Open AccessPerformance of Digital Drone Signage System Based on DUET
Author(s) -
Isaac Sim,
Young Ghyu Sun,
Soo Hyun Kim,
Sang Woon Lee,
Cheong Ghil Kim,
Jin Young Kim
Publication year - 2022
Publication title -
journal of web engineering/journal of web engineering on line
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.151
H-Index - 13
eISSN - 1544-5976
pISSN - 1540-9589
DOI - 10.13052/jwe1540-9589.21211
Subject(s) - computer science , signage , signal (programming language) , artificial intelligence , scheme (mathematics) , drone , attenuation , algorithm , pattern recognition (psychology) , mathematics , art , mathematical analysis , physics , biology , optics , visual arts , genetics , programming language
In this letter, we study a scenario based on degenerate unmixing estimation technique (DUET) that separates original signals from mixture of FHSS signals with two antennas. We have shown that the assumptions for separating mixed signals in DUET can be applied to drone based digital signage recognition signals and proposed the DUET-based separation scheme (DBSS) to classify the mixed recognition drone signals by extracting the delay and attenuation components of the mixture signal through the likelihood function and the short-term Fourier transform (STFT). In addition, we propose an iterative algorithm for signal separation with the conventional DUET scheme. Numerical results showed that the proposed algorithm is more separation-efficient compared to baseline schemes. DBSS can separate all signals within about 0.56 seconds when there are fewer than nine signage signals.