Adaptive Accurate Indoor-Localization Using Passive rFID Xi Chen,Lei Xie,Chuyu Wang,Sanglu Lu State Key Laboratory for Novel Software Technology,Nanjing University,China hawkxc@dislab.nju.edu.cn,Ixie@nju.edu.cn,wangcyu217@126.com,sanglu@nju.edu.cn Abstract-In many pervasive applications like the intelligent time,the regularities of the variation in backscattered signals is bookshelves in libraries,it is essential to accurately locate the still unclear enough in the realistic settings,which is different items to provide the location-based service,e.g.,the average lo- from conventional wireless devices. calization error should be smaller than 50 cm and the localization delay should be within several seconds.Conventional indoor- Therefore,it is essential to investigate the backscattering localization schemes cannot provide such accurate localization features of passive RFID system through experiment study,and results.In this paper,we design an adaptive,accurate indoor- further devise an efficient localization scheme by leveraging localization scheme using passive RFID systems.We propose the passive RFID system.In this paper,according to the two adaptive solutions,i.e.,the adaptive power stepping and reference tag-based localization,we design an adaptive,real- the adaptive calibration,which can adaptively adjust the critical time indoor-localization scheme using passive RFID systems. parameters and leverage the feedbacks to improve the localization Specifically,we make the following contributions in this paper accuracy.The realistic experiment results indicate that,our adaptive localization scheme can achieve an accuracy of 31 cm We conduct an extensive experimental study over within 2.6 seconds on average. the passive RFID systems,and obtain several novel findings from the experiments.We thus propose a Keywords-Indoor localization,adaptive,accurate,passive R- FID tag,calibration,power stepping model to depict the regularities in RFID localization. We propose two adaptive solutions for localization, I.INTRODUCTION i.e..the adaptive power stepping and the adaptive calibration,which can adaptively adjust the critical In many pervasive applications,the proliferation of wireless parameters and leverage the feedbacks to improve the and mobile devices has fostered the demand for context-aware localization accuracy. or location-based services,therefore,it is essential to accu- rately locate the items to provide the location-based service. ● We build a realistic testbed,i.e.,a large bookshelf With the rapid proliferation of RFID-based applications,RFID embedded with passive RFID systems,to evaluate the performance of our solutions.The realistic experiment tags have been deployed into pervasive spaces in increasingly results indicate that,our adaptive localization scheme large numbers,e.g.,the shelves of super markets or libraries are filled with tag-labeled items.In these applications,a high- can achieve an accuracy of 31 cm within 2.6 seconds on average. precision localization scheme is essentially required in accurate approach,e.g.,the average localization error should be smaller The rest of this paper is organized as follows.We dis- than 50cm and the localization delay should be within several cuss the indoor localization technology in Section II.The seconds. experimental observations in the realistic settings are presented However.conventional indoor localization schemes can- in Section III.Section IV presents the system architecture not provide such accurate localization results.For example, of the whole work.The basic framework and motivation of localization schemes based on WiFi,bluetooth and Zigbee our localization methods is presented in Section V.Section usually achieve localization errors of no smaller than 2~3m VI presents the details of APS method and Section VII RFID-based localization schemes like LANDMARC leverages presents the details of AGC method.Then integrated method the active RFID system to assist localization.It employs the is presented in Section VIII.We evaluate the performance of idea of having extra fixed location reference tags to support all the methods in different dimension in Section IX.Finally. location calibration.Still,it achieves localization errors of We conclude the work in Section X. no smaller than 1m and suffers from several drawbacks in adaptivity.By comparison,the passive RFID system brings us II.RELATED WORKS opportunities to devise a highly accurate localization scheme Indoor localization technology has been studied for many First,due to the backscatter property,the received signal years.Generally,they are divided into transmitting model- strength indicator(RSSI)from passive RFID system is very based localization and fingerprint-based localization.The sensitive to the distance,a small change of the distance can model-based localization includes time of arrival(TOA)[1], greatly impact the RSSI of the passive tag.Second,due to the time delay of arrival(TDOA)[2],angle of arrival(AOA)[3], low cost of the chip,the passive tags can be widely deployed signal phase[4].Another approach to use RSSI is building a as reference tags to provide more fingerprints in offsetting the model for localization[56]. surrounding environmental factors.However,the passive RFID The fingerprint-based Localization uses RSSI by site sur- system is also impacted by several factors in localization,e.g.. vey.Multiple readers are deployed in order to collect the RSSI the RSSI from the passive tag is very unstable and varies all the fingerprints.Yang et al.investigate novel sensors integrated inAdaptive Accurate Indoor-Localization Using