Deep learning approach for UHF RFID-based indoor localization

2021 ◽  
pp. 1-13
Author(s):  
Haishu Ma ◽  
Zongzheng Ma ◽  
Lixia Li ◽  
Ya Gao
Keyword(s):  
Radio Frequency Identification ◽  
Indoor Environment ◽  
Indoor Localization ◽  
Estimation Error ◽  
Research Direction ◽  
Linear Interpolation ◽  
Linear Mapping ◽  
Uhf Rfid ◽  
Indoor Location ◽  
Main Research

Due to the proliferation of the IoT devices, indoor location-based service is bringing huge business values and potentials. The positioning accuracy is restricted by the variability and complexity of the indoor environment. Radio Frequency Identification (RFID), as a key technology of the Internet of Things, has became the main research direction in the field of indoor positioning because of its non-contact, non-line-of-sight and strong anti-interference abilities. This paper proposes the deep leaning approach for RFID based indoor localization. Since the measured Received Signal Strength Indicator (RSSI) can be influenced by many indoor environment factors, Kalman filter is applied to erase the fluctuation. Furthermore, linear interpolation is adopted to increase the density of the reference tags. In order to improve the processing ability of the fingerprint database, deep neural network is adopted together with the fingerprinting method to optimize the non-linear mapping between fingerprints and indoor coordinates. The experimental results show that the proposed method achieves high accuracy with a mean estimation error of 0.347 m.

Accurate Dead Reckoning Localization System Using RFID Phase

2014 ◽  
Vol 513-517 ◽  
pp. 3296-3299 ◽  
Author(s):  
Bo Li ◽  
Dong Wang
Keyword(s):  
Radio Frequency Identification ◽  
Indoor Environment ◽  
Indoor Localization ◽  
Dead Reckoning ◽  
Location Based Service ◽  
Rfid Tag ◽  
Whole Process ◽  
Localization Scheme ◽  
Frequency Identification ◽  
Series Of Experiments

Nowadays, the demands of Location-based Service are growing fast. It contains huge business opportunities. This paper presents an efficient indoor localization scheme using Radio-Frequency Identification technology. The major idea of our method is Dead Reckoning, a method of navigation that using the best estimates of speed and direction to calculate users' motion trace. We implemented Dead Reckoning in indoor environment by taking advantage of features of RFID. We collected RFID tag phase value to calculate the velocity of users and recalibrate users' position by using known fixed RFID reader. We designed a series of experiments to verify the feasibility of our velocity calculation method, then we simulated the whole process of our system. The results show that our system can track user's motion effectively in indoor environment. We believe this is an encouraging result, holding promise for real-world deployment.

The RFID Indoor Positioning Algorithm Based on Lagrange Interpolation

2014 ◽  
Vol 998-999 ◽  
pp. 947-950
Author(s):  
Hui Bao ◽  
Jiu Ying Zhi
Keyword(s):  
Radio Frequency Identification ◽  
Linear Interpolation ◽  
Virtual Reference ◽  
Indoor Location ◽  
Original Algorithm ◽  
Reference Tags ◽  
Frequency Identification ◽  
Location Methods ◽  
Positioning Algorithm ◽  
Better Than

This paper analyzes two classic indoor location methods based on Radio Frequency Identification (RFID),LANDMARC and VIRE,and presents a location method based on the lagrange interpolation.Make up for the inadequacy of VIRE algorithm uses linear interpolation to get the virtual reference tags signal strength value lead to inaccurate positioning.Then making improvement to weight definition to make it more accurately reflect the weight of each selected nearest label to get more accurate positioning results. The experimental results show that the improved algorithm is better than the original algorithm has better positioning results and stability.

scholarly journals WallSense: Device-Free Indoor Localization Using Wall-Mounted UHF RFID Tags

