各向异性无线传感器网络节点定位算法的研究

发布时间：2019-03-04 18:24

【摘要】：无线传感器网络大多应用于复杂的环境中,甚至是远离人类生活区的恶劣环境下,所以节点的分布多经过飞行器抛撒的方式进行随机分布,这使得定位成为一个技术难点。大部分的定位算法都假设网络拓扑是各向同性的,然而由于节点抛撒的随机性、地理形状的复杂多变、分布几何形状不规则、节点密度不均匀等原因,实际的网络拓扑结构往往呈现出各向异性的特点。这就使得传统的定位算法性能恶化,定位精度下降,网络可定位节点覆盖率降低。因此,研究适用于各向异性无线传感器网络并具有良好定位精度的定位算法具有重要意义。本文在对各向异性无线传感器网络研究分析的基础上,提出了一种基于跳距和测距的各向异性网络节点定位算法HRL (Hops and Range based Localization algorithm for anisotropic networks)。HRL算法设计了基于各向异性的跳距模型和测距模型。在跳距模型中,针对传统跳距算法计算平均跳距误差大的问题,提出了HRL跳数阈值限定以及HRL跳距算法设计。在测距模型中,针对各向异性网络中传输信号的各向异性特点,本文设计了不规则信号的传输模型。提出了基于中值数绝对偏差的加权滤波算法,对测距信号进行优化处理。在距离计算中提出了信号模型参数识别算法,使得节点根据周围环境确定自己的信号模型参数值。为提高定位精度,提出了锚节点选择策略。在锚节点选择中提出了共线度的计算方法,对共线的锚节点进行排除,对三边测量法中三个圆相交于一个区域的问题设计了解决方案。最后,对本文提出的HRL算法设计了详细的算法流程。本文对HRL算法进行了仿真实现,并对实验结果进行了详细分析,仿真结果验证了HRL算法的有效性。
[Abstract]:Wireless sensor networks (WSNs) are mostly used in complex environments, even in harsh environments far away from human living areas, so the distribution of nodes is distributed randomly by means of aerial vehicle scattering, which makes positioning a difficult technical problem. (2) Wireless sensor networks (WSNs) are widely used in wireless sensor networks (WSNs). Most of the localization algorithms assume that the network topology is isotropic. However, due to the randomness of node scattering, the complexity of geographical shape, the irregular geometric shape of distribution, the uneven density of nodes, and so on. The actual network topology often presents the characteristics of anisotropy. This makes the performance of the traditional localization algorithm worse, the positioning accuracy decreases, and the coverage of the network locatable nodes decreases. Therefore, it is of great significance to study the localization algorithm which is suitable for anisotropic wireless sensor networks and has good positioning accuracy. In this paper, based on the research and analysis of anisotropic wireless sensor networks, In this paper, an anisotropic network node location algorithm based on jump distance and ranging is proposed. The HRL (Hops and Range based Localization algorithm for anisotropic networks) algorithm designs the distance hopping model and ranging model based on anisotropy. In the jump model, aiming at the problem of the large average jump error of the traditional distance algorithm, the threshold limit of the HRL hop number and the design of the HRL hop distance algorithm are proposed. In the ranging model, aiming at the anisotropic characteristics of the transmitted signal in the anisotropic network, the transmission model of the irregular signal is designed in this paper. A weighted filtering algorithm based on the absolute deviation of median number is proposed to optimize the ranging signal. In the distance calculation, a signal model parameter identification algorithm is proposed, which enables the nodes to determine their own signal model parameter values according to the surrounding environment. In order to improve the positioning accuracy, an anchor node selection strategy is proposed. In the selection of anchor nodes, the calculation method of collinear degree is put forward, and the solution to the problem of three circles intersecting in one area in the trilateral measurement method is designed to exclude the collinear anchor nodes. Finally, a detailed algorithm flow is designed for the HRL algorithm proposed in this paper. In this paper, the HRL algorithm is simulated, and the experimental results are analyzed in detail. The simulation results verify the effectiveness of the HRL algorithm.
【学位授予单位】：东北大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TN929.5;TP212.9

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