无线传感器网络非测距和光带辅助定位研究
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摘要
随着嵌入式系统、微电机系统、处理器、存储技术以及无线电技术的飞跃发展孕育了无线传感器网络这项新兴技术。无线传感器网络是一种由成百上千的带有传感元件、信息处理元件和通信元件的传感节点组成的自组织网络。广泛应用于森林火灾、洪水监测、环境保护、工业、农业、军事和抢险等领域。
低成本、低功耗、大规模无线传感器网络提供了一种全新的信息获取和信息处理方式,扩展了现代网络的功能和人类认识世界的能力,成为当前一个热点研究领域并被认为是能对21世纪产生巨大影响力的技术之一。也必将成为物联网核心技术之一。
作为无线传感器网络支撑技术的定位技术一直是研究的热点问题。在无线传感网络应用中,感知数据必须带有位置信息才有意义,如果缺少位置信息,则在环境监测、森林火灾监控等领域则无法及时有效的处理。低成本、低功耗、低运算量和高定位精度的无线传感器网络定位算法是当前研究中需进一步研究的热点问题之一
论文首先从非测距分布式定位方法为出发点,针对质心定位算法受锚节点分布不均匀而定位精度降低的情况,提出了一种改进的质心算法(CSA)。定位精度相对多跳质心算法得到10%提高。接着根据未知节点必定处于周围—跳锚节点通信半径范围内重叠区域中的基本事实,提出了基于非测距的分布式intersection-grid-sector (IGS)定位算法。IGS算法以锚节点通信半径的10%作为网格大小来获取重叠区域,并把重叠区域的每个网格坐标求质心作为未知节点估计坐标,仿真结果表明比Bonding Box精度明显提高,比经典质心提高近20%。RSSI-IGS在IGS基础上引入RSSI测得最近一跳锚节点与未知节点间的距离作为参考距离信息,从重叠区域坐标中找到最接近未知节点的值求质心获得未知节点估计值。仿真结果表明,RSSI-IGS相对IGS精度有很大提高。然后,从目标跟踪的逆向方法出发,提出了一种采用可移动节点在未知节点布设区域上空进行行列扫描,同时发射相应标识信号给未知节点的定位算法——LA-SCAN。算法具有节点定位的通信能耗低、计算公式简单等优点。最后,结合网格、光带和移动定位策略分析、设计、实现了称为光扫描定位(BLS)的方案。BLS通过带有光带装置的移动定位助理(LA)对未知节点布设区按一定间隔光照扫描和发射相应的标识号,未知节点只需要扫描间距、布设区起点位置和接收到的标识号即可计算出估计坐标。其精度可达到十几厘米(sub-meter)。并且给出了两类4种不同的定位模式。理论分析、比较与实验表明BLS有效可行。
With the rapid development of embedded systems, micro-electromechanical systems, processors, storage technology and radio technology, wireless sensor networks (WSN) emerges. WSN consist of numerous small computers equipped with sensors to detect events, information processing components and communications components and it is self-organizing network. Wireless sensor networks extend our capability to explore, monitor, and control the physical world in forest fires and flood monitoring, environmental protection, industry, agriculture, military, and rescue and other fields.
Low-cost, low power, large-scale wireless sensor networks provides a new way of information acquisition and processing, extends the capabilities of modern networks and the ability of the human understanding of the world. It has become a hot research field and researchers agree WSN can have enormous influence in the 21st century. At the same time, it will certainly become one of the core technologies of Internet of Things (IOT).
In WSN, the localization information is an important criterion and localization technology is a hotspot research issue also. Meanwhile, in various applications of wireless sensor networks, the sensory data with location information must be meaningful. If the lack of location information, the tasks such as environmental monitoring, forest fire monitoring and other works can not be timely and effective treatment. Low cost, low power, low computation and high accuracy localization algorithms for wireless sensor networks will be further researched in future.
