An Experimental Comparison of RSSI-Based Indoor Localization Techniques Using ZigBee Technology

Fahama, Hassoon Salman; Ansari-Asl, Karim; Kavian, Yousef S.; Soorki, Mehdi Naderi

doi:10.1109/access.2023.3305396

Cited by 14 publications

(5 citation statements)

References 57 publications

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“…When only a single measurement is considered as the final result, the maximum error exceeds 6 m. By adopting the median of 16 consecutive measurements to cover all available frequency channels, the maximum error drops to below 0.65 m. The proposed localization system achieves high accuracy using only a single node with a known location, compared to other techniques that require at least three anchors [ 40 ]. Acquiring many measurements is time-consuming for mobile device scenarios where a high update rate is essential for accurate device tracking.…”

Section: Experiments Results and Analysismentioning

confidence: 99%

“…These protocols are based on the IEEE 802.15.4 standard and its TSCH protocol, added in the 2016 amendment [ 8 ]. There have been several studies on applying the IEEE 802.15.4 standard and related IoT technologies for localization, primarily using the RSSI metric for proximity-based and fingerprint-based localization methods [ 20 , 40 ]. Although the accuracy of RSSI-based localization systems is continuously improving with the development of ML algorithms [ 41 ], the main drawback remains.…”

Section: Related Workmentioning

confidence: 99%

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Distance- and Angle-Based Hybrid Localization Integrated in the IEEE 802.15.4 TSCH Communication Protocol

Morano,

Simončič,

Kocevska

et al. 2024

Sensors

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Accurate localization of devices within Internet of Things (IoT) networks is driven by the emergence of novel applications that require context awareness to improve operational efficiency, resource management, automation, and safety in industry and smart cities. With the Integrated Localization and Communication (ILAC) functionality, IoT devices can simultaneously exchange data and determine their position in space, resulting in maximized resource utilization with reduced deployment and operational costs. Localization capability in challenging scenarios, including harsh environments with complex geometry and obstacles, can be provided with robust, reliable, and energy-efficient communication protocols able to combat impairments caused by interference and multipath, such as the IEEE 802.15.4 Time-Slotted Channel Hopping (TSCH) protocol. This paper presents an enhancement of the TSCH protocol that integrates localization functionality along with communication, improving the protocol’s operational capabilities and setting a baseline for monitoring, automation, and interaction within IoT setups in physical environments. A novel approach is proposed to incorporate a hybrid localization by integrating Direction of Arrival (DoA) estimation and Multi-Carrier Phase Difference (MCPD) ranging methods for providing DoA and distance estimates with each transmitted packet. With the proposed enhancement, a single node can determine the location of its neighboring nodes without significantly affecting the reliability of communication and the efficiency of the network. The feasibility and effectiveness of the proposed approach are validated in a real scenario in an office building using low-cost proprietary devices, and the software incorporating the solution is provided. The experimental evaluation results show that a node positioned in the center of the room successfully estimates both the DoA and the distance to each neighboring node. The proposed hybrid localization algorithm demonstrates an accuracy of a few tens of centimeters in a two-dimensional space.

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Section: Experiments Results and Analysismentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Distance- and Angle-Based Hybrid Localization Integrated in the IEEE 802.15.4 TSCH Communication Protocol

Morano,

Simončič,

Kocevska

et al. 2024

Sensors

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show abstract

“…In the online positioning phase, the mobile device collects current RSSI data and compares it with the fingerprint database. Based on the matching results, the closest location coordinates are output [5]. The precision of the positioning outcomes is contingent on the efficacy of the matching algorithm.…”

Section: Related Workmentioning

confidence: 99%

Indoor location strategy based on the fusion of RSSI and RTT based on multilayer perceptron

yang,

Fei,

2024

Fourth International Conference on Sensors and Information Technology (ICSI 2024)

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In order to solve the problem of low positioning accuracy of single RSSI feature location algorithm, the multi-layer perceptron (MLP) fingerprint matching algorithm is enhanced through a combination with Round-Trip Time (RTT). The traditional MLP fingerprint matching algorithm based on multi-layer perceptron only uses the feature of RSSI, and the obstacles in the location space are easy to interfere with the RSSI signal and impact the accuracy of positioning. In order to solve the above problems, the MLP fingerprint matching algorithm based on multilayer perceptron is improved in this paper，RTT is added as the second eigenvalue, regression is used to predict the distance of unknown nodes from the Access Point (AP) as well as the input sequences of Received Signal Strength Indicator (RSSI) and Round-Trip Time (RTT). The predicted outcomes are then subjected to a weighted fusion process, following which the coordinates of the sample nodes are determined through mathematical calculations based on the sample output. The improved algorithm solves the interference problem at the same time. The location accuracy is further improved.

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“…The transmission power of Zigbee [26] and the channel selection in the indoor environment are also particularly important. The size of the transmission power determines the length of the communication distance and the penetration ability, and the channel selection determines the network performance and stability.…”

Section: Zigbee Device Parameter Settingsmentioning

confidence: 99%

A Combined Filtering Method for ZigBee Indoor Distance Measurement

Wei,

Zhou

2024

Sensors

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Indoor distance measurement technology utilizing Zigbee’s Received Signal Strength Indication (RSSI) offers cost-effective and energy-efficient advantages, making it widely adopted for indoor distance measurement applications. However, challenges such as multipath effects, signal attenuation, and signal blockage often degrade the accuracy of distance measurements. Addressing these issues, this study proposes a combined filtering approach integrating Kalman filtering, Dixon’s Q-test, Gaussian filtering, and mean filtering. Initially, the method evaluates Zigbee’s transmission power, channel, and other parameters, analyzing their impact on RSSI values. Subsequently, it fits a signal propagation loss model based on actual measured data to understand the filtering algorithm’s effect on distance measurement error. Experimental results demonstrate that the proposed method effectively improves the conversion relationship between RSSI and distance. The average distance measurement error, approximately 0.46 m, substantially outperforms errors derived from raw RSSI data. Consequently, this method offers enhanced distance measurement accuracy, making it particularly suitable for indoor positioning applications.

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An Experimental Comparison of RSSI-Based Indoor Localization Techniques Using ZigBee Technology

Cited by 14 publications

References 57 publications

Distance- and Angle-Based Hybrid Localization Integrated in the IEEE 802.15.4 TSCH Communication Protocol

Distance- and Angle-Based Hybrid Localization Integrated in the IEEE 802.15.4 TSCH Communication Protocol

Indoor location strategy based on the fusion of RSSI and RTT based on multilayer perceptron

A Combined Filtering Method for ZigBee Indoor Distance Measurement

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