传感器网络定位算法及相关技术研究
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摘要
近年来,微机电系统(MEMS)技术、通信技术和计算技术的发展,使得开发具有短距离无线通信能力的低成本、自组织、多功能传感器节点成为可能。这些大量的微节点即可组成分布式协同工作的传感器网络。传感器网络的快速布置、多跳路由、动态拓扑、容错、以数据为中心和面向应用等独特性,使其成为虚拟世界与物理世界互动的桥梁。
在传感器网络中,节点以自组织方式获得自身位置信息的过程称为节点定位。在诸如环境监测、智能交通和目标跟踪等众多应用场合下,传感器网络需要节点定位技术支持。但是,传感器网络固有的资源受限、能量受限等问题使节点定位变得十分困难。现有定位算法的主要缺点是:定位精度不高、定位引起的额外通信开销偏高、对测距噪声鲁棒性不好、节点能量消耗大等。
依托“基于网络的智能传感器技术理论研究”项目(广东海洋大学自然科学基金,项目编号:z0512142)及国家自然科学基金项目(项目批准号:50672015),本论文以传感器网络节点定位方法为研究对象,以提高定位精度和对测距噪声的鲁棒性、降低额外通信开销、降低节点能耗为目的,重点研究了节点的四种定位算法及其相关技术。四种定位算法包括:精确的二维节点定位算法(ACT)、具有低计算复杂性的二维节点定位算法改进(IACT)、具有通用性的三维节点定位算法(ACQ)和可明显降低节点成本、体积和能量消耗的加权最小二乘估计定位算法(WLS)。为了提高传感器网络节点定位信息传输可靠性、保证能量利用高效性,论文给出了基于主动队列管理、开环反向拥塞信息传播机制和优先权源节点速率调节机制的汇聚节点拥塞控制策略。由于能量问题一直是困扰传感器网络广泛应用的难题,所以论文最后初步探讨了基于MEMS技术的节点能量收集方法。
本论文主要内容如下:
第3章提出基于模型预测控制理论、用于汇聚节点队列长度控制的控制器,该控制器使用不同的延迟环节Pade近似方法,以增加队列稳定性、缩短节点响应时间。而且,针对传感器网络的特点,给出节点适时检测信道负载状况、开环反向广播拥塞信息和优先权源节点速率调节机制,目的是缩短数据包节点延时,稳定节点队列长度,提高链路利用率,减少数据包重传次数,提高定位及其它信息传输可靠性,降低能量消耗。
第4章提出一种分布式节点定位算法——循环三边组合测量法(ACT)。该算法只需利用少量信标节点位置信息和未知节点与信标节点间测距,即可估计未知节点坐标。为了减小节点定位误差、降低额外通信开销、提高
Recent advances in micro-electro-mechanism system (MEMS), communications and computing technology have enabled the development of low-cost, self-organized, multi-functional, wireless sensor nodes with short communication range. These micro nodes leverage the idea of sensor networks based on distributed collaborative effort of a very large number of nodes. Compared with traditional networks, sensor networks pose unique characteristics, such as rapid deployment, source constraint, multi-hop, dynamic topology, fault tolerance, data-centric and application-based. So, sensor networks have the potential to bridge the gap between the virtual world and the physical world.