In this paper, first, Centroid algorithm is a classical range-free localization algorithm. After receiving the anchor nodes, a node estimates its location using the centroid formula. But the set of the asymmetrical anchor nodes distributed around the unknown node may incur large error, and will jeopardize the localization precision. In order to solve the problem, we propose a Centroid algorithm with selective anchor node localization algorithm (CSA) for WSN in this paper. The triangle centroid and polygon centroid were used and the method of selecting nearest anchor node was adopted. The experiment results illustrate that our algorithm is valid and effective and increases 10% compared with classic centroid localization precison. Second, we introduce the novel grid-based distributed localization algorithm for wireless sensor networks, which we call intersection-grid-sector (IGS) for range-free localization. The IGS can obtain intersection grid coordinates through grid unit of one hop area intersection of every anchor around unknown node, which be divided into grid unit based on 10% of anchor node radius. Then, IGS calculates the center of gravity (COG) of the intersection grid coordinates in which a node resides to determine its estimated position. Simulation shows that IGS algorithm estimation error comparing with Bonding Box is significantly improved and comparing classical Centroid ascends about 20%. The RSSI-IGS algorithm adopts RSSI (Received Signal Strength Indicator) to get the distance to the nearest one hop anchor of unknown node. Subsequently, the set of coordinates selected from intersection grid coordinates obtained by the IGS in virtue of the distance information is constructed. Finally, the RSSI-IGS calculates COG of the set of coordinates as estimation value. Experiment presents that the RSSI-IGS localization increases in comparison to IGS. The third, Using the dual of target tracking, We utilize a moving location-assistant(LA) to scan location-unaware sensors deployed area by row(column), construct grids and LA only send ID, at the same time, location-unaware sensors receive the first arrival ID merely. We call our proposed system LA-SCAN. LA-SCAN has some significant benefits compared to other methods applicable:(1) LA-SCAN saves communication energy (2) compared with Landscape or Centroid, unknown nodes can calculate themselves positions only by means of movement gap, the start position of deployed area and receiving ID. Extensive simulations and analysis show that LA-SCAN is a high-performance sensor positioning algorithm. Finally, we describe, design, implement, and evaluate a novel localization scheme called band of light scan localization (BLS) by combining grid and light (laser) with mobile localization policy for wireless sensor networks. The scheme utilizes a moving location assistant (LA) with a band of light, through which the deployed area is scanned. The LA sends IDs to unknown nodes to obtain the locations of sensor nodes. BLS reaches a sub-meter localization error. Four modes are analyzed, simulated, and implemented, and four positioning mode features in BLS are compared. The theory of analysis, simulation, and experiment demonstrate the effectiveness and advantages of BLS.
低成本、低功耗、大规模无线传感器网络提供了一种全新的信息获取和信息处理方式,扩展了现代网络的功能和人类认识世界的能力,成为当前一个热点研究领域并被认为是能对21世纪产生巨大影响力的技术之一。也必将成为物联网核心技术之一。
作为无线传感器网络支撑技术的定位技术一直是研究的热点问题。在无线传感网络应用中,感知数据必须带有位置信息才有意义,如果缺少位置信息,则在环境监测、森林火灾监控等领域则无法及时有效的处理。低成本、低功耗、低运算量和高定位精度的无线传感器网络定位算法是当前研究中需进一步研究的热点问题之一
论文首先从非测距分布式定位方法为出发点,针对质心定位算法受锚节点分布不均匀而定位精度降低的情况,提出了一种改进的质心算法(CSA)。定位精度相对多跳质心算法得到10%提高。接着根据未知节点必定处于周围—跳锚节点通信半径范围内重叠区域中的基本事实,提出了基于非测距的分布式intersection-grid-sector (IGS)定位算法。IGS算法以锚节点通信半径的10%作为网格大小来获取重叠区域,并把重叠区域的每个网格坐标求质心作为未知节点估计坐标,仿真结果表明比Bonding Box精度明显提高,比经典质心提高近20%。RSSI-IGS在IGS基础上引入RSSI测得最近一跳锚节点与未知节点间的距离作为参考距离信息,从重叠区域坐标中找到最接近未知节点的值求质心获得未知节点估计值。仿真结果表明,RSSI-IGS相对IGS精度有很大提高。然后,从目标跟踪的逆向方法出发,提出了一种采用可移动节点在未知节点布设区域上空进行行列扫描,同时发射相应标识信号给未知节点的定位算法——LA-SCAN。算法具有节点定位的通信能耗低、计算公式简单等优点。最后,结合网格、光带和移动定位策略分析、设计、实现了称为光扫描定位(BLS)的方案。BLS通过带有光带装置的移动定位助理(LA)对未知节点布设区按一定间隔光照扫描和发射相应的标识号,未知节点只需要扫描间距、布设区起点位置和接收到的标识号即可计算出估计坐标。其精度可达到十几厘米(sub-meter)。并且给出了两类4种不同的定位模式。理论分析、比较与实验表明BLS有效可行。
With the rapid development of embedded systems, micro-electromechanical systems, processors, storage technology and radio technology, wireless sensor networks (WSN) emerges. WSN consist of numerous small computers equipped with sensors to detect events, information processing components and communications components and it is self-organizing network. Wireless sensor networks extend our capability to explore, monitor, and control the physical world in forest fires and flood monitoring, environmental protection, industry, agriculture, military, and rescue and other fields.
