When there are bigger obstacles in the indoor environment such as elevator, the radio waves basically can not penetrate it. The contribution of received signal strength by transmission and reflection will be greatly r...When there are bigger obstacles in the indoor environment such as elevator, the radio waves basically can not penetrate it. The contribution of received signal strength by transmission and reflection will be greatly reduced, and most of the time, the radio waves will reach the user by bypass diffraction. Therefore, the traditional path loss model is no longer applicable, and the improved model should be proposed. In this paper, we firstly proposed an indoor radio propagation model based on dominant path in which the received signal strength has nothing to do with the direct distance between user and access point, but is related to the length of dominant path. Then on the basis of dominant path model, the NLOS influence is considered in order to further improve the accuracy of dominant path model. Experimental results demonstrated that the proposed dominant path model can improve the accuracy of traditional path loss model remarkably.展开更多
Automatic robot navigation is being utilized in many industries for the purpose of high speed work delivery. Color follower, fix path follower robots are current solution to this activities but dynamic path configurat...Automatic robot navigation is being utilized in many industries for the purpose of high speed work delivery. Color follower, fix path follower robots are current solution to this activities but dynamic path configuration is not possible in these robots. Hence new system proposes effective and fully dynamic path follower robots using RFID and directional antenna. Radio Frequency Identification (RFID) system permits automatic identification of objects with RFID tags using radio waves which have been widely used in mobile robot navigation, localization and mapping both in indoor and outdoor environment. This article presents a navigation strategy for autonomous mobile robot using passive RFID system. Proposed robot system is provided with RFID tag functionality which will load tag number and direction instruction. At some turning point, user will put RF tag, this tag will be read by RF reader which is placed on robot. As per direction instruction robot will change the direction and reach to the destination. Also as per the movement, robot will send its GPS location to PC (Personal Computer) which will be displayed on PC. Hence main goal is to provide more reliable and low energy consumption based indoor positioning system which will be achieved using directional antenna.展开更多
Indoor positioning systems (IPSs) have been intended to provide position information of persons and devices. Higher user percentage of handheld devices such as tablets or mobile phones had led to the development of a ...Indoor positioning systems (IPSs) have been intended to provide position information of persons and devices. Higher user percentage of handheld devices such as tablets or mobile phones had led to the development of a number of indoor positioning systems. In this research a work on a real time portable RFID indoor positioning device such as on smartphone will be performed. The personal networks will be designed to meet the users’ needs and interconnect users’ devices equipped with different communications technologies in various places to form one network for better result. Radio frequency identification (RFID) with directional antenna has proved its potential for locating objects in indoor environment. Hence, the proposed device idea will be used to exploit various unknown locations in an indoor environment such as college campus;this interpretation will rely on Wireless LAN, Received Signal Strength values from Access Points (AP) in specific mentioned arenas;these APs will be monitored constantly by RFID with directional antenna (DA) and handheld devices. For obtaining the better results from existing devices, algorithms of Range Estimation are proposed, which can be used on various handheld devices for locating indoor objects.展开更多
We propose a novel indoor positioning algorithm based on the received signal strength(RSS) fingerprint. The proposed algorithm can be divided into three steps, an offline phase at which an advanced clustering(AC) stra...We propose a novel indoor positioning algorithm based on the received signal strength(RSS) fingerprint. The proposed algorithm can be divided into three steps, an offline phase at which an advanced clustering(AC) strategy is used, an online phase of approximate localization at which cluster matching is used, and an online phase of precise localization with kernel ridge regression. Specifically, after offline fingerprint collection and similarity measurement, we employ an AC strategy based on the K-medoids clustering algorithm using additional reference points that are geographically located at the outer cluster boundary to enrich the data of each cluster. During the approximate localization, RSS measurements are compared with the cluster radio maps to determine to which cluster the target most likely belongs. Both the Euclidean distance of the RSSs and the Hamming distance of the coverage vectors between the observations and training records are explored for cluster matching. Then, a kernel-based ridge regression method is used to obtain the ultimate positioning of the target. The performance of the proposed algorithm is evaluated in two typical indoor environments, and compared with those of state-of-the-art algorithms. The experimental results demonstrate the effectiveness and advantages of the proposed algorithm in terms of positioning accuracy and complexity.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
为解决常规的模型存在比较明显的误差,定位时通常不能实现预期定位的问题,设计了一类室内定位系统。该系统很大程度上结合了标准化的RSSI(Received Signal Strength Indicator)测距模型,并应用了高精度的3边定位算法。实验表明,该系统...为解决常规的模型存在比较明显的误差,定位时通常不能实现预期定位的问题,设计了一类室内定位系统。该系统很大程度上结合了标准化的RSSI(Received Signal Strength Indicator)测距模型,并应用了高精度的3边定位算法。实验表明,该系统能在很大程度上解决定位误差问题,误差减小15%,得到可靠的定位结果。展开更多
文摘When there are bigger obstacles in the indoor environment such as elevator, the radio waves basically can not penetrate it. The contribution of received signal strength by transmission and reflection will be greatly reduced, and most of the time, the radio waves will reach the user by bypass diffraction. Therefore, the traditional path loss model is no longer applicable, and the improved model should be proposed. In this paper, we firstly proposed an indoor radio propagation model based on dominant path in which the received signal strength has nothing to do with the direct distance between user and access point, but is related to the length of dominant path. Then on the basis of dominant path model, the NLOS influence is considered in order to further improve the accuracy of dominant path model. Experimental results demonstrated that the proposed dominant path model can improve the accuracy of traditional path loss model remarkably.