The process of determining the physical coordinates of sensor nodes, which is self-organizing, is called localization. Location information of nodes is especially critical for some applications of sensor networks. However, the sensor networks are typically resource–constrained and energy-constrained. These disadvantages make it difficult to locate the sensor nodes. Supported by the“Research on Network-Based Intelligent Sensor Technology”(Nature Science Foundation of Guangdong Ocean University, No: z0512142) and the“National Natural Science Foundation (No: 50672015), the dissertation explores several localization methods and related technologies for sensor nodes to improve localization accuracy and robustness to range noise, decrease additional communication overhead, lower energy consumption. Four localization algorithms include: Alternating Combination Trilateration (ACT) with accuracy for 2D nodes, Improved Alternating Combination Trilateration (IACT) with low computational complexity, Universal Alternating Combination Quadrilateration (ACQ) for 3D and 2D, and the weighted least squares (WLS) estimation localization with which the sensor nodes can be low-cost, compact and energy efficient. For the sink node, the dissertation presents a new congestion control method using active queue management, open-loop reverse transmission mechanism for congestion information and transmission rate adjustment of source node based on priority. Energy problems have hindered wide application of sensor networks, so some new energy collection methods MEMS-based for sensor nodes are discussed. The main contents of the dissertation are as follows:
Based on the theoretical model predictive control theory, we present an active
在传感器网络中,节点以自组织方式获得自身位置信息的过程称为节点定位。在诸如环境监测、智能交通和目标跟踪等众多应用场合下,传感器网络需要节点定位技术支持。但是,传感器网络固有的资源受限、能量受限等问题使节点定位变得十分困难。现有定位算法的主要缺点是:定位精度不高、定位引起的额外通信开销偏高、对测距噪声鲁棒性不好、节点能量消耗大等。
依托“基于网络的智能传感器技术理论研究”项目(广东海洋大学自然科学基金,项目编号:z0512142)及国家自然科学基金项目(项目批准号:50672015),本论文以传感器网络节点定位方法为研究对象,以提高定位精度和对测距噪声的鲁棒性、降低额外通信开销、降低节点能耗为目的,重点研究了节点的四种定位算法及其相关技术。四种定位算法包括:精确的二维节点定位算法(ACT)、具有低计算复杂性的二维节点定位算法改进(IACT)、具有通用性的三维节点定位算法(ACQ)和可明显降低节点成本、体积和能量消耗的加权最小二乘估计定位算法(WLS)。为了提高传感器网络节点定位信息传输可靠性、保证能量利用高效性,论文给出了基于主动队列管理、开环反向拥塞信息传播机制和优先权源节点速率调节机制的汇聚节点拥塞控制策略。由于能量问题一直是困扰传感器网络广泛应用的难题,所以论文最后初步探讨了基于MEMS技术的节点能量收集方法。
本论文主要内容如下:
第3章提出基于模型预测控制理论、用于汇聚节点队列长度控制的控制器,该控制器使用不同的延迟环节Pade近似方法,以增加队列稳定性、缩短节点响应时间。而且,针对传感器网络的特点,给出节点适时检测信道负载状况、开环反向广播拥塞信息和优先权源节点速率调节机制,目的是缩短数据包节点延时,稳定节点队列长度,提高链路利用率,减少数据包重传次数,提高定位及其它信息传输可靠性,降低能量消耗。
第4章提出一种分布式节点定位算法——循环三边组合测量法(ACT)。该算法只需利用少量信标节点位置信息和未知节点与信标节点间测距,即可估计未知节点坐标。为了减小节点定位误差、降低额外通信开销、提高
Recent advances in micro-electro-mechanism system (MEMS), communications and computing technology have enabled the development of low-cost, self-organized, multi-functional, wireless sensor nodes with short communication range. These micro nodes leverage the idea of sensor networks based on distributed collaborative effort of a very large number of nodes. Compared with traditional networks, sensor networks pose unique characteristics, such as rapid deployment, source constraint, multi-hop, dynamic topology, fault tolerance, data-centric and application-based. So, sensor networks have the potential to bridge the gap between the virtual world and the physical world.
The process of determining the physical coordinates of sensor nodes, which is self-organizing, is called localization. Location information of nodes is especially critical for some applications of sensor networks. However, the sensor networks are typically resource–constrained and energy-constrained. These disadvantages make it difficult to locate the sensor nodes. Supported by the“Research on Network-Based Intelligent Sensor Technology”(Nature Science Foundation of Guangdong Ocean University, No: z0512142) and the“National Natural Science Foundation (No: 50672015), the dissertation explores several localization methods and related technologies for sensor nodes to improve localization accuracy and robustness to range noise, decrease additional communication overhead, lower energy consumption. Four localization algorithms include: Alternating Combination Trilateration (ACT) with accuracy for 2D nodes, Improved Alternating Combination Trilateration (IACT) with low computational complexity, Universal Alternating Combination Quadrilateration (ACQ) for 3D and 2D, and the weighted least squares (WLS) estimation localization with which the sensor nodes can be low-cost, compact and energy efficient. For the sink node, the dissertation presents a new congestion control method using active queue management, open-loop reverse transmission mechanism for congestion information and transmission rate adjustment of source node based on priority. Energy problems have hindered wide application of sensor networks, so some new energy collection methods MEMS-based for sensor nodes are discussed. The main contents of the dissertation are as follows:
Based on the theoretical model predictive control theory, we present an active
引文
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