The challenging conditions prevalent in indoor environments have rendered many traditional positioning methods inept to yield satisfactory results. Our work tackles the challenging problem of accurate indoor positioni...The challenging conditions prevalent in indoor environments have rendered many traditional positioning methods inept to yield satisfactory results. Our work tackles the challenging problem of accurate indoor positioning in hazardous multipath environments through three versatile super resolution techniques: time domain Multiple Signal Classification (TD-MUSIC), frequency domain MUSIC (FD-MUSIC) algorithms, and frequency domain Eigen value (FD-EV) method. The advantage of using these super resolution techniques is twofold. First for Line-of-Sight (LoS) conditions this provides the most accurate means of determining the time delay estimate from transmitter to receiver for any wireless sensor network. The high noise immunity and resolvability of these methods makes them ideal for cost-effective wireless sensor networks operating in indoor channels. Second for non-LoS conditions the resultant pseudo-spectrum generated by these methods provides the means to construct the ideal location based fingerprint. We provide an in depth analysis of limitation as well as advantages inherent in all of these methods through a detailed behavioral analysis under constrained environments. Hence, the bandwidth versatility, higher resolution capability and higher noise immunity of the TD-MUSIC algorithm and the FD-EV method’s ability to resurface submerged signal peaks when the signal subspace dimensions are underestimated are all presented in detail.展开更多
为了完成短距离室内定位问题,提出了一种利用ZigBee技术的解决方案.通过对无线电传播路径损耗模型的分析,给出了一种基于接受信号强度指示(Received Signal StrengthIndicator,RSSI)的节点定位算法.以三边定位算法为基础,对得出的解加...为了完成短距离室内定位问题,提出了一种利用ZigBee技术的解决方案.通过对无线电传播路径损耗模型的分析,给出了一种基于接受信号强度指示(Received Signal StrengthIndicator,RSSI)的节点定位算法.以三边定位算法为基础,对得出的解加权平均以达到优化定位结果的作用.实验研究表明,在一定的通讯距离之内,可实现在扩大定位范围的同时提高定位精度.现场实验中最佳定位控制精度可达到0.5 m.展开更多
文摘The challenging conditions prevalent in indoor environments have rendered many traditional positioning methods inept to yield satisfactory results. Our work tackles the challenging problem of accurate indoor positioning in hazardous multipath environments through three versatile super resolution techniques: time domain Multiple Signal Classification (TD-MUSIC), frequency domain MUSIC (FD-MUSIC) algorithms, and frequency domain Eigen value (FD-EV) method. The advantage of using these super resolution techniques is twofold. First for Line-of-Sight (LoS) conditions this provides the most accurate means of determining the time delay estimate from transmitter to receiver for any wireless sensor network. The high noise immunity and resolvability of these methods makes them ideal for cost-effective wireless sensor networks operating in indoor channels. Second for non-LoS conditions the resultant pseudo-spectrum generated by these methods provides the means to construct the ideal location based fingerprint. We provide an in depth analysis of limitation as well as advantages inherent in all of these methods through a detailed behavioral analysis under constrained environments. Hence, the bandwidth versatility, higher resolution capability and higher noise immunity of the TD-MUSIC algorithm and the FD-EV method’s ability to resurface submerged signal peaks when the signal subspace dimensions are underestimated are all presented in detail.
文摘为了完成短距离室内定位问题,提出了一种利用ZigBee技术的解决方案.通过对无线电传播路径损耗模型的分析,给出了一种基于接受信号强度指示(Received Signal StrengthIndicator,RSSI)的节点定位算法.以三边定位算法为基础,对得出的解加权平均以达到优化定位结果的作用.实验研究表明,在一定的通讯距离之内,可实现在扩大定位范围的同时提高定位精度.现场实验中最佳定位控制精度可达到0.5 m.
