With the rapid development of wireless local area network （WLAN） technology, an important target of indoor positioning systems is to improve the positioning accuracy while reducing the online calibration effort to o...With the rapid development of wireless local area network （WLAN） technology, an important target of indoor positioning systems is to improve the positioning accuracy while reducing the online calibration effort to overcome signal time-varying. A novel fingerprint positioning algorithm, known as the adaptive radio map with updated method based on hidden Markov model （HMM）, is proposed. It is shown that by using a collection of user traces that can be cheaply obtained, the proposed algorithm can take advantage of these data to update the labeled calibration data to further improve the position estimation accuracy. This algorithm is a combination of machine learning, information gain theory and fingerprinting. By collecting data and testing the algorithm in a realistic indoor WLAN environment, the experiment results indicate that, compared with the widely used K nearest neighbor algorithm, the proposed algorithm can improve the positioning accuracy while greatly reduce the calibration effort.展开更多
针对接收信号强度(received signal strength,RSS)的时变性降低WLAN室内定位精度的问题,提出了一种基于核直接判别分析(kernel direct discriminant analysis,KDDA)和混洗蛙跳最小二乘支持向量回归机(SFLA-LSSVR)的定位算法,该算法通过...针对接收信号强度(received signal strength,RSS)的时变性降低WLAN室内定位精度的问题,提出了一种基于核直接判别分析(kernel direct discriminant analysis,KDDA)和混洗蛙跳最小二乘支持向量回归机(SFLA-LSSVR)的定位算法,该算法通过核函数策略将采集的各接入点(access point,AP)的RSS信号映射到非线性领域,有效提取了非线性定位特征,重组定位信息,去除冗余定位特征和噪声;然后采用LSSVR算法构建指纹点定位特征数据与物理位置的映射关系模型,采用SFLA算法优化该关系模型的参数,并用该关系模型对测试点的位置进行回归预测.实验结果表明:提出算法在相同的采样次数下的定位精度明显优于WKNN,ANN,LSSVR算法,并且在相同的定位精度下,采样次数较大减少,是一种性能良好的WLAN室内定位算法.展开更多
接收信号强度(received signal strength,RSS)浮动和无线接入点缺失是制约无线局域网(wirelesslocal area network,WLAN)定位精度的主要问题。利用智能终端已有的MARG(magnetic,angular rate,andgravity)传感器,设计了基于粒子滤波和卡...接收信号强度(received signal strength,RSS)浮动和无线接入点缺失是制约无线局域网(wirelesslocal area network,WLAN)定位精度的主要问题。利用智能终端已有的MARG(magnetic,angular rate,andgravity)传感器,设计了基于粒子滤波和卡尔曼滤波的数据融合算法,实现了一个低成本高精度的WLAN/MARG组合定位系统。该系统利用WLAN和MARG定位技术的互补特性,有效校正了由RSS浮动引起的定位误差和由传感器噪声引起的累积误差。室内WLAN环境下的实验结果表明,本文所提系统,相比WLAN和MARG定位系统,定位均方根误差分布减少了62%和91%,并且有效扩大了系统应用范围。展开更多
基金supported by the National Natural Science Foundation of China(61571162)the Major National Science and Technology Project(2014ZX03004003-005)
文摘With the rapid development of wireless local area network （WLAN） technology, an important target of indoor positioning systems is to improve the positioning accuracy while reducing the online calibration effort to overcome signal time-varying. A novel fingerprint positioning algorithm, known as the adaptive radio map with updated method based on hidden Markov model （HMM）, is proposed. It is shown that by using a collection of user traces that can be cheaply obtained, the proposed algorithm can take advantage of these data to update the labeled calibration data to further improve the position estimation accuracy. This algorithm is a combination of machine learning, information gain theory and fingerprinting. By collecting data and testing the algorithm in a realistic indoor WLAN environment, the experiment results indicate that, compared with the widely used K nearest neighbor algorithm, the proposed algorithm can improve the positioning accuracy while greatly reduce the calibration effort.
文摘针对接收信号强度(received signal strength,RSS)的时变性降低WLAN室内定位精度的问题,提出了一种基于核直接判别分析(kernel direct discriminant analysis,KDDA)和混洗蛙跳最小二乘支持向量回归机(SFLA-LSSVR)的定位算法,该算法通过核函数策略将采集的各接入点(access point,AP)的RSS信号映射到非线性领域,有效提取了非线性定位特征,重组定位信息,去除冗余定位特征和噪声;然后采用LSSVR算法构建指纹点定位特征数据与物理位置的映射关系模型,采用SFLA算法优化该关系模型的参数,并用该关系模型对测试点的位置进行回归预测.实验结果表明:提出算法在相同的采样次数下的定位精度明显优于WKNN,ANN,LSSVR算法,并且在相同的定位精度下,采样次数较大减少,是一种性能良好的WLAN室内定位算法.
文摘接收信号强度(received signal strength,RSS)浮动和无线接入点缺失是制约无线局域网(wirelesslocal area network,WLAN)定位精度的主要问题。利用智能终端已有的MARG(magnetic,angular rate,andgravity)传感器,设计了基于粒子滤波和卡尔曼滤波的数据融合算法,实现了一个低成本高精度的WLAN/MARG组合定位系统。该系统利用WLAN和MARG定位技术的互补特性,有效校正了由RSS浮动引起的定位误差和由传感器噪声引起的累积误差。室内WLAN环境下的实验结果表明,本文所提系统,相比WLAN和MARG定位系统,定位均方根误差分布减少了62%和91%,并且有效扩大了系统应用范围。
