Modeling received signal strength and multipath propagation effects of moving persons

Cimdins, Marco; Hellbrück, Horst

doi:10.1109/wpnc.2017.8250061

Cited by 7 publications

(5 citation statements)

References 13 publications

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“…The diffraction model describes how an obstacle alters the signal transmitted by T x and measured by Rx. The knife-edge model has been initially derived for a radio frequency-based system [11] in 2017. The knife-edge model describes the influence on the magnitude and phase of an obstacle, such as a person, on the transmitted radio waves.…”

Section: A Diffraction Modelmentioning

confidence: 99%

“…This paper transfers the knife-edge diffraction model developed for radio frequency-based localization to underwater ultrasonic applications. Also, we extend the model with reflectors [11], transmission through the obstacle in between the line-of-sight (LOS), wideband pulses, and time finite signals with phase accurate superposition.…”

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

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Underwater Ultrasonic Multipath Diffraction Model for Short Range Communication and Sensing Applications

2021

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In acoustic underwater communication and sonar applications, obstacles inside and outside the line-of-sight (LOS) affect signal propagation. Both reflection and diffraction occur in underwater communication and measurement systems due to these obstacles. To the best of our knowledge, the influence of diffraction and reflection is neither described nor modeled for finite pulses yet. We propose and develop a multipath propagation model for spectral diffraction components and phase information of the received signal based on knife-edge diffraction together with reflections, transmission effects, and backscatter. This paper designs a short range underwater ultrasonic experimental system composed of an ultrasonic transceiver with wideband pulses and advanced spectral signal processing. We evaluate our proposed model with measurements made in a water tank with an obstacle moved between the transmitter and receiver. When the model includes all major propagation components and effects, it achieves an accuracy for localization of 97 % of the results in the range of twice the obstacle diameter in our test setup.

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Section: A Diffraction Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Underwater Ultrasonic Multipath Diffraction Model for Short Range Communication and Sensing Applications

2021

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“…Our goal is to develop a model-based device-free localization system that is free from extensive training periods. In [ 18 ], we model the impact of a person with a knife-edge diffraction model. Although the model has been derived for narrowband radio-frequency signals, we applied the model to the magnitude and phase values that are extracted from multipath components of CIR measurements [ 6 ].…”

Section: Related Workmentioning

confidence: 99%

“…Figure 2 shows a typical scenario. For more details on this model, we refer to our previous publication in [ 18 ].…”

Section: Mampi Dfl Approachmentioning

confidence: 99%

MAMPI-UWB—Multipath-Assisted Device-Free Localization with Magnitude and Phase Information with UWB Transceivers

Cimdins

Schmidt

Hellbrück

2020

Sensors

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In this paper, we propose a multipath-assisted device-free localization (DFL) system that includes magnitude and phase information (MAMPI). The DFL system employs ultra-wideband (UWB) channel impulse response (CIR) measurements, enabling the extraction of several multipath components (MPCs) and thereby benefits from multipath propagation. We propose a radio propagation model that calculates the effect on the received signal based on the position of a person within a target area. Additionally, we propose a validated error model for the measurements and explain the creation of different feature vectors and extraction of the MPCs from Decawave DW1000 CIR measurements. We evaluate the system via simulations of the position error probability and a measurement setup in an indoor scenario. We compare the performance of MAMPI to a conventional DFL system based on four sensor nodes that measures radio signal strength values. The combination of the magnitude and phase differences for the feature vectors results in a position error probability that is comparable to a conventional system but requires only two sensor nodes.

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MAMPI – Multipath-assisted Device-free Localization with Magnitude and Phase Information

Cimdins

Schmidt

Hellbrück

2020

2020 International Conference on Localization and GNSS (ICL-GNSS)

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Modeling received signal strength and multipath propagation effects of moving persons

Cited by 7 publications

References 13 publications

Underwater Ultrasonic Multipath Diffraction Model for Short Range Communication and Sensing Applications

Underwater Ultrasonic Multipath Diffraction Model for Short Range Communication and Sensing Applications

MAMPI-UWB—Multipath-Assisted Device-Free Localization with Magnitude and Phase Information with UWB Transceivers

MAMPI – Multipath-assisted Device-free Localization with Magnitude and Phase Information

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