Sensors ◽  
2018 ◽  
Vol 19 (1) ◽  
pp. 68 ◽  
Author(s):  
Liang Ma ◽  
Meng Liu ◽  
Hongjun Wang ◽  
Yang Yang ◽  
Na Wang ◽  
...  
Keyword(s):  
Radio Frequency Identification ◽  
Indoor Localization ◽  
Fitness Function ◽  
Rfid Tags ◽  
Uhf Rfid ◽  
Swarm Optimization ◽  
Median Error ◽  
Frequency Identification ◽  
Device Free ◽  
Extract Information

To achieve device-free indoor localization without the active participation of the users, this paper presents WallSense, a device-free indoor localization system based on off-the-shelf Radio RFID (Radio-Frequency Identification) equipment. The system deploys two orthogonal tag arrays in adjoining walls and uses the RSSI and phase information measured by RFID readers to localize the target. By differentiating the backscattered signal between adjacent tag pairs, WallSense is able to eliminate most undesirable factors and extract information directly related to the location of the target. By applying Particle Swarm Optimization (PSO) with a novel weighted fitness function and combining the localization result of two orthogonal tag arrays, the system is able to localize the target with high accuracy. Experiments show that the system is able to localize human target with 0.24 m median error. Also, WallSense has low deployment overhead and do not require the users to carry any devices.

scholarly journals Mobile Drone Localization in Indoor Environment Based on Passive RFID

2020 ◽  
Vol 14 (05) ◽  
pp. 4
Author(s):  
Mohamed Hadi Habaebi ◽  
Rashid Khamis Omar ◽  
Md Rafiqul Islam
Keyword(s):  
Radio Frequency Identification ◽  
Information Exchange ◽  
Indoor Environment ◽  
Indoor Localization ◽  
Localization Accuracy ◽  
Localization Method ◽  
Mobile Objects ◽  
Frequency Identification ◽  
Passive Rfid ◽  
Rfid Readers

<p class="AEEEAbstract">Radio Frequency Identification (RFID) is an information exchange technology based on RF communication. It provides solution to track and localize mobile objects in the indoor environment. Localization of mobile objects in an indoor environment garnered a significant attention due to the variety of applications needing higher degree of localization accuracy. RSS-based localization techniques are the major tools for tracking applications due to their simplicity. In this paper, a trilateration method for indoor localization is proposed. This method provides a solution for the drone tracking problem by collecting the RSS values between RFID tagged drone and reader, and estimate its location. The localization method is implemented in MATLAB by multiple readers; 4 RFID readers and 8 RFID readers. The performance of the localization method is also compared with other RFID localization previously reported in the literature. The simulation results in the case of 8 RFID readers demonstrate more accurate results than 4 RFID readers by minimizing the localization error from 0.84606 to 0.40079m. The results also indicate an improved localization performance of tracking a tagged drone in indoor environment by 42.8% when 8RFID readers are placed in the localization area.</p>

scholarly journals Smartphone Sensor Based Indoor Positioning: Current Status, Opportunities, and Future Challenges

Electronics ◽  
2020 ◽  
Vol 9 (6) ◽  
pp. 891
Author(s):  
Imran Ashraf ◽  
Soojung Hur ◽  
Yongwan Park
Keyword(s):  
Radio Frequency Identification ◽  
Indoor Localization ◽  
Indoor Positioning ◽  
Location Based Services ◽  
Ultra Wideband ◽  
Current Status ◽  
Indoor Location ◽  
Use Of Data ◽  
Future Challenges ◽  
Smartphone Sensors

The last two decades have witnessed a rich variety of indoor positioning and localization research. Starting with Microsoft Research pioneering the fingerprint approach based RADAR, MIT’s Cricket, and then moving towards beacon-based localization are few among many others. In parallel, researchers looked into other appealing and promising technologies like radio frequency identification, ultra-wideband, infrared, and visible light-based systems. However, the proliferation of smartphones over the past few years revolutionized and reshaped indoor localization towards new horizons. The deployment of MEMS sensors in modern smartphones have initiated new opportunities and challenges for the industry and academia alike. Additionally, the demands and potential of location-based services compelled the researchers to look into more robust, accurate, smartphone deployable, and context-aware location sensing. This study presents a comprehensive review of the approaches that make use of data from one or more sensors to estimate the user’s indoor location. By analyzing the approaches leveraged on smartphone sensors, it discusses the associated challenges of such approaches and points out the areas that need considerable research to overcome their limitations.

