Exploiting the Rules of the TF-MUSIC and Spatial Smoothing to Enhance the DOA Estimation for Coherent and Non-stationary Sources

Ruslan Zhagypar; Kalamkas Zhagyparova; Muhammad Tahir Akhtar

Exploiting the Rules of the TF-MUSIC and Spatial Smoothing to Enhance the DOA Estimation for Coherent and Non-stationary Sources

Ruslan Zhagypar, Kalamkas Zhagyparova, Muhammad Tahir Akhtar

Electrical and Computer Engineering

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

4 Scopus citations

Abstract

The paper introduces a combination of several techniques and methods to tackle the problem of Direction-of Arrival (DOA) estimation for coherent and non-stationary signals under severe noise conditions. Until now, these properties of the signals were studied by many researchers, yet the solutions were developed separately. At the first stage of the algorithm, the Spatial Time-Frequency Distribution (STFD) matrix is derived, which accounts for non-stationarity of the signals and allows denoising. The forward-backward spatial smoothing is applied to the STFD matrix to solve the problem of signals coherency. The main principle of the Root MUltiple SIgnal Classification (Root-MUSIC), namely, solving for the roots of the polynomial to obtain the signals DOA is exploited. The algorithm was simulated with coherent chirp signals with different Signal-to Noise Ratio (SNR) values to observe its efficiency compared to the conventional Root-MUSIC and Time-Frequency MUSIC TF-MUSIC) methods.

Original language	English (US)
Title of host publication	2020 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2020 - Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	236-241
Number of pages	6
ISBN (Electronic)	9789881476883
State	Published - Dec 7 2020
Event	2020 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2020 - Virtual, Auckland, New Zealand Duration: Dec 7 2020 → Dec 10 2020

Publication series

Name	2020 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2020 - Proceedings

Conference

Conference	2020 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2020
Country/Territory	New Zealand
City	Virtual, Auckland
Period	12/7/20 → 12/10/20

Bibliographical note

Publisher Copyright:
© 2020 APSIPA.

ASJC Scopus subject areas

Artificial Intelligence
Computer Networks and Communications
Computer Vision and Pattern Recognition
Hardware and Architecture
Signal Processing
Decision Sciences (miscellaneous)
Instrumentation

Cite this

Zhagypar, R., Zhagyparova, K., & Akhtar, M. T. (2020). Exploiting the Rules of the TF-MUSIC and Spatial Smoothing to Enhance the DOA Estimation for Coherent and Non-stationary Sources. In 2020 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2020 - Proceedings (pp. 236-241). Article 9306210 (2020 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2020 - Proceedings). Institute of Electrical and Electronics Engineers Inc..

Zhagypar, Ruslan ; Zhagyparova, Kalamkas ; Akhtar, Muhammad Tahir. / Exploiting the Rules of the TF-MUSIC and Spatial Smoothing to Enhance the DOA Estimation for Coherent and Non-stationary Sources. 2020 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2020 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2020. pp. 236-241 (2020 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2020 - Proceedings).

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title = "Exploiting the Rules of the TF-MUSIC and Spatial Smoothing to Enhance the DOA Estimation for Coherent and Non-stationary Sources",

abstract = "The paper introduces a combination of several techniques and methods to tackle the problem of Direction-of Arrival (DOA) estimation for coherent and non-stationary signals under severe noise conditions. Until now, these properties of the signals were studied by many researchers, yet the solutions were developed separately. At the first stage of the algorithm, the Spatial Time-Frequency Distribution (STFD) matrix is derived, which accounts for non-stationarity of the signals and allows denoising. The forward-backward spatial smoothing is applied to the STFD matrix to solve the problem of signals coherency. The main principle of the Root MUltiple SIgnal Classification (Root-MUSIC), namely, solving for the roots of the polynomial to obtain the signals DOA is exploited. The algorithm was simulated with coherent chirp signals with different Signal-to Noise Ratio (SNR) values to observe its efficiency compared to the conventional Root-MUSIC and Time-Frequency MUSIC TF-MUSIC) methods.",

author = "Ruslan Zhagypar and Kalamkas Zhagyparova and Akhtar, {Muhammad Tahir}",

note = "Publisher Copyright: {\textcopyright} 2020 APSIPA.; 2020 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2020 ; Conference date: 07-12-2020 Through 10-12-2020",

year = "2020",

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series = "2020 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2020 - Proceedings",

