A Novel Statistical AOA Model Pertinent to Indoor Geolocation

Akgül, Ferit Ozan; Pahlavan, Kaveh

doi:10.4236/jgis.2010.21009

Cited by 3 publications

(3 citation statements)

References 10 publications

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“…Recently, much work has been conducted to model the AoA distribution in different multipath environments. AoA measurements by [9,10] in an indoor communication channel revealed that the AS has a Laplacian distribution. Another common angular spread profile includes uniform and Gaussian PDFs [7,11].…”

Section: Introductionmentioning

confidence: 99%

Spatial Characterization of GNSS Multipath Channels

Keshvadi

Broumandan

2012

International Journal of Antennas and Propagation

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There is a growing interest in detecting and processing Global Navigation Satellite System (GNSS) signals in indoors and urban canyons by handheld devices. To overcome the signal attenuation problem in such adverse fading environments, long coherent integration is normally used. Moving the antenna arbitrarily while collecting signals is generally avoided as it temporally decorrelates the signals and limits the coherent integration gain. This decorrelation is a function of the antenna displacement and geometry of reflectors and angle of arrival of the received signal. Hence, to have an optimum receiver processing strategy it is crucial to characterize the multipath fading channel parameters. Herein, Angle of Arrival (AoA) and Angle Spread (AS) along with signal spatial correlation coefficient and fading intensity in GNSS multipath indoor channels are defined and quantified theoretically and practically. A synthetic uniform circular array utilizing a right-hand circular polarized (RHCP) antenna has been used to measure the spatial characteristics of indoor GNSS fading channels. Furthermore, rotating effect of a circular polarized antenna on the synthetic array processing and AoA estimation has been characterized. The performance of the beamforming technique via array gain is also assessed to explore the advantages and limitations of beamforming in fading conditions.

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Section: Introductionmentioning

confidence: 99%

Spatial Characterization of GNSS Multipath Channels

Keshvadi

Broumandan

2012

International Journal of Antennas and Propagation

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“…We used the average distance as the threshold of the distance determination for the stay point in the first step. The distance threshold was determined by the average distance between two adjacent points in the customer trajectory dataset, as shown in Equations (6) and (7) as follows:…”

Section: Distance Threshold Determinationmentioning

confidence: 99%

“…Therefore, research on indoor 2 of 22 positioning is currently a popular topic. Indoor positioning technology provides the TOA (time difference of arrival) based on the electromagnetic wave propagation time positioning technology [5,6], the AOA (angle of arrival) based on the incidence angle of electromagnetic waves [7,8], the TDOA based on the arrival of the frequency of magnetic wave positioning technology [9,10], signal strength based on RSSI (received signal strength indication) positioning technology [11,12], and the AP (access point) sensor signal strength based on positioning technology [13,14].…”

Section: Introductionmentioning

confidence: 99%

A Drift-of-Stay Pattern Extraction Method for Indoor Pedestrian Trajectories for the Error and Accuracy Assessment of Indoor Wi-Fi Positioning

Wang

2019

IJGI

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The uncertainty of indoor Wi-Fi positioning is susceptible to many factors, such as sensor distribution, the internal environment (e.g., of a shopping mall), differences between receivers, and the flow of people. In this paper, an indoor pedestrian trajectory pattern mining approach for the assessment of the error and accuracy of indoor Wi-Fi positioning is proposed. First, the stay points of the customer were extracted from the pedestrian trajectories based on the spatiotemporal staying patterns of the customers in a shopping mall. Second, the drift points were distinguished from the stay points through analysis of noncustomer behavior patterns. Finally, the drift points were presented to calculate the errors in the pedestrian trajectories for the accuracy assessment of the indoor Wi-Fi positioning system. A one-month indoor pedestrian trajectories dataset from the Xinxiang Baolong shopping mall in Henan Province, China, was used for the assessment of the error and accuracy values with the proposed approach. The experimental results were verified by incorporating the distribution of the AP sensors. The proposed approach using big data pattern mining can explore the error distribution of indoor positioning systems, which can provide strong support for improving indoor positioning accuracy in the future.

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RFID-Based indoor localization using angle-of-arrival and return time

Şafak

2014

2014 22nd Signal Processing and Communications Applications Conference (SIU)

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A Novel Statistical AOA Model Pertinent to Indoor Geolocation

Cited by 3 publications

References 10 publications

Spatial Characterization of GNSS Multipath Channels

Spatial Characterization of GNSS Multipath Channels

A Drift-of-Stay Pattern Extraction Method for Indoor Pedestrian Trajectories for the Error and Accuracy Assessment of Indoor Wi-Fi Positioning

RFID-Based indoor localization using angle-of-arrival and return time

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