Low-cost, low power, large-scale wireless sensor networks provides a new way of information acquisition and processing, extends the capabilities of modern networks and the ability of the human understanding of the world. It has become a hot research field and researchers agree WSN can have enormous influence in the 21st century. At the same time, it will certainly become one of the core technologies of Internet of Things (IOT).
In WSN, the localization information is an important criterion and localization technology is a hotspot research issue also. Meanwhile, in various applications of wireless sensor networks, the sensory data with location information must be meaningful. If the lack of location information, the tasks such as environmental monitoring, forest fire monitoring and other works can not be timely and effective treatment. Low cost, low power, low computation and high accuracy localization algorithms for wireless sensor networks will be further researched in future.
In this paper, first, Centroid algorithm is a classical range-free localization algorithm. After receiving the anchor nodes, a node estimates its location using the centroid formula. But the set of the asymmetrical anchor nodes distributed around the unknown node may incur large error, and will jeopardize the localization precision. In order to solve the problem, we propose a Centroid algorithm with selective anchor node localization algorithm (CSA) for WSN in this paper. The triangle centroid and polygon centroid were used and the method of selecting nearest anchor node was adopted. The experiment results illustrate that our algorithm is valid and effective and increases 10% compared with classic centroid localization precison. Second, we introduce the novel grid-based distributed localization algorithm for wireless sensor networks, which we call intersection-grid-sector (IGS) for range-free localization. The IGS can obtain intersection grid coordinates through grid unit of one hop area intersection of every anchor around unknown node, which be divided into grid unit based on 10% of anchor node radius. Then, IGS calculates the center of gravity (COG) of the intersection grid coordinates in which a node resides to determine its estimated position. Simulation shows that IGS algorithm estimation error comparing with Bonding Box is significantly improved and comparing classical Centroid ascends about 20%. The RSSI-IGS algorithm adopts RSSI (Received Signal Strength Indicator) to get the distance to the nearest one hop anchor of unknown node. Subsequently, the set of coordinates selected from intersection grid coordinates obtained by the IGS in virtue of the distance information is constructed. Finally, the RSSI-IGS calculates COG of the set of coordinates as estimation value. Experiment presents that the RSSI-IGS localization increases in comparison to IGS. The third, Using the dual of target tracking, We utilize a moving location-assistant(LA) to scan location-unaware sensors deployed area by row(column), construct grids and LA only send ID, at the same time, location-unaware sensors receive the first arrival ID merely. We call our proposed system LA-SCAN. LA-SCAN has some significant benefits compared to other methods applicable:(1) LA-SCAN saves communication energy (2) compared with Landscape or Centroid, unknown nodes can calculate themselves positions only by means of movement gap, the start position of deployed area and receiving ID. Extensive simulations and analysis show that LA-SCAN is a high-performance sensor positioning algorithm. Finally, we describe, design, implement, and evaluate a novel localization scheme called band of light scan localization (BLS) by combining grid and light (laser) with mobile localization policy for wireless sensor networks. The scheme utilizes a moving location assistant (LA) with a band of light, through which the deployed area is scanned. The LA sends IDs to unknown nodes to obtain the locations of sensor nodes. BLS reaches a sub-meter localization error. Four modes are analyzed, simulated, and implemented, and four positioning mode features in BLS are compared. The theory of analysis, simulation, and experiment demonstrate the effectiveness and advantages of BLS.
引文
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