Indoor Multipath Assisted Angle of Arrival Localization

Wielandt, Stijn; Strycker, Lieven De

doi:10.3390/s17112522

Cited by 71 publications

(50 citation statements)

References 55 publications

(75 reference statements)

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“…As a result, short-range radio waves such as Wi-Fi are actively studied as alternative methods. In these methods, a target device receives a signal from each AP (access point) with known position of the AP, detects signal propagation distance and AoA (angle of arrival) from information, such as signal strength/phase, and on this basis computes its own position [13][14][15][16]. In addition, device-free methods [17][18][19][20] for detecting a person without any wearable device are also proposed, which monitor the changes in signal reception status between pairs of preset devices.…”

Section: Indoor Positioning Via Radio Wavesmentioning

confidence: 99%

Radiation Angle Estimation and High-Precision Pedestrian Positioning by Tracking Change of Channel State Information

Komamiya

Tang

Obana

2020

Sensors

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P2V (pedestrian-to-vehicle) communication, in which a pedestrian’s mobile device notifies its position to nearby vehicles in order to prevent pedestrian accidents, has attracted much research interest recently, but its performance largely depends on the precision of pedestrians’ positioning. Pedestrian positioning is generally performed by using GPS (Global Positioning System), and its precision may greatly degrade in urban canyons. To improve positioning precision of pedestrians, it was proposed that vehicles around pedestrians be used as anchors beside satellites. In this method, a pedestrian device overhears V2V (vehicle-to-vehicle) communication signals which carry the vehicle position and calculates a pedestrian’s position using pedestrian–vehicle distance/angle information estimated from CSI (channel state information) of the V2V signals. However, angle estimation typically depends on the number of antennas of the pedestrian device. In this paper, we propose a new method to estimate signal radiation angle by tracking temporal change of CSI caused by vehicle movement during signal transmission and investigate its application to precise pedestrian positioning. Three-dimensional ray tracing simulations confirm that compared to the base method using eight antennas, the proposed method with a single antenna reduces average angle error from 13 degrees to 3.9 degrees, and reduces average positioning error from 2.49 m to 0.78 m.

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Section: Indoor Positioning Via Radio Wavesmentioning

confidence: 99%

Radiation Angle Estimation and High-Precision Pedestrian Positioning by Tracking Change of Channel State Information

Komamiya

Tang

Obana

2020

Sensors

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“…Tomic et al [29], used both the RSSI value and the AoA to locate and track a wireless emitting mobile device. Wielandt et al [30] proposed an AoA scheme in which spatial smoothing of the reference vectors is applied. This approach was empirically evaluated in LOS and non-LOS (NLOS) scenarios.…”

Section: Related Workmentioning

confidence: 99%

Three-Dimensional Empirical AoA Localization Technique for Indoor Applications

Alma'aitah

Alsaify

Bani-Hani

2019

Sensors

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Small and pervasive devices have been increasingly used to identify and track objects automatically. Consequently, several low-cost localization schemes have been proposed in the literature based on angle of arrival (AoA), time difference of arrival (TDoA), received signal strength indicator (RSSI) or their combinations. In this paper, we propose a three-dimensional empirical AoA localization (TDEAL) technique for battery-powered devices. The proposed technique processes the AoA measurements at fixed reader nodes to estimate the locations of the tags. The proposed technique provides localization accuracy that mitigates non-linear empirical errors in AoA measurements. We utilize two omni-directional antenna arrays at each fixed reader node to estimate the location vector. With multiple location estimations from different fixed reader nodes, each estimated location is assigned a weight that is inversely proportional to the AoA phase-difference error. Furthermore, the actual AoA parabolic formula of the location is approximated to a cone to simplify the location calculation process. The proposed localization technique has a low hardware cost, low computational requirements, and precise location estimates. Based on the performance evaluation, significant location accuracy is achieved by TDEAL; where, for instance, an average error margin of less than 13 cm is achieved using 10 readers in an area of 10 m × 10 m . TDEAL can be utilized to provide reference points when integrated with a relative (e.g., inertial navigation systems) localization systems.

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“…It is well known that a location can be estimated from various measurement models such as distance-based and orientation-based measurement models [6,7]. Generally, there are four types of measurements used for Wi-Fi and smartphone-based indoor positioning: time of arrival (ToA) [8,9], time difference of arrival (TDoA) [10,11], angle of arrival (AoA) [12], and received signal strength indicator (RSSI) based models [13][14][15]. The RSSI-based model is more popular than the other three [16,17] and therefore is employed for SLDC.…”

Section: Measurement Modelmentioning

confidence: 99%

A New Approach for Wi-Fi-Based People Localization in a Long Narrow Space

Gao

Tang

Bai

2019

Wireless Communications and Mobile Computing

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Wi-Fi-based positioning technology has been recognized as an effective technology for indoor positioning along with the rapid development and application of smartphones. One of its typical applications is localizing people in large public areas such as shopping malls, schools, and airports. A common and critical task from such applications is localizing people in long narrow spaces such as a long corridor which is considered as the most frequent place where people activities take place. Generally, the geographical distribution of Wi-Fi access points (APs) in long spaces is poor for localizing people since normally less than 3 APs are connected to a smartphone. In addition, all these APs are normally mounted along a straight line; hence, it is difficult to track people using traditional positioning algorithms such as trilateration and fingerprinting. To address this issue, a new approach called same-line-dual-connection (SLDC) was developed to estimate user locations with a good positioning accuracy, particularly for long narrow spaces where only limited Wi-Fi connections are available. The SLDC approach integrates geometry principle with positioning theories and machine learning ideas. The test outcome has shown that the SLDC approach produced a promising result, and a mean positioning accuracy of 1.60 m was achieved.

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Indoor Multipath Assisted Angle of Arrival Localization

Cited by 71 publications

References 55 publications

Radiation Angle Estimation and High-Precision Pedestrian Positioning by Tracking Change of Channel State Information

Radiation Angle Estimation and High-Precision Pedestrian Positioning by Tracking Change of Channel State Information

Three-Dimensional Empirical AoA Localization Technique for Indoor Applications

A New Approach for Wi-Fi-Based People Localization in a Long Narrow Space

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