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作 者:乐燕芬[1] 罗红玉[1] 赵妍[1] 施伟斌[1] LE Yanfen;LUO Hongyu;ZHAO Yan;SHI Weibin(School of Optical Electrical and Computer Engineering,University of Shanghai tor Science and Technology,Shanghai 20093,China)
机构地区:[1]上海理工大学光电信息与计算机工程学院,上海200093
出 处:《电子科技》2018年第11期42-46,共5页Electronic Science and Technology
基 金:上海市科委重点科技攻关项目(14511107902)
摘 要:目前无线传感器网络中移动节点进行室内定位时,实际应用环境中存在的随机环境噪声会影响定位稳定性和精度。针对这一问题,文中提出了一种基于无线传感器节点RSS值的位置指纹定位算法。该算法利用高斯核函数完成位置指纹匹配,再通过卡尔曼滤波减少估计误差。为了研究实际应用环境中本算法的有效性,设计并实现了基于Android平台的室内移动目标的实时定位系统。实验结果表明,移动目标3 m内的定位精度达100%,单次定位时间在1 s内。High resolution localization tor indoor environment has got increasing attention in wireless sensor networks. The stability and accuracy of indoor positioning were limited due to the noise in the indoor environment. To solve this problem, a new location fingerprint localization algorithm based on RSS value of wireless sensor nodes was presented in this paper. The algorithm combined kernel - based fingerprint with Kalman filter to estimate position of a moving target. In order to study the ettectiveness of this algorithm in real environment, a real - time location system for indoor mobile targets based on Android platform was designed and implemented. The experimental resuhs showed that the positioning accuracy of the moving target within 3 m reached 100% and the single positioning time was within 1 s, which was an efficiency solution tbr mobile target tracking in indoor environment.
关 键 词:无线传感器网络 室内定位 位置指纹 核函数 卡尔曼滤波 ANDROID平台
分 类 号:TP393[自动化与计算机技术—计算机应用技术]
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