scholarly journals INDOOR LOCALIZATION SOLUTION FOR GPS

2017 ◽  
Vol 5 (4RACEEE) ◽  
pp. 124-129
Author(s):  
Shreyanka B. Chougule ◽  
Sayed Abdulhayan
Keyword(s):  
Performance Improvement ◽  
Radio Frequency Identification ◽  
Indoor Environment ◽  
Review Paper ◽  
Indoor Localization ◽  
Multipath Propagation ◽  
Signal Attenuation ◽  
Improve Performance ◽  
Frequency Identification ◽  
Dense Urban Environment

GPS technology is used for positioning application and it is highly reliable and accurate when used outdoor. Due to multipath propagation, signal attenuation and blockage its performance is limited in indoor and dense urban environment. As a solution, technologies like Apple’s iBeacon, Radio-frequency identification (RFID), Ultrasonic and Wireless Fidelity (Wi-Fi) access points are used to improve performance in Indoor environment. We are having a look at all these technologies which are meant for GPS Indoor performance improvement in this review paper.

scholarly journals Passive Radio-Frequency Identification Tag-Based Indoor Localization in Multi-Stacking Racks for Warehousing

2020 ◽  
Vol 10 (10) ◽  
pp. 3623 ◽  
Author(s):  
Jaehun Park ◽  
Yong-Jeong Kim ◽  
Byung Kwon Lee
Keyword(s):  
Radio Frequency ◽  
Radio Frequency Identification ◽  
Large Scale ◽  
Indoor Localization ◽  
Electronic Device ◽  
Location Awareness ◽  
Indoor Location ◽  
Significant Difference ◽  
Frequency Identification ◽  
Passive Rfid

Radio-frequency identification (RFID) technology-based real-time indoor location awareness has been widely studied. In this paper, a passive RFID-based indoor inventory localization method for small and medium-sized enterprises (SMEs) is proposed to effectively manage their indoor inventory tracking in terms of the multi-stacking racking (MSR). To achieve this, we introduce a concept of reference tags and a calculation of measurement for the distance between the RFID reader and reference tag to improve the accuracy of the item location recognition. To illustrate the efficacy and applicability of the method, an empirical case study that applies it to an electronic device manufacturing company is conducted. It was noted that there was no significant difference in the location awareness rate of the proposed system compared with the existing active RFID-based methods. Also, it is demonstrated that the construction can be relatively inexpensive in terms of identifying the location of the items loaded in MSR and relatively narrow areas using a passive tag. This advantage makes it suitable for SMEs that have issues with large-scale facility investment, applying the method to compare the location difference between the registered location information in the inventory system and the actual location of the item in the rack.

RFID Indoor Localization Techniques

2018 ◽  
pp. 142-192 ◽  
Author(s):  
Yongtao Ma ◽  
Zheng Gao ◽  
Yang Zhao
Keyword(s):  
Radio Frequency Identification ◽  
Indoor Localization ◽  
Low Cost ◽  
Research Area ◽  
Uhf Rfid ◽  
Passive Uhf Rfid ◽  
Frequency Identification ◽  
Active Research ◽  
Passive Rfid ◽  
Key Techniques

Radio frequency identification (RFID) is a technique using two-way radio transmission pattern to transmit information through the device of interrogator (also called reader) and tag. It is considered to be one of the most popular techniques for internet of things (IOT). In this chapter, the authors study indoor localization techniques based on passive UHF RFID, which works around the frequency of 900MHz. Passive RFID has the advantage of reasonable reading distance, non-contact, easy deployment, and low cost. The tags do not need battery and it can harvest power through wireless charging. Due to those advantages, passive UHF RFID positioning has always been an active research area in the past few decades. This chapter discusses the key techniques in passive UHF RFID positioning, which include range-based, range-free, tag-based (device-based), tag-free (device-free), and improved positioning methods. All the techniques studied are suited to be implemented in RFID systems, each of which can be accommodated to a specific application scenario.

