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Clutter Cancellation Methods for Small Target Detection Using High-Resolution W-band Radar

Drones are currently being used for various applications. However, the detection of drones for defense or security purposes has become problematic because of the use of plastic materials and the small size of these drones. Any drone can be placed under surveillance to accurately determine its positi...

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Autores principales: Hwang, Woosung, Jang, Hongje, Choi, Myungryul
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10490681/
https://www.ncbi.nlm.nih.gov/pubmed/37688013
http://dx.doi.org/10.3390/s23177557
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author Hwang, Woosung
Jang, Hongje
Choi, Myungryul
author_facet Hwang, Woosung
Jang, Hongje
Choi, Myungryul
author_sort Hwang, Woosung
collection PubMed
description Drones are currently being used for various applications. However, the detection of drones for defense or security purposes has become problematic because of the use of plastic materials and the small size of these drones. Any drone can be placed under surveillance to accurately determine its position by collecting high-resolution data using various detectors such as the radar system proposed in this paper. The W-band radar has a high carrier frequency, which makes it easy to design a wide bandwidth system, and the wideband FMCW signal is suitable for creating high resolution images from a distance. Unfortunately, the huge amounts of data gathered in this way also contain clutter (such as background data and noise) that is usually generated from unstable radar systems and complex environmental factors, and which frequently gives rise to distorted data. Accurate extraction of the position of the target from this big data requires the clutter to be suppressed and canceled, but conventional clutter cancellation methods are not suitable. Four clutter cancellation algorithms are assessed and compared: standard deviation, adaptive least mean squares (LMS), recursive least squares (RLS), and the proposed LMS. The proposed LMS has combined LMS with the standard deviation method. First, the big data pertaining to the target position is collected using the W-band radar system. Subsequently, the target position is calculated by applying these algorithms. The performance of the proposed algorithms is measured and compared to that of the other three algorithms by conducting outdoor experiments.
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spelling pubmed-104906812023-09-09 Clutter Cancellation Methods for Small Target Detection Using High-Resolution W-band Radar Hwang, Woosung Jang, Hongje Choi, Myungryul Sensors (Basel) Communication Drones are currently being used for various applications. However, the detection of drones for defense or security purposes has become problematic because of the use of plastic materials and the small size of these drones. Any drone can be placed under surveillance to accurately determine its position by collecting high-resolution data using various detectors such as the radar system proposed in this paper. The W-band radar has a high carrier frequency, which makes it easy to design a wide bandwidth system, and the wideband FMCW signal is suitable for creating high resolution images from a distance. Unfortunately, the huge amounts of data gathered in this way also contain clutter (such as background data and noise) that is usually generated from unstable radar systems and complex environmental factors, and which frequently gives rise to distorted data. Accurate extraction of the position of the target from this big data requires the clutter to be suppressed and canceled, but conventional clutter cancellation methods are not suitable. Four clutter cancellation algorithms are assessed and compared: standard deviation, adaptive least mean squares (LMS), recursive least squares (RLS), and the proposed LMS. The proposed LMS has combined LMS with the standard deviation method. First, the big data pertaining to the target position is collected using the W-band radar system. Subsequently, the target position is calculated by applying these algorithms. The performance of the proposed algorithms is measured and compared to that of the other three algorithms by conducting outdoor experiments. MDPI 2023-08-31 /pmc/articles/PMC10490681/ /pubmed/37688013 http://dx.doi.org/10.3390/s23177557 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Communication
Hwang, Woosung
Jang, Hongje
Choi, Myungryul
Clutter Cancellation Methods for Small Target Detection Using High-Resolution W-band Radar
title Clutter Cancellation Methods for Small Target Detection Using High-Resolution W-band Radar
title_full Clutter Cancellation Methods for Small Target Detection Using High-Resolution W-band Radar
title_fullStr Clutter Cancellation Methods for Small Target Detection Using High-Resolution W-band Radar
title_full_unstemmed Clutter Cancellation Methods for Small Target Detection Using High-Resolution W-band Radar
title_short Clutter Cancellation Methods for Small Target Detection Using High-Resolution W-band Radar
title_sort clutter cancellation methods for small target detection using high-resolution w-band radar
topic Communication
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10490681/
https://www.ncbi.nlm.nih.gov/pubmed/37688013
http://dx.doi.org/10.3390/s23177557
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