Super-Resolution Time Delay Estimation Algorithm Based on the Frequency Domain Channel Model in OFDM Systems

Li, Jing; Liang, Peng; Cao, Maoyong; Dong, Yu

doi:10.1109/wcica.2006.1713371

Cited by 2 publications

(1 citation statement)

References 4 publications

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“…The simulation results show that super-resolution techniques can significantly improve the performance of TOA estimation as compared with conventional techniques including direct IFT and DSSS signal-based cross-correlation techniques. Jing et al [ 24 ] proposed a frequency-domain-based cross-spectral super-resolution time delay estimate algorithm, and the method performed an accurate time delay estimation in the multipath channel model that they proposed in the paper. Fang et al [ 25 ] compared the performance of the super-resolution method with MUSIC and a traditional cross-correlation algorithm in a simulated indoor multipath TOA environment, the simulation results showed that TOA estimation with time domain channel estimation can approach high level accuracy and stability.…”

Section: Introductionmentioning

confidence: 99%

A Novel Time Delay Estimation Algorithm for 5G Vehicle Positioning in Urban Canyon Environments

Deng

Zheng

Wang

et al. 2020

Sensors

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Vehicle positioning with 5G can effectively compensate for the lack of vehicle positioning based on GNSS (Global Navigation Satellite System) in urban canyons. However, there is also a large ranging error in the non-line of sight (NLOS) propagation of 5G. Aiming to solve this problem, we consider a new time delay estimation algorithm called non-line of sight cancellation multiple signal classification (NC-MUSIC). This algorithm uses cross-correlation to identify and cancel the NLOS signal. Then, an unsupervised multipath estimation method is used to estimate the number of multipaths and extract the noise subspace. The MUSIC spectral function can be calculated by the noise subspace. Finally, the time delay of the direct path is estimated by searching the peak of MUSIC spectral function. This paper adopts the 5G channel model developed by 3GPP TR38.901 for simulation experiments. The experiment results demonstrated that the proposed algorithm has obvious advantages in terms of NLOS propagation for urban canyon environments. It provided a high-precision time delay estimation algorithm for observed time difference of arrival (OTDOA), joint angle of arrival (AOA) ranging, and other positioning methods in the 5G vehicle positioning method, which can effectively improve the positioning accuracy of 5G vehicle positioning in urban canyon environments.

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Section: Introductionmentioning

confidence: 99%

A Novel Time Delay Estimation Algorithm for 5G Vehicle Positioning in Urban Canyon Environments

Deng

Zheng

Wang

et al. 2020

Sensors

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an Improved Indoor Geolocation Algorithm based on Log-distance Path Loss Model

Pei

Liu

Wang³

et al. 2016

Proceedings of the 2016 International Conference on Computer and Information Technology Applications

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This paper proposes an indoor localization algorithm based on Log-distance path loss model. The two parameters of the Log-distance path loss model are estimated by the measured RSSI data. Then the two step filtering was carried out to keep the RSSI signals with the higher probabilities. Finally the Taylor's series iteration method is used to compute the position coordinate of the moving objects. The experiment results show that the location error is no more than 3m.

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Super-Resolution Time Delay Estimation Algorithm Based on the Frequency Domain Channel Model in OFDM Systems

Cited by 2 publications

References 4 publications

A Novel Time Delay Estimation Algorithm for 5G Vehicle Positioning in Urban Canyon Environments

A Novel Time Delay Estimation Algorithm for 5G Vehicle Positioning in Urban Canyon Environments

an Improved Indoor Geolocation Algorithm based on Log-distance Path Loss Model

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