Passive RFID Xi Chen, Lei Xie, Chuyu Wang, Sanglu Lu State Key Laboratory for Novel Software Technology, Nanjing University, China hawkxc@dislab.nju.edu.cn, lxie@nju.edu.cn, wangcyu217@126.com, sanglu@nju.edu.cn Abstract—In many pervasive applications like the intelligent bookshelves in libraries, it is essential to accurately locate the items to provide the location-based service, e.g., the average lo￾calization error should be smaller than 50 cm and the localization delay should be within several seconds. Conventional indoor￾localization schemes cannot provide such accurate localization results. In this paper, we design an adaptive, accurate indoor￾localization scheme using passive RFID systems. We propose two adaptive solutions, i.e., the adaptive power stepping and the adaptive calibration, which can adaptively adjust the critical parameters and leverage the feedbacks to improve the localization accuracy. The realistic experiment results indicate that, our adaptive localization scheme can achieve an accuracy of 31 cm within 2.6 seconds on average. Keywords—Indoor localization, adaptive, accurate, passive R￾FID tag, calibration, power stepping I. INTRODUCTION In many pervasive applications, the proliferation of wireless and mobile devices has fostered the demand for context-aware or location-based services, therefore, it is essential to accu￾rately locate the items to provide the location-based service. With the rapid proliferation of RFID-based applications, RFID tags have been deployed into pervasive spaces in increasingly large numbers, e.g., the shelves of super markets or libraries are filled with tag-labeled items. In these applications, a high￾precision localization scheme is essentially required in accurate approach, e.g., the average localization error should be smaller than 50cm and the localization delay should be within several seconds. However, conventional indoor localization schemes can￾not provide such accurate localization results. For example, localization schemes based on WiFi, bluetooth and Zigbee usually achieve localization errors of no smaller than 2∼3m. RFID-based localization schemes like LANDMARC leverages the active RFID system to assist localization. It employs the idea of having extra fixed location reference tags to support location calibration. Still, it achieves localization errors of no smaller than 1m and suffers from several drawbacks in adaptivity. By comparison, the passive RFID system brings us opportunities to devise a highly accurate localization scheme. First, due to the backscatter property, the received signal strength indicator(RSSI) from passive RFID system is very sensitive to the distance, a small change of the distance can greatly impact the RSSI of the passive tag. Second, due to the low cost of the chip, the passive tags can be widely deployed as reference tags to provide more fingerprints in offsetting the surrounding environmental factors. However, the passive RFID system is also impacted by several factors in localization, e.g., the RSSI from the passive tag is very unstable and varies all the time, the regularities of the variation in backscattered signals is still unclear enough in the realistic settings, which is different from conventional wireless devices. Therefore, it is essential to investigate the backscattering features of passive RFID system through experiment study, and further devise an efficient localization scheme by leveraging the passive RFID system. In this paper, according to the reference tag-based localization, we design an adaptive, real￾time indoor-localization scheme using passive RFID systems. Specifically, we make the following contributions in this paper. • We conduct an extensive experimental study over the passive RFID systems, and obtain several novel findings from the experiments. We thus propose a model to depict the regularities in RFID localization. • We propose two adaptive solutions for localization, i.e., the adaptive power stepping and the adaptive calibration, which can adaptively adjust the critical parameters and leverage the feedbacks to improve the localization accuracy. • We build a realistic testbed, i.e., a large bookshelf embedded with passive RFID systems, to evaluate the performance of our solutions. The realistic experiment results indicate that, our adaptive localization scheme can achieve an accuracy of 31 cm within 2.6 seconds on average. The rest of this paper is organized as follows. We dis￾cuss the indoor localization technology in Section II. The experimental observations in the realistic settings are presented in Section III. Section IV presents the system architecture of the whole work. The basic framework and motivation of our localization methods is presented in Section V. Section VI presents the details of APS method and Section VII presents the details of AGC method. Then integrated method is presented in Section VIII. We evaluate the performance of all the methods in different dimension in Section IX. Finally, We conclude the work in Section X. II. RELATED WORKS Indoor localization technology has been studied for many years. Generally, they are divided into transmitting model￾based localization and fingerprint-based localization.The model-based localization includes time of arrival(TOA)[1], time delay of arrival(TDOA)[2], angle of arrival(AOA)[3], signal phase[4]. Another approach to use RSSI is building a model for localization[5][6]. The fingerprint-based Localization uses RSSI by site sur￾vey. Multiple readers are deployed in order to collect the RSSI fingerprints. Yang et al. investigate novel sensors integrated in