文摘Automatic robot navigation is being utilized in many industries for the purpose of high speed work delivery. Color follower, fix path follower robots are current solution to this activities but dynamic path configuration is not possible in these robots. Hence new system proposes effective and fully dynamic path follower robots using RFID and directional antenna. Radio Frequency Identification (RFID) system permits automatic identification of objects with RFID tags using radio waves which have been widely used in mobile robot navigation, localization and mapping both in indoor and outdoor environment. This article presents a navigation strategy for autonomous mobile robot using passive RFID system. Proposed robot system is provided with RFID tag functionality which will load tag number and direction instruction. At some turning point, user will put RF tag, this tag will be read by RF reader which is placed on robot. As per direction instruction robot will change the direction and reach to the destination. Also as per the movement, robot will send its GPS location to PC (Personal Computer) which will be displayed on PC. Hence main goal is to provide more reliable and low energy consumption based indoor positioning system which will be achieved using directional antenna.
文摘Indoor positioning systems (IPSs) have been intended to provide position information of persons and devices. Higher user percentage of handheld devices such as tablets or mobile phones had led to the development of a number of indoor positioning systems. In this research a work on a real time portable RFID indoor positioning device such as on smartphone will be performed. The personal networks will be designed to meet the users’ needs and interconnect users’ devices equipped with different communications technologies in various places to form one network for better result. Radio frequency identification (RFID) with directional antenna has proved its potential for locating objects in indoor environment. Hence, the proposed device idea will be used to exploit various unknown locations in an indoor environment such as college campus;this interpretation will rely on Wireless LAN, Received Signal Strength values from Access Points (AP) in specific mentioned arenas;these APs will be monitored constantly by RFID with directional antenna (DA) and handheld devices. For obtaining the better results from existing devices, algorithms of Range Estimation are proposed, which can be used on various handheld devices for locating indoor objects.
基金Project supported by the National Natural Science Foundation of China (Nos. 51705324 and 61702332)。
文摘We propose a novel indoor positioning algorithm based on the received signal strength(RSS) fingerprint. The proposed algorithm can be divided into three steps, an offline phase at which an advanced clustering(AC) strategy is used, an online phase of approximate localization at which cluster matching is used, and an online phase of precise localization with kernel ridge regression. Specifically, after offline fingerprint collection and similarity measurement, we employ an AC strategy based on the K-medoids clustering algorithm using additional reference points that are geographically located at the outer cluster boundary to enrich the data of each cluster. During the approximate localization, RSS measurements are compared with the cluster radio maps to determine to which cluster the target most likely belongs. Both the Euclidean distance of the RSSs and the Hamming distance of the coverage vectors between the observations and training records are explored for cluster matching. Then, a kernel-based ridge regression method is used to obtain the ultimate positioning of the target. The performance of the proposed algorithm is evaluated in two typical indoor environments, and compared with those of state-of-the-art algorithms. The experimental results demonstrate the effectiveness and advantages of the proposed algorithm in terms of positioning accuracy and complexity.
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.
文摘为解决常规的模型存在比较明显的误差,定位时通常不能实现预期定位的问题,设计了一类室内定位系统。该系统很大程度上结合了标准化的RSSI(Received Signal Strength Indicator)测距模型,并应用了高精度的3边定位算法。实验表明,该系统能在很大程度上解决定位误差问题,误差减小15%,得到可靠的定位结果。
