摘要
传统的近似三角形内点测试(APIT),即近似三角形内点测试定位算法,广泛应用于静态节点定位。结合粒子滤波提出改进算法,将APIT算法推广到节点动态定位。算法根据节点的移动性和APIT多边重合区域确定采样区域,通过目标节点的接收信号强度指示(RSSI)序列值过滤样本,使样本值的数学期望收敛于目标节点。仿真表明:该算法有效缩小采样区域,降低了定位能耗,与MCL,MCB算法相比,更精确地实现了动态定位。
Traditional APIT test localization algorithm is widely used in static node location. An improved APIT algorithm is proposed combined with particle filter to promote it into node dynamic location. This algorithm determines the sample area according to node mobility and the APIT Polygon overlap area, and filter samples through the target node＇ s received signal strength indication （RSS]） sequence values, in order that mathematical expectation of the sample values could converge to that of the target node. Simulation results show that the algorithm e^ficently reduce the sampling area and the location energy consumption. To a certain extent, more accurately realize dynamic positioning compared with MCL and MCB algorithm.
出处
《传感器与微系统》
CSCD
北大核心
2011年第9期72-75,共4页
Transducer and Microsystem Technologies
基金
国家"863"计划资助项目(2007AA04Z174)
