A novel adaptive cooperative location algorithm for wireless sensor networks

To overcome the disadvantages of the location algorithm based on received signal strength indication(RSSI) in the existing wireless sensor networks(WSNs),a novel adaptive cooperative location algorithm is proposed.To tolerate some minor errors in the information of node position,a reference anchor node is employed.On the other hand,Dixon method is used to remove the outliers of RSSI,the standard deviation threshold of RSSI and the learning model are put forward to reduce the ranging error of RSSI and improve the positioning precision effectively.Simulations are run to evaluate the performance of the algorithm.The results show that the proposed algorithm offers more precise location and better stability and robustness.     

基于RSSI距离修正的WSNs定位算法

针对无线传感器网络(WSNs)易受外界因素影响,导致三边定位的锚圆不能相交的情况,提出了一种接收信号强度指示(RSSI)距离修正定位算法。通过对锚圆半径进行修正,形成3个锚圆相交的区域,然后用加权定位法对未知节点进行准确定位。仿真和实验结果表明:在6 m×10 m的区域范围内,该算法的平均定位误差为0.62 m,和其他定位方法相比,有更好的定位精度。     

蚁群聚类能量分簇在802．11无线网络定位中的应用

IEEE 802．11无线网络以快速灵活的组网方式得到广泛部署和应用,其定位方法也成为近年研究热点。论文提出了一种基于蚁群聚类能量分簇RSSI指纹定位算法,利用蚁群信息素反馈机制优化能量聚类分簇和收敛速度,再根据能量指纹匹配定位节点位置。仿真实验表明,该算法定位精确,能很好地减小由信号波动引起的定位误差。     

针对多目标的分布式多边融合定位

针对基于接收信号强度指数(Received Signal Strength Indicator,RSSI)的多目标定位问题,结合点估计与椭圆估计算法,提出一种新的分布式多边融合定位(Distributed Multi-lateral Fusion Localization,DMFL)算法.首先,通过多边定位算法进行粗定位,估计目标的大致位置.其次,基于区间分析理论在线获取泰勒展式高阶余项的边界,并通过集员递归算法求解多目标定位问题.最后,通过实验和仿真验证该算法的定位性能.结果表明,在相同的节点布置条件下,与最新的RSSI定位算法相比,该算法的定位精度更高,最大误差小于0.3 m,并可提供保证包含目标真实位置的最优区域.     

Mathematical Advancement of General Chlorine Bulk Decay Model

An accurate chlorine bulk decay model is needed to ensure that potable water meets the microbial and the chemical safeties at the treatment plant and throughout the distribution. Among the mathematical models available,the general second-order chlorine bulk decay model( GBDM) is the most fundamentally sound.Application of the GBDM,however,has been hindered by its numerous fictive parameters and lack of an analytical solution. This theoretical work removes the two obstacles. The GBDM is solved through transformation and integration. The analytical solution provides deep insights into the GBDM and facilitates the parameterization and sensitivity analysis. The background natural organic matter( NOM) is characterized with the probabilistic distribution of functional groups. It reveals that the mean of the function group distribution is correlated with the initial chlorine decay rate coefficient( κ_0). A simple formula is developed to determine κ_0 directly from the initial chlorine decay. The theoretical treatment reduces the fictive parameters to a minimum. For the common lognormal distribution,the GBDM needs only three parameters,well defined as initial chlorine demand X_0,median rate coefficient km,and heterogeneity index σ. For more complicated scenarios,composite distributions are constructed through superposition of individual distributions. A highlighted example is to predict chlorine decay in blends of different waters. With the theoretical and mathematical advancement here,the GBDM can be applied effectively to any reactive background matter in any reaction systems.     

一种用于家庭牧场的RSSI定位算法

针对家庭牧场对羊的定位需求,提出了一种用于草原环境的RSSI定位算法.该算法采用噪声模型处理原始数据,结合质心算法进行目标定位及路径距离计算.实验结果表明,该算法可较准确地计算出牧场内羊的位置坐标及活动的路径距离.     

基于平方位置误差下限的优化功率分配方案

在无线传感网络中,节点定位是基于位置的应用基本要求。然而,现多数文献仅关注定位精度,而忽略了能量消耗对定位精度的影响。为此,针对基于接收信号强度RSSI(Received Signal Strength Indicator)定位方案,提出基于平方位置误差下限SPEB(Squared Position Error Bound)的优化功率分配SPEB-OPA(SPEB-Based Optimal Power Allocation)方案,目的在于最小化能量消耗。在SPEB-OPA算法中,将SPEB作为评定定位精度的参数,并推导出SPEB表达式,然后建立优化功率分配的目标函数,并考虑到锚节点位置存在误差。仿真结果表明,提出的SPEB-OPA方案极大地减少了功率消耗。当误差门限T=8时,SPEB-OPA方案的功率消耗比统一功率分配UPA(Uniform Power allocation)方案减少至50%。     

ZigBee网中减少障碍物影响的定位算法

从ZigBee定位优势出发,阐述了用于定位的ZigBee系统的拓扑结构,重点分析了基于RSSI的ZigBee的定位算法及实现,并建立了测量的物理模型.经过实验验证,该算法具有一定的实际应用价值,可以得到实验场景的最优测距模型.     

基于RSSI的无线传感器网络迭代安全定位算法

分析了无线传感器网络节点定位过程中的安全性问题,针对接收信号强度指示(RSSI)测距技术,提出了一种结合梯度下降法和离群检测技术的安全定位算法.仿真和实验结果表明:使用该算法的无线传感器节点在存在攻击的环境下依然能够正常定位,当平均测距误差为0.7m时,定位误差为1m.     

无线传感器网络中APIT-HR定位算法

针对无线传感器网络(WSNs)中近似四面体内点(APIT)质心定位算法计算复杂度高、定位精度差的问题,提出一种基于RSSI值折半的APIT (APIT-HR)质心定位算法.该算法以未知节点与三角形中的两个锚节点同时感知第三个锚节点的RSSI值进行比较并确定未知节点的存在区域,再以该区域质心作为定位结果.以面积规则和圆交域质心法改善APIT算法中存在的一些缺陷.仿真实验表明:相对于原始的APIT质心定位算法,APIT-HR算法降低了计算复杂度,提高了定位覆盖率和定位精度,定位误差缩小了22.8％.