scholarly journals IKULDAS: An Improved kNN-Based UHF RFID Indoor Localization Algorithm for Directional Radiation Scenario

Sensors ◽  
2019 ◽  
Vol 19 (4) ◽  
pp. 968 ◽  
Author(s):  
Weiguang Shi ◽  
Jiangxia Du ◽  
Xiaowei Cao ◽  
Yang Yu ◽  
Yu Cao ◽  
...  
Keyword(s):  
Radio Frequency Identification ◽  
Nearest Neighbor ◽  
Indoor Localization ◽  
Rotation Angle ◽  
Localization Algorithm ◽  
Uhf Rfid ◽  
Estimation Model ◽  
K Value ◽  
Directional Radiation ◽  
Reader Antenna

Ultra high frequency radio frequency identification (UHF RFID)-based indoor localization technology has been a competitive candidate for context-awareness services. Previous works mainly utilize a simplified Friis transmission equation for simulating/rectifying received signal strength indicator (RSSI) values, in which the directional radiation of tag antenna and reader antenna was not fully considered, leading to unfavorable performance degradation. Moreover, a k-nearest neighbor (kNN) algorithm is widely used in existing systems, whereas the selection of an appropriate k value remains a critical issue. To solve such problems, this paper presents an improved kNN-based indoor localization algorithm for a directional radiation scenario, IKULDAS. Based on the gain features of dipole antenna and patch antenna, a novel RSSI estimation model is first established. By introducing the inclination angle and rotation angle to characterize the antenna postures, the gains of tag antenna and reader antenna referring to direct path and reflection paths are re-expressed. Then, three strategies are proposed and embedded into typical kNN for improving the localization performance. In IKULDAS, the optimal single fixed rotation angle is introduced for filtering a superior measurement and an NJW-based algorithm is advised for extracting nearest-neighbor reference tags. Furthermore, a dynamic mapping mechanism is proposed to accelerate the tracking process. Simulation results show that IKULDAS achieves a higher positioning accuracy and lower time consumption compared to other typical algorithms.

scholarly journals A Novel 3D PILA-Type UHF RFID Tag Antenna Mountable on Metallic Objects for IoT Indoor Localization

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Mondher Dhaouadi ◽  
Fethi Choubani
Keyword(s):  
Radio Frequency Identification ◽  
Indoor Localization ◽  
Equivalent Circuit Model ◽  
Dielectric Substrate ◽  
Anechoic Chamber ◽  
Optimized Design ◽  
Uhf Rfid ◽  
Copper Sheet ◽  
Antenna Structure ◽  
Rfid Tag

In this paper, a novel 3D planar inverted-L antenna (PILA) Ultrahigh Frequency (UHF) Radio Frequency Identification (RFID) tag mountable on metallic surfaces is proposed for the Internet of Things (IoT) indoor localization applications. The proposed tag antenna (45 mm × 82 mm × 4 mm or 0.137λ × 0.25λ × 0.012λ) is designed for mounting on metallic objects. The 3D PILA antenna is fabricated using a copper sheet of thickness 1 mm and air as the dielectric substrate in order to minimize costs for materials and realization. In the design, T-slot has been inserted in the radiating element for tuning of the tag’s resonance for achieving good matching with the chip. Also, a simple equivalent circuit model has been obtained to analyze the impedance of the 3D PILA. Based on the optimized design, the fabricated prototype has been measured in the anechoic chamber. The resonant frequency of the proposed tag is stable, and it is not affected much by the metallic object. The measurement results of the antenna prototype demonstrated a reasonable agreement with the simulation results, and a read range of 3.6 m was measured inside an anechoic chamber. Most importantly, in the building hallway, the proposed tag is able to achieve a maximum read distance of 18 m with a transmitted power of 31.5 dBm at 867 MHz when placed on metal. With the 3D PILA antenna structure, the proposed antimetal tag is a suitable solution that can be integrated into an indoor localization scenario.

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