位算法进行优化,以提高算法的性能和定位的精度。本论文将利用RSS参数与现有数据融合技术进一步运用到定位中,构造多层数据融合模型,提出LRRF算法以消除或减小非视距误差,改善定位稳定性和精确度,并证明该方法的有效性。本论文对TOA-DOA定位算法进行了性能仿真,同传统的TOA定位算法进行了比较,稳定性更好。联邦滤波器对TOA-DOA定位算法结果的优化,使性能有了提高,比单一卡尔曼滤波和扩展卡尔曼滤波,有更好的稳定性和可靠性。非视距下的冗余RSS数据融合,能有效减低非视距误差,提高精度。结果显示TOA-DOA定位算法,可以运用到中小规模MANET网络环境。本文研究对无线自组网的定位算法研究有一定的参考意义。
[Abstract]:With the popularization and development of the wireless network technology, the positioning service of the wireless local area network has attracted more and more attention, and has shown great vitality in the fields of vehicle navigation and hedging, fire disaster relief, marine rescue, unmanned aerial vehicle navigation and communication, And the development and application of the wireless local area network positioning technology are developed and promoted. The wireless LAN positioning technology has also attracted the attention of the countries and the research institutions, among which the Mobile Ad hoc Network (MANET) is the hot spot of the research. At present, the research of the MANET network is based on the GPS positioning to get the position of the network node. In this paper, under the condition of not using GPS and other external positioning systems, the positioning algorithm of MANET in the sight-of-sight environment and the positioning algorithm under the non-sight-of-sight environment are studied. In this paper, combined with the characteristics of MANET mobility and no-center base station, this paper introduces a positioning algorithm, semi-distributed TOA-DOA multi-point cooperative location algorithm, under the sight distance two-dimensional environment. The algorithm is a multi-data fusion TOA-DOA location algorithm, based on the position information obtained from a single base station, the data fusion is used as the core, and the position information measured by the same target is fused by using a plurality of base station points. The algorithm comprises the steps of selecting a reference point, positioning a base station point, and positioning a target point. Based on the above basic theory, this paper discusses and studies the selection of the reference point, the co-rotation of the coordinate system and the use of the intermediate node. The Kalman filter, the extended Kalman filter and the federated filter optimize the positioning algorithm to improve the performance and accuracy of the algorithm. The paper will use the RSS parameters and the existing data fusion technology to further apply to the positioning, construct the multi-layer data fusion model, propose the LRRF algorithm to eliminate or reduce the non-line-of-sight error, improve the positioning stability and accuracy, and prove the effectiveness of the method. In this paper, the TOA-DOA location algorithm is simulated, and compared with the traditional TOA positioning algorithm, the stability is better. The results of the TOA-DOA location algorithm are optimized by the federated filter, and the performance is improved, which is better than the single Kalman filter and the extended Kalman filter, and has better stability and reliability. The non-sight-of-sight redundant RSS data fusion can effectively reduce the non-line-of-sight error and improve the accuracy. The results show that the TOA-DOA location algorithm can be applied to the small-scale MANET network environment. In this paper, the research on the positioning algorithm of wireless ad hoc network has some reference significance.
【学位授予单位】：电子科技大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：TN925.93

【相似文献】