针对传感器网络在空间、海洋等三维场景下的应用,基于划分空间为球壳并取球壳交集定位的思想,提出了对传感器结点进行三维定位的非距离定位算法APIS(approximate point in sphere),研究了该算法的原理和实现方法,并对该算法在VC环境中...针对传感器网络在空间、海洋等三维场景下的应用,基于划分空间为球壳并取球壳交集定位的思想,提出了对传感器结点进行三维定位的非距离定位算法APIS(approximate point in sphere),研究了该算法的原理和实现方法,并对该算法在VC环境中进行了仿真实验,并对其结果进行了分析.实验表明,在100×100×100单位的三维空间中,随机放置55个锚结点,就能对98%的结点进行定位,其平均相对误差仅为60%.因此,APIS算法能有效地实现三维环境中的传感器结点定位.展开更多
As much as accurate or precise position estimation is always desirable, coarse accuracy due to sensor node localization is often sufficient. For such level of accuracy, Range-free localization techniques are being exp...As much as accurate or precise position estimation is always desirable, coarse accuracy due to sensor node localization is often sufficient. For such level of accuracy, Range-free localization techniques are being explored as low cost alternatives to range based localization techniques. To manage cost, few location aware nodes, called anchors are deployed in the wireless sensor environment. It is from these anchors that all other free nodes are expected to estimate their own positions. This paper therefore, takes a look at some of the foremost Range-free localization algorithms, detailing their limitations, with a view to proposing a modified form of Centroid Localization Algorithm called Reach Centroid Localization Algorithm. The algorithm employs a form of anchor nodes position validation mechanism by looking at the consistency in the quality of Received Signal Strength. Each anchor within the vicinity of a free node seeks to validate the actual position or proximity of other anchors within its vicinity using received signal strength. This process mitigates multipath effects of radio waves, particularly in an enclosed environment, and consequently limits localization estimation errors and uncertainties. Centroid Localization Algorithm is then used to estimate the location of a node using the anchors selected through the validation mechanism. Our approach to localization becomes more significant, particularly in indoor environments, where radio signal signatures are inconsistent or outrightly unreliable. Simulated results show a significant improvement in localization accuracy when compared with the original Centroid Localization Algorithm, Approximate Point in Triangulation and DV-Hop.展开更多
文摘针对传感器网络在空间、海洋等三维场景下的应用,基于划分空间为球壳并取球壳交集定位的思想,提出了对传感器结点进行三维定位的非距离定位算法APIS(approximate point in sphere),研究了该算法的原理和实现方法,并对该算法在VC环境中进行了仿真实验,并对其结果进行了分析.实验表明,在100×100×100单位的三维空间中,随机放置55个锚结点,就能对98%的结点进行定位,其平均相对误差仅为60%.因此,APIS算法能有效地实现三维环境中的传感器结点定位.
文摘As much as accurate or precise position estimation is always desirable, coarse accuracy due to sensor node localization is often sufficient. For such level of accuracy, Range-free localization techniques are being explored as low cost alternatives to range based localization techniques. To manage cost, few location aware nodes, called anchors are deployed in the wireless sensor environment. It is from these anchors that all other free nodes are expected to estimate their own positions. This paper therefore, takes a look at some of the foremost Range-free localization algorithms, detailing their limitations, with a view to proposing a modified form of Centroid Localization Algorithm called Reach Centroid Localization Algorithm. The algorithm employs a form of anchor nodes position validation mechanism by looking at the consistency in the quality of Received Signal Strength. Each anchor within the vicinity of a free node seeks to validate the actual position or proximity of other anchors within its vicinity using received signal strength. This process mitigates multipath effects of radio waves, particularly in an enclosed environment, and consequently limits localization estimation errors and uncertainties. Centroid Localization Algorithm is then used to estimate the location of a node using the anchors selected through the validation mechanism. Our approach to localization becomes more significant, particularly in indoor environments, where radio signal signatures are inconsistent or outrightly unreliable. Simulated results show a significant improvement in localization accuracy when compared with the original Centroid Localization Algorithm, Approximate Point in Triangulation and DV-Hop.
