【作者】 李娟；

【导师】 王珂；

【作者基本信息】 吉林大学 ， 通信与信息系统， 2009， 博士

【摘要】 节点定位技术是无线传感器网络的关键性技术,无论对于无线传感器网络的基本理论研究还是应用研究都有着重要意义。路由协议解决的是数据传输的问题。同样也是保证无线传感器网络性能的核心技术之一。本文对无线传感器网络节点自身定位和路由协议等问题做出了探讨,提出了有关二维和三维节点定位的算法,并研究了传感器网络的路由协议,在路由协议的节省能量方面做出了尝试。本文的创新性工作主要有三个方面。第一,提出了一种基于锚圆内交点质心定位算法,该算法利用未知节点无线通信范围内的三个锚节点,由三个锚节点的锚圆内交点构成三角形,即未知节点所在的三角形区域,将三角形的质心作为未知节点的位置估计。该算法无需测量距离,仅根据网络的连通度,算法计算量小,节点通信开销小,仿真显示,当网络连通度高时,算法精度优于质心算法和Bounding box算法;第二,在基于锚圆内交点质心定位算法的基础上,提出利用RSSI值作为三个锚圆内交点权值的加权质心算法,进一步提高了定位精度;第三,提出了一种三维节点定位算法Bounding cube,该算法将节点的无线射程近似为一个正方体,通过将未知节点周围的信标节点的无线射程确定出未知节点所在的立方体,以立方体的质心作为未知节点的估计位置。该算法计算简单,通信量小,适合于能量有限的三维传感器网络。此外,本文对基于RSSI的最小二乘定位算法、基于TDOA的最小二乘算法和Chan算法做了深入的研究。最后,对无线传感器网络基于LEACH的路由协议在节省能量方面做出了改进。更多还原

【Abstract】 Being the most important and most basic skill for information access, Sensor Technology has grown gradually from simplification in the past to integration, miniaturization and network now. Moreover, as the Time’s footstep of“Internet of Things”is closer and closer, the sensor network will have a wider range of application prospects. As sensor networks have unique nature of short-range wireless communications, low-cost, self-organization, rapid deployment, multi-hop routing, dynamic topology, fault tolerance, data-centric and application-oriented, and so on, that is different from other networks, it does not follow the old network approach. Currently the wireless sensor networks are just beginning to develop, and its technology, applications are still far from mature. In this circumstances that the development urgently required in the era, this article has made an exploration on the wireless sensor networks node location and routing protocols, such issues presented some two-dimensional and three-dimensional node localization algorithms, and had an attempt on energy saving about routing protocols.This dissertation mainly includes the following aspects:1. A centroid localization algorithm based on intersection of anchor circleRange-based localization schemes are sometimes not feasible due to hardware cost and resource restriction of sensor nodes. This paper studies the geometric relationships and communication constraints among unknown node and anchor nodes, and presents a weighted centroid localization algorithm based on intersection of anchor circle. When there are three anchor nodes in the communications range of the unknown node, the unknown node must be in the triangle of constituting by the intersection of the anchors circle. This paper assumes the location estimation of unknown node is the triangle centroid.2. Tow RSSI-based positioning algorithmsAfter studying the signal propagation model, using the maximum likelihood method, the scheme of optimizing the RSSI value received by node is proposed, and proving the RSSI maximum likelihood estimates are unbiased estimates and the variance is the minimum of the Cramer - Rao inequality. Analyzing many methods about getting the distance from receiving node to the launch node using received RSSI value, studying and describing the advantages and disadvantages of different methods. Finally, after three or more distances from beacon to the unknown node were known, using the least-squares method and calculating the coordinates of unknown nodes. Simulation results show that when the known node is only 6% and 9%, the location results are not good; when the known node is more than 16%, the communication radius is greater than 30m, the coverage can reach 100%. As the beacon node density increases, the relative positioning error was tend to reduce, but it is not very significant; and as the communication radius increases, the relative positioning error will be reduced also. Regardless of how much communication radius value is, the variance increase with the outside interference, the relative positioning errors increased, whenσ2≤9, the relative error of the location algorithm is less than 0.3, which can basically meet the position requirements.For increasing the positioning accuracy, the improved scheme use RSSI as weight function and let the weighted centroid of the triangle be the location estimation of unknown node. This range-free algorithm is based exclusively on connectivity of sensor networks. The communication and computational loads are small. Simulation results show that the relative localization error is 22.7 percent when 100 sensor nodes are randomly deployed in 100m*100m scenarios with 30m communication range and the anchor density is 16 percent.3. The study of positioning algorithm based on TDOAIn this part, we introduced the available estimating method of the time difference and the time delay, Analyzing the advantages and disadvantages of each method and in different circumstances which method should be used.Positioning algorithm uses the least-squares method and the Chan algorithms. Using the least-squares method and the Chan algorithms we calculated the value of the unknown node coordinates many times, we found that the results of some positioning will deviate far from the true value , making the results of the current positioning is invalid. To improve positioning accuracy, the centroid algorithm is proposed after using the least squares method and Chan algorithm, it reducing the positioning error between the true value and the results of positioning.4. A three-dimensional positioning algorithm based on the Bounding cubeDespite the fact that sensor networks could often be deployed over three-dimensional (3D) terrains, most approaches on sensor localizations are designed and evaluated considering only two-dimensional (2D) applications. According to the shortage of energy in wireless sensor networks, we present a localization scheme Bounding Cube for 3D. Both principles and practice were discussed, simulation were done. The simulation results show that, when 400 nodes are randomly deployed in 100m×100m×100m the three-dimensional terrains, the known node density is greater than 20% and the communication radius r is 30m, 40m and 50m, the relative positioning error will be less than 40%. When the known nodes density is greater than 20% and communication radius is greater than 30m, the proportion of a targeted is 100%. The outstanding characteristic of this algorithm are the method is simple and the calculation is small.5. Research and Improvement of routing protocol based on LEACHConsidering limited energy characteristic of wireless sensor networks(WSN),this paper propose an improved routing LEACH cluster head selection algorithm based on distributed stochastic cluster-head selection LEACH routing protocol. This improved algorithm takes full account of the residual energy of node and the position information of the cluster-head, using the knowledge of probability theory and mathematical statistics, in a specific region calculating the cluster-head number that making energy-consumption over the whole network is the less. Through the compute simulation, the new algorithm was compared with LEACH Routing Protocol. Using the LEACH algorithm nodes begin dying at 351 rounds, and using the improved algorithm nodes begin dying until 703 rounds. The LEACH algorithm consumes 13J through 351 rounds, the improved algorithm only consumes 5.8J and energy-consumption is lower 53% than the LEACH algorithm in this period. It is obviously that the improved algorithm saves the node energy and prolongs the life-cycle of the entire network.There are three innovative works in this dissertation. Firstly, this paper presents a centroid location algorithm based on the intersection of anchor circle. Using the intersection of three anchor circles making a triangle, and the three anchors are within wireless communication range of the unknown node. Then the unknown node should be in this triangular area, and the triangle centroid will be the location estimation of unknown nodes. Secondly, basing on the centroid location algorithm of the intersection of anchor circle, we proposed a weighted centroid algorithm, that uses the RSSI value as weighting factor. This algorithm further improves the positioning accuracy. Thirdly, we proposed a three-dimensional positioning algorithm Bounding cube, this algorithm approximate the node’s wireless range as a cube. Finding the cube where an unknown nodes in by the beacon nodes around an unknown nodes, simply using the center of the cube as the estimated location of unknown nodes. This algorithm is simple and the traffic is small, just adapting to a limited energy three-dimensional sensor networks.更多还原