Indoor Fingerprinting Localization and Tracking System Using Particle Swarm Optimization and Kalman Filter

Ding, Genming; Zhang, Tan; Wu, Jinsong; Zeng, Jinshan; Zhang, Lingwen

doi:10.1587/transcom.e98.b.502

Cited by 46 publications

(24 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…More advanced solutions complement Wi-Fi fingerprint matching with Bayesian filters such as Kalman and particle filters to improve accuracy. For instance, the system presented in [81] establishes a Bayesianrule based objective function and then applies the particle swarm optimization technique to identify the optimal solution (i.e., estimated location). Subsequently, the Kalman filter is used to update the initial location and track the mobile user, thus mitigating the estimation error.…”

Section: B Fingerprint Matchingmentioning

confidence: 99%

“…Hence, these approaches may fail in sparse anchor scenarios. Moreover, the distance estimates to the reliable anchors may include large errors, which means their Wi-Dist uses a convex-optimization formulation and fuses noisy fingerprints Applicable to various sensors and wireless fingerprints, with uncertain mutual distances given by their bounds up to 40% better accuracy than state-of-the-art [80] Integration of human-centric collaboration to improve accuracy by positive Robust with respect to malicious feedback, quickly and negative user feedback on their estimated locations self-correcting based on subsequent helpful feedback [81] Bayesian-rule based objective function and particle swarm optimization Kalman filter updates the initial location and tracks technique combined with Kalman filter for user tracking the user, thus mitigating the estimation error [82] Non-parametric information filter for Wi-Fi RSS fingerprints and sensor Sensitive to sensor drifting readings combined with RP selection, AP selection, and outlier detection [83] Bayesian filter predicts location from motion sensors and updates it with Sensitive to sensor drifting Wi-Fi fingerprint matching formulated as a compressive sensing problem [85] Conditional entropy metric as a dynamic measure of the uncertainty Low entropy values are correlated with small errors, associated to each position estimate high values may indicate small or large errors [86] Extensive analysis for the causes of large errors in Wi-Fi fingerprint Some large errors may be due to the geometry matching with the aim to dynamically estimate the positioning error of the space and access points placement [87] Parametric pathloss model for the GP mean and a non-parametric Using 23 RPs similar accuracy was achieved with covariance function to create the RSS radiomap with a few training data over 230 RPs for an office space of 2500 m 2 [88] Empirical Regional Propagation Model to construct the RSS radiomap Better prediction of RSS values than existing models, from sparse fingerprints through affinity propagation clustering 50% workload reduction for fingerprint data collection…”

Section: Range-free Localization In Wireless Sensor Networkmentioning

confidence: 99%

See 1 more Smart Citation

A Survey of Enabling Technologies for Network Localization, Tracking, and Navigation

Laoudias¹,

Moreira

Kim

et al. 2018

IEEE Commun. Surv. Tutorials

369

171

View full text Add to dashboard Cite

Abstract-Location information for events, assets, and individuals, mostly focusing on two dimensions so far, has triggered a multitude of applications across different verticals, such as consumer, networking, industrial, health care, public safety, and emergency response use cases. To fully exploit the potential of location awareness and enable new advanced location-based services, localization algorithms need to be combined with complementary technologies including accurate height estimation, i.e., three dimensional location, reliable user mobility classification, and efficient indoor mapping solutions. This survey provides a comprehensive review of such enabling technologies. In particular, we present cellular localization systems including recent results on 5G localization, and solutions based on Wireless Local Area Networks (WLAN), highlighting those that are capable of computing 3D location in multi-floor indoor environments. We overview range-free localization schemes, which have been traditionally explored in Wireless Sensor Networks (WSN) and are nowadays gaining attention for several envisioned Internet of Things (IoT) applications. We also present user mobility estimation techniques, particularly those applicable in cellular networks, that can improve localization and tracking accuracy. Regarding the mapping of physical space inside buildings for aiding tracking and navigation applications, we study recent advances and focus on smartphone-based indoor Simultaneous Localization and Mapping (SLAM) approaches.The survey concludes with service availability and system scalability considerations, as well as security and privacy concerns in location architectures, discusses the technology roadmap, and identifies future research directions.

show abstract

Section: B Fingerprint Matchingmentioning

confidence: 99%

Section: Range-free Localization In Wireless Sensor Networkmentioning

confidence: 99%

A Survey of Enabling Technologies for Network Localization, Tracking, and Navigation

Laoudias¹,

Moreira

Kim

et al. 2018

IEEE Commun. Surv. Tutorials

369

171

View full text Add to dashboard Cite

show abstract

“…They have their own favourite places to visit and some places of interest may attract many IDEN UEs. Relying on stateof-the-art localisation techniques [296], [297], the mobility traces of the UEs can be acquired by the network operator. As a result, we have to firstly understand the UEs' geographic preferences, when we deploy IDEN in a specific area.…”

