基于虛擬力的WSAN定位算法的研究
發(fā)布時間：2018-12-24 08:32
【摘要】：無線傳感器與執(zhí)行器網絡(Wireless Sensor and Actor Network,WSAN)是在無線傳感器網絡(Wireless Sensor Network,WSN)的基礎上衍生而來,通常由若干傳感器節(jié)點和執(zhí)行器節(jié)點組成。執(zhí)行器節(jié)點具有較強的處理能力、較高的能量,能夠根據傳感器節(jié)點采集的信息進行分析、決策并采取相應的措施。在某種意義上,WSAN是能夠改變物理世界的新型網絡。因此,WSAN對于重要的定位技術也提出了更高的要求。另外現有的WSN定位算法不能直接移植到WSAN中使用,故本文針對傳統WSN定位算法的缺陷并結合WSAN的定位需求,對WSAN定位算法進行了研究。具體研究內容如下1.總結了國內外關于WSN/WSAN定位算法的研究進展并分析了現有WSN定位算法不適用于WSAN的原因。以WSN為基礎,從體系結構、節(jié)點組成、網絡特征等方面對WSAN進行了全面介紹。同時列舉了WSAN定位算法中常見的6種分類方式,并對其中的代表算法進行了詳細介紹。2.提出了一種基于正方形區(qū)域的移動非測距定位算法(Mobile Range-free Localization Algorithm based on Square Area,MRFS)。算法利用移動的執(zhí)行器節(jié)點代替WSN中的錨節(jié)點進行定位,首先通過執(zhí)行器節(jié)點正方形的布局確定未知節(jié)點所在區(qū)域,然后通過迭代不斷縮小該區(qū)域,最后計算該區(qū)域質心作為未知節(jié)點的坐標。利用移動的執(zhí)行器節(jié)點能有效節(jié)省網絡部署成本,另外與測距技術相比,非測距的定位方式大大降低了硬件成本。仿真實驗表明,算法能夠取得不錯的定位效果。為避免執(zhí)行器節(jié)點分布局部密集或稀疏,使空閑執(zhí)行器節(jié)點的分布均勻合理,在定位的同時引入虛擬力模型,提出了一種基于虛擬力的MRFS非測距定位算法(MRFS Localization Algorithm based on Virtual Force,MRFSVF)。仿真實驗證明,虛擬力算法的引入能有效改善執(zhí)行器節(jié)點分布不均的情況,從而優(yōu)化其覆蓋面積,并且減少了定位誤差及時間。3.測距定位方面,傳統的基于信號傳輸時間(Time of Arrival,TOA)的定位算法通過計算信號的傳輸時間來測量節(jié)點間距離,將TOA算法與虛擬力模型相結合,促使執(zhí)行器節(jié)點在虛擬力作用下不斷移動,有利于執(zhí)行器節(jié)點向請求定位的傳感器節(jié)點靠近,從而提高定位成功率。仿真實驗驗證了算法的性能。4.針對各定位算法的特點及適用場合,介紹了各算法的應用。
[Abstract]:Wireless sensor and actuator network (Wireless Sensor and Actor Network,WSAN) is derived from the wireless sensor network (Wireless Sensor Network,WSN) and is usually composed of several sensor nodes and actuator nodes. The actuator node has strong processing ability and high energy. It can analyze, make decision and take corresponding measures according to the information collected by sensor node. In a sense, WSAN is a new network that can change the physical world. Therefore, WSAN also puts forward higher requirements for important positioning technology. In addition, the existing WSN localization algorithm can not be directly transplanted to WSAN, so this paper aims at the shortcomings of the traditional WSN localization algorithm and combined with the needs of WSAN location, the WSAN location algorithm is studied. The specific contents of the study are as follows. This paper summarizes the research progress of WSN/WSAN localization algorithms at home and abroad and analyzes the reasons why existing WSN localization algorithms are not suitable for WSAN. Based on WSN, WSAN is introduced from architecture, node composition and network features. At the same time, six common classification methods in WSAN localization algorithm are listed, and the representative algorithms are introduced in detail. 2. A mobile non-ranging location algorithm (Mobile Range-free Localization Algorithm based on Square Area,MRFS) based on square region is proposed. The algorithm uses moving actuator nodes instead of anchor nodes in WSN to locate. Firstly, the location of unknown nodes is determined by the square layout of actuator nodes, and then the region is continuously reduced by iteration. Finally, the coordinates of the region's centroid as unknown nodes are calculated. The use of mobile actuator nodes can effectively save the network deployment costs, in addition, compared with ranging technology, the location mode of non-ranging greatly reduces the hardware cost. Simulation results show that the algorithm can achieve a good localization effect. In order to avoid the local dense or sparse distribution of actuator nodes and to make the distribution of idle actuator nodes uniform and reasonable, a virtual force model was introduced into the localization process, and a virtual force based MRFS non-ranging localization algorithm (MRFS Localization Algorithm based on Virtual Force, was proposed. MRFSVF). Simulation results show that the introduction of virtual force algorithm can effectively improve the uneven distribution of actuator nodes, thus optimize the coverage area, and reduce the positioning error and time. In the field of ranging and location, the traditional localization algorithm based on signal transmission time (Time of Arrival,TOA) measures the distance between nodes by calculating the signal transmission time, and combines the TOA algorithm with the virtual force model. It is advantageous for the actuator node to approach the sensor node which requests to locate, which can improve the success rate of location because of the continuous movement of the actuator node under the action of virtual force. Simulation results verify the performance of the algorithm. 4. According to the characteristics of each location algorithm and its application, the application of each algorithm is introduced.
