IMPROVING THE ACCURACY OF MODEL ORDER ESTIMATION IN MULTIBAND SIGNAL FUSION

Di Xiong; Junling Wang; Zhenhong Chen; Yuan Jiang

doi:10.1049/icp.2021.0515

IMPROVING THE ACCURACY OF MODEL ORDER ESTIMATION IN MULTIBAND SIGNAL FUSION

Di Xiong, Junling Wang^*, Zhenhong Chen, Yuan Jiang

^*Corresponding author for this work

School of Information and Electronics

Beijing Institute of Radio Metrology & Measurement

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Citations (Scopus)

Abstract

This paper proposes a method to estimate the model order based on the singular values of a synthetic real matrix. The synthetic data matrix includes the complex observation data and its conjugate data, which fully exploits the existing data information, is more suitable for model order estimation of multiband signal fusion spectrum than the complex observation matrix. Simulation experiments show that this method has better results than the traditional model order estimation methods based on complex observation data matrix, the model order can be estimated at a lower signal to noise ratio (SNR).

Original language	English
Title of host publication	IET Conference Proceedings
Publisher	Institution of Engineering and Technology
Pages	1707-1710
Number of pages	4
Volume	2020
Edition	9
ISBN (Electronic)	9781839535406
DOIs	https://doi.org/10.1049/icp.2021.0515
Publication status	Published - 2020
Event	5th IET International Radar Conference, IET IRC 2020 - Virtual, Online Duration: 4 Nov 2020 → 6 Nov 2020

Conference

Conference	5th IET International Radar Conference, IET IRC 2020
City	Virtual, Online
Period	4/11/20 → 6/11/20

Keywords

MODEL ORDER ESTIMATION
MULTIBAND FUSION
SINGULAR VALUE DECOMPOSITION

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10.1049/icp.2021.0515

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title = "IMPROVING THE ACCURACY OF MODEL ORDER ESTIMATION IN MULTIBAND SIGNAL FUSION",

abstract = "This paper proposes a method to estimate the model order based on the singular values of a synthetic real matrix. The synthetic data matrix includes the complex observation data and its conjugate data, which fully exploits the existing data information, is more suitable for model order estimation of multiband signal fusion spectrum than the complex observation matrix. Simulation experiments show that this method has better results than the traditional model order estimation methods based on complex observation data matrix, the model order can be estimated at a lower signal to noise ratio (SNR).",

keywords = "MODEL ORDER ESTIMATION, MULTIBAND FUSION, SINGULAR VALUE DECOMPOSITION",

author = "Di Xiong and Junling Wang and Zhenhong Chen and Yuan Jiang",

note = "Publisher Copyright: {\textcopyright} 2020 IET Conference Proceedings. All rights reserved.; 5th IET International Radar Conference, IET IRC 2020 ; Conference date: 04-11-2020 Through 06-11-2020",

year = "2020",

doi = "10.1049/icp.2021.0515",

language = "English",

volume = "2020",

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T1 - IMPROVING THE ACCURACY OF MODEL ORDER ESTIMATION IN MULTIBAND SIGNAL FUSION

AU - Xiong, Di

AU - Wang, Junling

AU - Chen, Zhenhong

AU - Jiang, Yuan

PY - 2020

Y1 - 2020

N2 - This paper proposes a method to estimate the model order based on the singular values of a synthetic real matrix. The synthetic data matrix includes the complex observation data and its conjugate data, which fully exploits the existing data information, is more suitable for model order estimation of multiband signal fusion spectrum than the complex observation matrix. Simulation experiments show that this method has better results than the traditional model order estimation methods based on complex observation data matrix, the model order can be estimated at a lower signal to noise ratio (SNR).

AB - This paper proposes a method to estimate the model order based on the singular values of a synthetic real matrix. The synthetic data matrix includes the complex observation data and its conjugate data, which fully exploits the existing data information, is more suitable for model order estimation of multiband signal fusion spectrum than the complex observation matrix. Simulation experiments show that this method has better results than the traditional model order estimation methods based on complex observation data matrix, the model order can be estimated at a lower signal to noise ratio (SNR).

KW - MODEL ORDER ESTIMATION

KW - MULTIBAND FUSION

KW - SINGULAR VALUE DECOMPOSITION

UR - http://www.scopus.com/inward/record.url?scp=85160301231&partnerID=8YFLogxK

U2 - 10.1049/icp.2021.0515

DO - 10.1049/icp.2021.0515

M3 - Conference contribution

AN - SCOPUS:85160301231

VL - 2020

SP - 1707

EP - 1710

BT - IET Conference Proceedings

PB - Institution of Engineering and Technology

T2 - 5th IET International Radar Conference, IET IRC 2020

Y2 - 4 November 2020 through 6 November 2020

ER -

IMPROVING THE ACCURACY OF MODEL ORDER ESTIMATION IN MULTIBAND SIGNAL FUSION

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Keywords

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