Section: Socially Aware Placement Of Iden Stationsmentioning

confidence: 99%

Integrated Data and Energy Communication Network: A Comprehensive Survey

Yang

Wen

et al. 2018

IEEE Commun. Surv. Tutorials

135

View full text Add to dashboard Cite

In order to satisfy the power thirsty of communication devices in the imminent 5G era, wireless charging techniques have attracted much attention both from the academic and industrial communities. Although the inductive coupling and magnetic resonance based charging techniques are indeed capable of supplying energy in a wireless manner, they tend to restrict the freedom of movement. By contrast, RF signals are capable of supplying energy over distances, which are gradually inclining closer to our ultimate goal -charging anytime and anywhere. Furthermore, transmitters capable of emitting RF signals have been widely deployed, such as TV towers, cellular base stations and Wi-Fi access points. This communication infrastructure may indeed be employed also for wireless energy transfer (WET). Therefore, no extra investment in dedicated WET infrastructure is required. However, allowing RF signal based WET may impair the wireless information transfer (WIT) operating in the same spectrum. Hence, it is crucial to coordinate and balance WET and WIT for simultaneous wireless information and power transfer (SWIPT), which evolves to Integrated Data and Energy communication Networks (IDENs). To this end, a ubiquitous IDEN architecture is introduced by summarising its natural heterogeneity and by synthesising a diverse range of integrated WET and WIT scenarios. Then the inherent relationship between WET and WIT is revealed from an information theoretical perspective, which is followed by the critical appraisal of the hardware enabling techniques extracting energy from RF signals. Furthermore, the transceiver design, resource allocation and user scheduling as well as networking aspects are elaborated on. In a nutshell, this treatise can be used as a handbook for researchers and engineers, who are interested in enriching their knowledge base of IDENs and in putting this vision into practice.Index Terms-RF signals, wireless energy transfer (WET), wireless information transfer (WIT), simultaneous wireless information and power transfer (SWIPT), wireless powered communication networks (WPCNs), integrated data and energy communication networks (IDENs).an increasing research interest from both the electronic and communication engineering communities. C. Near-field Wireless Energy TransferAt the time of writing, resonant inductive coupling [35] and magnetic resonance coupling [36] emerge as flexible wireless charging options for electronic devices in the nearfield. Resonant inductive coupling based wireless charging relies on the magnetic coupling that delivers electrical energy between two coils tuned to resonate at the same frequency. This technique has already been commercialised for small electronic appliances [37], such as mobile phones, electric toothbrushes and smart watches etc. However, the coupling coils only support near-field wireless power transfer over a distance spanning from a few millimetres to a few centimetres [38], while achieving a power transfer efficiency as high as 56.7%, when operating at a frequency of 508 kHz [...

show abstract

“…The spatial distributed CPS nodes also can be used to analyze location information. The paper [190] proposed an efficient indoor positioning based on a new empirical propagation model using fingerprinting sensors, called regional propagation model (RPM), which is based on the cluster based propagation model theory, and then the paper [191] used particle swarm optimization (PSO) to estimate the location information via Kalman filter to update the initial estimated location.…”

Section: Spatial-temporal Analyticsmentioning

confidence: 99%

“…to prolong WSN lifetime. CPS based big data may also support localization applications [190], [191].…”

Section: City Managementmentioning

confidence: 99%

Big Data Meet Cyber-Physical Systems: A Panoramic Survey

et al. 2018

Self Cite

View full text Add to dashboard Cite

The world is witnessing an unprecedented growth of cyber-physical systems (CPS), which are foreseen to revolutionize our world via creating new services and applications in a variety of sectors such as environmental monitoring, mobilehealth systems, intelligent transportation systems and so on. The information and communication technology (ICT) sector is experiencing a significant growth in data traffic, driven by the widespread usage of smartphones, tablets and video streaming, along with the significant growth of sensors deployments that are anticipated in the near future. It is expected to outstandingly increase the growth rate of raw sensed data. In this paper, we present the CPS taxonomy via providing a broad overview of data collection, storage, access, processing and analysis. Compared with other survey papers, this is the first panoramic survey on big data for CPS, where our objective is to provide a panoramic summary of different CPS aspects. Furthermore, CPS require cybersecurity to protect them against malicious attacks and unauthorized intrusion, which become a challenge with the enormous amount of data that is continuously being generated in the network. Thus, we also provide an overview of the different security solutions proposed for CPS big data storage, access and analytics. We also discuss big data meeting green challenges in the contexts of CPS.

show abstract

Indoor Fingerprinting Localization and Tracking System Using Particle Swarm Optimization and Kalman Filter

Cited by 46 publications

References 22 publications

A Survey of Enabling Technologies for Network Localization, Tracking, and Navigation

A Survey of Enabling Technologies for Network Localization, Tracking, and Navigation

Integrated Data and Energy Communication Network: A Comprehensive Survey

Big Data Meet Cyber-Physical Systems: A Panoramic Survey

Contact Info

Product

Resources

About