【學位授予單位】：南京農業(yè)大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：TP212.9;TN929.5
本文編號：2390405
[Abstract]:Wireless sensor and actuator network (Wireless Sensor and Actor Network,WSAN) is derived from the wireless sensor network (Wireless Sensor Network,WSN) and is usually composed of several sensor nodes and actuator nodes. The actuator node has strong processing ability and high energy. It can analyze, make decision and take corresponding measures according to the information collected by sensor node. In a sense, WSAN is a new network that can change the physical world. Therefore, WSAN also puts forward higher requirements for important positioning technology. In addition, the existing WSN localization algorithm can not be directly transplanted to WSAN, so this paper aims at the shortcomings of the traditional WSN localization algorithm and combined with the needs of WSAN location, the WSAN location algorithm is studied. The specific contents of the study are as follows. This paper summarizes the research progress of WSN/WSAN localization algorithms at home and abroad and analyzes the reasons why existing WSN localization algorithms are not suitable for WSAN. Based on WSN, WSAN is introduced from architecture, node composition and network features. At the same time, six common classification methods in WSAN localization algorithm are listed, and the representative algorithms are introduced in detail. 2. A mobile non-ranging location algorithm (Mobile Range-free Localization Algorithm based on Square Area,MRFS) based on square region is proposed. The algorithm uses moving actuator nodes instead of anchor nodes in WSN to locate. Firstly, the location of unknown nodes is determined by the square layout of actuator nodes, and then the region is continuously reduced by iteration. Finally, the coordinates of the region's centroid as unknown nodes are calculated. The use of mobile actuator nodes can effectively save the network deployment costs, in addition, compared with ranging technology, the location mode of non-ranging greatly reduces the hardware cost. Simulation results show that the algorithm can achieve a good localization effect. In order to avoid the local dense or sparse distribution of actuator nodes and to make the distribution of idle actuator nodes uniform and reasonable, a virtual force model was introduced into the localization process, and a virtual force based MRFS non-ranging localization algorithm (MRFS Localization Algorithm based on Virtual Force, was proposed. MRFSVF). Simulation results show that the introduction of virtual force algorithm can effectively improve the uneven distribution of actuator nodes, thus optimize the coverage area, and reduce the positioning error and time. In the field of ranging and location, the traditional localization algorithm based on signal transmission time (Time of Arrival,TOA) measures the distance between nodes by calculating the signal transmission time, and combines the TOA algorithm with the virtual force model. It is advantageous for the actuator node to approach the sensor node which requests to locate, which can improve the success rate of location because of the continuous movement of the actuator node under the action of virtual force. Simulation results verify the performance of the algorithm. 4. According to the characteristics of each location algorithm and its application, the application of each algorithm is introduced.
【學位授予單位】：南京農業(yè)大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：TP212.9;TN929.5
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