Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/89153
Title: Comparisons of the Super-resolution TOA/TDOA Estimation Algorithms
Authors: Gao, Caicai
Wang, Guohua
Razul, Sirajudeen Gulam
Keywords: Signal Resolution
Signal to Noise Ratio
Issue Date: 2017
Source: Gao, C., Wang, G., & Razul, S. G. (2017). Comparisons of the Super-resolution TOA/TDOA Estimation Algorithms. 2017 Progress in Electromagnetics Research Symposium - Fall (PIERS - FALL), 2752-2758.
Abstract: In order to separate signals from different sources while estimating time of arrival (TOA), the super-resolution technique in range/time domain is desirable in the scenario of multi-target with high density or in the presence of strong multipath, due to the limitation on the bandwidth. In this paper, we provide an overview of several existing range super-resolution algorithms, including the adaptive regularization least squares (APLS) method, the inverse filter (IF), the iterative adaptive approach (IAA), the multiple signal classification (MUSIC) algorithm using cross correlation (MUSIC-CC), and the MUSIC algorithm based on channel response (MUSIC-CR). Both numerical data and trial data transmitted and received by the universal software radio peripheral (USRP) are used to compare their performance.
URI: https://hdl.handle.net/10356/89153
http://hdl.handle.net/10220/44834
DOI: 10.1109/PIERS-FALL.2017.8293604
Rights: © 2017 IEEE.
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:TL Conference Papers

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