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Performance comparison of MVDR, MUSIC, and ESPRIT algorithms in signal classification


Article Information

Title: Performance comparison of MVDR, MUSIC, and ESPRIT algorithms in signal classification

Authors: Macario O. Corde, Elmer R. Magsino

Journal: ARPN Journal of Engineering and Applied Sciences

HEC Recognition History
Category From To
Y 2023-07-01 2024-09-30
Y 2022-07-01 2023-06-30
Y 2021-07-01 2022-06-30
X 2020-07-01 2021-06-30

Publisher: Khyber Medical College, Peshawar

Country: Pakistan

Year: 2020

Volume: 15

Issue: 21

Language: English

Categories

Abstract

In this study, the performance of three well-known algorithms for classifying/localizing arriving signals at an array of antennas is presented. These three algorithms are (1) Minimum Variance Distortionless Response (MVDR), (2) Multiple Signal Classification (MUSIC), and (3) Estimation of Signal Parameter via Rotational Invariance (ESPRIT). Exhaustive simulations are done to evaluate and analyze these three localization algorithms where the array SNR, separation and relative power of sources, and number of samples varied to determine how each algorithm performs. Simulation results show that MVDR relies on the received signal’s relative power, while both MUSIC and ESPRIT can still detect signals that are closely spaced.


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