A fast and accurate calibration algorithm for real-time locating systems based on the received signal strength indication

Narzullaev, Anvar; Park, Yongwan; Yoo, Kook-Yeol; Yu, Jae-Hwang

doi:10.1016/j.aeue.2010.03.012

Cited by 50 publications

(17 citation statements)

References 7 publications

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“…However, it is difficult to find an accurate traditional propagation model because of the indoor complex propagation environments. Narzullaev et al [20] and our research team [22] proposed new propagation models to improve the RSS prediction accuracy, and achieved an acceptable level of localization performance.…”

Section: Scalabilitymentioning

confidence: 99%

“…Whereas the database reconstruction can be realized only when the sensing matrix satisfies the restricted isometric property (RIP) condition which is difficult to get such matrix physically. Other approaches are based on the propagation models such as one-slope model (OSM) [20] or multi wall model (MWM) [21]. Those approaches use the propagation model to predict the RSS values to further recover the entire fingerprint database.…”

Section: Scalabilitymentioning

confidence: 99%

See 1 more Smart Citation

Overview of received signal strength based fingerprinting localization in indoor wireless LAN environments

Ding

Zhang

et al. 2013

2013 5th IEEE International Symposium on Microwave, Antenna, Propagation and EMC Technologies for Wireless Communications

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In recent years, indoor localization technique is anticipated to play an increasingly important role in our society. In general, the indoor localization techniques include trilateral, triangulation and fingerprinting localization. As an important alternative, fingerprinting localization techniques are extensively studied and applied in the existing localization systems. This paper presents an overview of the fingerprinting localization system based on the received signal strength (RSS) in indoor wireless LAN (WLAN) environments. In particular, we describe the structure of localization system and then analyze the challenges that most existing research works try to deal with. Corresponding solutions and several pattern matching algorithms are also presented. Furthermore, we demonstrate a comparative study of existing fingerprinting localization systems and address the possible directions of future research in indoor localization techniques.

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Section: Scalabilitymentioning

confidence: 99%

Section: Scalabilitymentioning

confidence: 99%

Overview of received signal strength based fingerprinting localization in indoor wireless LAN environments

Ding

Zhang

et al. 2013

2013 5th IEEE International Symposium on Microwave, Antenna, Propagation and EMC Technologies for Wireless Communications

View full text Add to dashboard Cite

show abstract

“…This approach, however, will increase the computational time. There are also other similar works [15,16] trying to use Wi-Fi RSS in the fingerprinting process.…”

Section: Related Workmentioning

confidence: 99%

Indoor Location Sensing with Invariant Wi-Fi Received Signal Strength Fingerprinting

Husen

Lee

2016

Sensors

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A method of location fingerprinting based on the Wi-Fi received signal strength (RSS) in an indoor environment is presented. The method aims to overcome the RSS instability due to varying channel disturbances in time by introducing the concept of invariant RSS statistics. The invariant RSS statistics represent here the RSS distributions collected at individual calibration locations under minimal random spatiotemporal disturbances in time. The invariant RSS statistics thus collected serve as the reference pattern classes for fingerprinting. Fingerprinting is carried out at an unknown location by identifying the reference pattern class that maximally supports the spontaneous RSS sensed from individual Wi-Fi sources. A design guideline is also presented as a rule of thumb for estimating the number of Wi-Fi signal sources required to be available for any given number of calibration locations under a certain level of random spatiotemporal disturbances. Experimental results show that the proposed method not only provides 17% higher success rate than conventional ones but also removes the need for recalibration. Furthermore, the resolution is shown finer by 40% with the execution time more than an order of magnitude faster than the conventional methods. These results are also backed up by theoretical analysis.

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“…In the past, a great amount of work has been done on estimating the locations of objects using different techniques and technologies [3], [5][6][7][8][9][10][11]. The main focus of these studies is to improve the accuracy and granularity of indoor localization systems, whereas less attention has been given to understand the behavior of the signals and to analyze it.…”

Section: Introductionmentioning

confidence: 99%

An Experimental Study on the Behavior of Received Signal Strength in Indoor Environment

Ullah

Custodio

Shah

et al. 2013

2013 11th International Conference on Frontiers of Information Technology

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Due to widespread availability of WiFi networks in buildings, indoor location based systems become a reality. To provide indoor location based services (LBS), finding the current location of a human, a computer, a mobile device or equipment such as a small UAV (like Quadcopter) is of great interest. The most prominent method for this purpose is the received signal strength (RSS)-based location from WiFi Access Points (APs) inside a building. Considerable amount of research is carried out in estimating current location and providing different services based on different wireless technologies. On the other hand, little attention has been paid to study and analyze the behavior of the received signal strength itself. It is challenging because the intensity of signal can change very frequently due to environmental features like topology, temperature, interaction with objects etc. In this paper, we study the behavior of WiFi signals in an indoor environment for RSS based localization by analyzing signals from three different access points by using triangulation technique. Our method is based on fingerprinting method. The experimental results reveal that the behavior of signal changes very frequently. The results lead us to the conclusion that understanding signals behavior is important before estimating current location and providing different LBS.

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A fast and accurate calibration algorithm for real-time locating systems based on the received signal strength indication

Cited by 50 publications

References 7 publications

Overview of received signal strength based fingerprinting localization in indoor wireless LAN environments

Overview of received signal strength based fingerprinting localization in indoor wireless LAN environments

Indoor Location Sensing with Invariant Wi-Fi Received Signal Strength Fingerprinting

An Experimental Study on the Behavior of Received Signal Strength in Indoor Environment

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