LocHunt: Angle of Arrival Based Location Estimation in Harsh Multipath Environments

Rahman, Muhammed Tahsin; Tadayon, Navid; Han, S.; Valaee, Shahrokh

doi:10.1109/glocom.2018.8647870

Cited by 12 publications

(6 citation statements)

References 12 publications

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“…If it is a cluster, the amplitude samples have a Rayleigh distribution and if it is a single path the amplitudes should be more stable with a lognormal fading behavior. The number of paths in the cluster also governs the accuracy of delay of the path measurement using the phase of the received CSI stream [72]. Recently, these data streams have been paired with artificial intelligence (AI) algorithms to initiate research in several cyberspace applications.…”

Section: Characteristics Of Features Of Wi-fi Signals In Multipathmentioning

confidence: 99%

Evolution and Impact of Wi-Fi Technology and Applications: A Historical Perspective

Pahlavan

Krishnamurthy

2020

Int J Wireless Inf Networks

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The IEEE 802.11 standard for wireless local area networking (WLAN), commercially known as Wi-Fi, has become a necessity in our day-today life. Over a billion Wi-Fi access points connect close to hundred billion of IoT devices, smart phones, tablets, laptops, desktops, smart TVs, video cameras, monitors, printers, and other consumer devices to the Internet to enable millions of applications to reach everyone, everywhere. The evolution of Wi-Fi technology also resulted in the first commercial piloting of spread spectrum, high speed optical communications, OFDM, MIMO and mmWave pulse transmission technologies, which then became more broadly adopted by cellular phone and wireless sensor networking industries. The popularity and widespread Wi-Fi deployment in indoor areas further motivated innovation in opportunistic cyberspace applications that exploit the ubiquitous Wi-Fi signals. The RF signal radiated from Wi-Fi access points creates an "RF cloud" accessible to any Wi-Fi equipped device hosting or supporting these opportunistic applications. Wi-Fi positioning and location intelligence were the first popular opportunistic applications of Wi-Fi's RF cloud. Today, researchers are investigating opportunistic applications of Wi-Fi signals for gesture and motion detection as well as authentication and security. This paper provides a holistic overview of the evolution of Wi-Fi technology and its applications as the authors experienced it in the last few decades.

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Section: Characteristics Of Features Of Wi-fi Signals In Multipathmentioning

confidence: 99%

Evolution and Impact of Wi-Fi Technology and Applications: A Historical Perspective

Pahlavan

Krishnamurthy

2020

Int J Wireless Inf Networks

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“…ArrayTrack [32] employed eight antennas to improve the robustness of MUSIC algorithm in indoor environment. LocHunt algorithm [17] aggregated multiple AoA intersections and formed the empirical user location distribution. With 3 antennas at the receiver, SpotFi [8] estimated both the ToF and AoA based on MUSIC.…”

Section: Csi-based Indoor Localizationmentioning

confidence: 99%

Performance analysis of indoor localization based on channel state information ranging model

Gui

Xiao

Zhou

et al. 2020

Proceedings of the Twenty-First International Symposium on Theory, Algorithmic Foundations, and Protocol Design for Mobile Netw

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Due to robustness against multi-path effect, channel state information (CSI) of Orthogonal Frequency Division Multiplexing (OFDM) systems is supposed to provide accurate distance measurement for indoor localization. However, we find that the original CSI ranging model is biased, so the model cannot be used to directly derive Cramer-Rao lower bound (CRLB) of positioning error for CSI-ranging based localization scheme. In this paper we first analyze the estimation bias of the original CSI ranging model according to indoor wireless channel model. Then we propose a negative power summation ranging model which can be used as an unbiased ranging model for both Line-Of-Sight (LOS) and Non-LOS scenarios. Subsequently, based on the proposed model, we derive both the CRLB of ranging error and the CRLB of positioning error for CSI-ranging localization scheme. Through simulation we validate the bias of the original ranging model and the approximately zero bias of our proposed ranging model. Through comprehensive experiments in different indoor scenarios, localization errors by different ranging models are compared to the CRLB, meanwhile our proposed ranging model is demonstrated to have better ranging and localization accuracy than the original ranging model.

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“…where a(τj mp ) = 1, e −2πi∆f τ jmp , · · · , e −2πi(Nnz−1)∆f τ jmp T γ = γ1 · · · γN mp T γj mp = βj mp e −2πif 0 τ jmp and n = [n1 · · · nN nz ] T (20) Assuming independence of noise n from the signal γ in (19) and N nz > N mp , the covariance matrix ofcsi is given by Rc si = Rĉ si + R n where the noise-free CSI covariance matrix Rĉ si = AR γ A H is only of rank N mp (rank deficient). Therefore, the largest N mp eigenvalues in decomposition Rc si = EΛE H are due to signal (multipath arrivals) and the rest are due to noise.…”

Section: A Spectral-domain Music Algorithmmentioning

confidence: 99%

“…Therefore, it can be used to perform range (timebased or power-based) and angle-of-arrival estimation. When it comes down to implementation, while CSI-based localization with AoA achieved promising outcomes [2]- [4], [19], using CSI to estimate time-of-flight (ToF) measurement has either not been pursued or led to inconsistent results [2]. To our knowledge, the studies that do consider phase-based ranging all use software-defined radio (SDR), an open-source and finetuned platform that is expensive to acquire and so is unscalable.…”

Section: Introductionmentioning

confidence: 99%

Decimeter Ranging With Channel State Information

Tadayon

Rahman

Han

et al. 2019

IEEE Trans. Wireless Commun.

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This paper aims at the problem of time-of-flight (ToF) estimation using channel state information (CSI) obtainable from commercialized MIMO-OFDM WLAN receivers. It was often claimed that the CSI phase is contaminated with errors of known and unknown natures rendering ToF-based positioning difficult. To search for an answer, we take a bottom-up approach by first understanding CSI, its constituent building blocks, and the sources of error that contaminate it. We then model these effects mathematically. The correctness of these models is corroborated based on the CSI collected in extensive measurement campaign including radiated, conducted and chamber tests. Knowing the nature of contaminations in CSI phase and amplitude, we proceed with introducing pre-processing methods to clean CSI from those errors and make it usable for range estimation. To check the validity of proposed algorithms, the MUSIC superresolution algorithm is applied to post-processed CSI to perform range estimates. Results substantiate that median accuracy of 0.6m, 0.8m, and 0.9m is achievable in highly multipath line-ofsight environment where transmitter and receiver are 5m, 10m, and 15m apart.

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LocHunt: Angle of Arrival Based Location Estimation in Harsh Multipath Environments

Cited by 12 publications

References 12 publications

Evolution and Impact of Wi-Fi Technology and Applications: A Historical Perspective

Evolution and Impact of Wi-Fi Technology and Applications: A Historical Perspective

Performance analysis of indoor localization based on channel state information ranging model

Decimeter Ranging With Channel State Information

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