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Zhagypar, R , Zhagyparova, K & Akhtar, MT 2020, Exploiting the Rules of the TF-MUSIC and Spatial Smoothing to Enhance the DOA Estimation for Coherent and Non-stationary Sources. in 2020 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2020 - Proceedings., 9306210, 2020 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2020 - Proceedings, Institute of Electrical and Electronics Engineers Inc., pp. 236-241, 2020 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2020, Virtual, Auckland, New Zealand, 12/7/20.

Exploiting the Rules of the TF-MUSIC and Spatial Smoothing to Enhance the DOA Estimation for Coherent and Non-stationary Sources. / Zhagypar, Ruslan ; Zhagyparova, Kalamkas; Akhtar, Muhammad Tahir.
2020 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2020 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2020. p. 236-241 9306210 (2020 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2020 - Proceedings).

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

TY - GEN

T1 - Exploiting the Rules of the TF-MUSIC and Spatial Smoothing to Enhance the DOA Estimation for Coherent and Non-stationary Sources

AU - Zhagypar, Ruslan

AU - Zhagyparova, Kalamkas

AU - Akhtar, Muhammad Tahir

PY - 2020/12/7

Y1 - 2020/12/7

N2 - The paper introduces a combination of several techniques and methods to tackle the problem of Direction-of Arrival (DOA) estimation for coherent and non-stationary signals under severe noise conditions. Until now, these properties of the signals were studied by many researchers, yet the solutions were developed separately. At the first stage of the algorithm, the Spatial Time-Frequency Distribution (STFD) matrix is derived, which accounts for non-stationarity of the signals and allows denoising. The forward-backward spatial smoothing is applied to the STFD matrix to solve the problem of signals coherency. The main principle of the Root MUltiple SIgnal Classification (Root-MUSIC), namely, solving for the roots of the polynomial to obtain the signals DOA is exploited. The algorithm was simulated with coherent chirp signals with different Signal-to Noise Ratio (SNR) values to observe its efficiency compared to the conventional Root-MUSIC and Time-Frequency MUSIC TF-MUSIC) methods.

AB - The paper introduces a combination of several techniques and methods to tackle the problem of Direction-of Arrival (DOA) estimation for coherent and non-stationary signals under severe noise conditions. Until now, these properties of the signals were studied by many researchers, yet the solutions were developed separately. At the first stage of the algorithm, the Spatial Time-Frequency Distribution (STFD) matrix is derived, which accounts for non-stationarity of the signals and allows denoising. The forward-backward spatial smoothing is applied to the STFD matrix to solve the problem of signals coherency. The main principle of the Root MUltiple SIgnal Classification (Root-MUSIC), namely, solving for the roots of the polynomial to obtain the signals DOA is exploited. The algorithm was simulated with coherent chirp signals with different Signal-to Noise Ratio (SNR) values to observe its efficiency compared to the conventional Root-MUSIC and Time-Frequency MUSIC TF-MUSIC) methods.

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M3 - Conference contribution

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EP - 241

BT - 2020 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2020 - Proceedings

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2020 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2020

Y2 - 7 December 2020 through 10 December 2020

ER -

Zhagypar R , Zhagyparova K, Akhtar MT. Exploiting the Rules of the TF-MUSIC and Spatial Smoothing to Enhance the DOA Estimation for Coherent and Non-stationary Sources. In 2020 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2020 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2020. p. 236-241. 9306210. (2020 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2020 - Proceedings).

Exploiting the Rules of the TF-MUSIC and Spatial Smoothing to Enhance the DOA Estimation for Coherent and Non-stationary Sources

Abstract

Publication series

Conference

Bibliographical note

ASJC Scopus subject areas

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Cite this