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Fingerprinting-based positioning significantly improves the indoor localization performance in non-line-of-sight-dominated areas. However, its deployment and maintenance is cost-intensive as it needs ground-truth reference systems for both…
This paper proposes passive WiFi indoor localization. Instead of using WiFi signals received by mobile devices as fingerprints, we use signals received by routers to locate the mobile carrier. Consequently, software installation on the…
With the growing integration of location based services (LBS) such as GPS in mobile devices, indoor position systems (IPS) have become an important role for research. There are several IPS methods such as AOA, TOA, TDOA, which use…
Traditional global positioning systems often underperform indoors, whereas Wi-Fi has become an effective medium for various radio sensing services. Specifically, utilizing channel state information (CSI) from Wi-Fi networks provides a…
Indoor localization is getting increasing demands for various cutting-edged technologies, like Virtual/Augmented reality and smart home. Traditional model-based localization suffers from significant computational overhead, so fingerprint…
Widespread adoption of indoor positioning systems based on WiFi fingerprinting is at present hindered by the large efforts required for measurements collection during the offline phase. Two approaches were recently proposed to address such…
With expeditious development of wireless communications, location fingerprinting (LF) has nurtured considerable indoor location based services (ILBSs) in the field of Internet of Things (IoT). For most pattern-matching based LF solutions,…
Accurate and robust wireless localization is a key enabler for a wide range of mobile computing applications. Fingerprint-based localization using channel state information (CSI) has attracted significant attention due to its high accuracy…
Location tracking systems are increasingly becoming the focus of research in the field of Wireless Sensor Network (WSN). Received Signal Strength (RSS)-based localization systems are at the forefront of tracking research applications. Radio…
Channel state information (CSI)-based fingerprinting via neural networks (NNs) is a promising approach to enable accurate indoor and outdoor positioning of user equipments (UEs), even under challenging propagation conditions. In this paper,…
Fingerprint-based localization improves the positioning performance in challenging, non-line-of-sight (NLoS) dominated indoor environments. However, fingerprinting models require an expensive life-cycle management including recording and…
Indoor position technology has become one of the research highlights in the Internet of Things (IoT), but there is still a lack of universal, low-cost, and high-precision solutions. This paper conducts research on indoor position technology…
With the fast growing demand of location-based services in indoor environments, indoor positioning based on fingerprinting has attracted a lot of interest due to its high accuracy. In this paper, we present a novel deep learning based…
Indoor localization plays a vital role in the era of the IoT and robotics, with WiFi technology being a prominent choice due to its ubiquity. We present a method for creating WiFi fingerprinting datasets to enhance indoor localization…
Wearable and IoT devices requiring positioning and localisation services grow in number exponentially every year. This rapid growth also produces millions of data entries that need to be pre-processed prior to being used in any indoor…
In recent years WiFi became the primary source of information to locate a person or device indoor. Collecting RSSI values as reference measurements with known positions, known as WiFi fingerprinting, is commonly used in various positioning…
Accurate localization in indoor environments is a challenge due to the Non Line of Sight (NLoS) nature of the signaling. In this paper, we explore the use of AI/ML techniques for positioning accuracy enhancement in Indoor Factory (InF)…
The paper presents a novel Wi-Fi fingerprinting system that uses Channel State Information (CSI) data for fine-grained pedestrian localization. The proposed system exploits the frequency diversity and spatial diversity of the features…
Modern techniques in the Internet of Things or autonomous driving require more accuracy positioning ever. Classic location techniques mainly adapt to outdoor scenarios, while they do not meet the requirement of indoor cases with multiple…
Modern indoor localization techniques are essential to overcome the weak GPS coverage in indoor environments. Recently, considerable progress has been made in Channel State Information (CSI) based indoor localization with signal…