Time-frequency analysis of millimeter-wave radar micro-Doppler data from small UAVs

Samiur Rahman; Duncan Robertson

doi:10.1109/SSPD.2017.8233269

Time-frequency analysis of millimeter-wave radar micro-Doppler data from small UAVs

Samiur Rahman, Duncan Robertson

School of Physics and Astronomy

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

Abstract

Micro-Doppler feature analysis of small UAVs (sUAVs) is of great importance for identifying such targets. This paper discusses methods that can be used for analyzing various Doppler features present in the radar signal return from sUAVs. A 94 GHz radar is used in both CW and FMCW modes for data collection, and produces high fidelity micro-Doppler returns. Wavelet decomposition method is then used to extract the high frequency components of the signal that correspond to the characteristic fast moving parts of the sUAVs. Finally, time-frequency analysis is performed to visualize and interpret the features.

Original language	English
Title of host publication	2017 Sensor Signal Processing for Defence Conference (SSPD)
Publisher	Institute of Electrical and Electronics Engineers Inc.
Number of pages	5
ISBN (Print)	9781538616635
DOIs	https://doi.org/10.1109/SSPD.2017.8233269
Publication status	Published - 21 Dec 2017
Event	2017 Sensor Signal Processing for Defence Conference (SSPD) - London, United Kingdom Duration: 6 Dec 2017 → 7 Dec 2017 https://www.sspd.eng.ed.ac.uk/conference-archive/2017/welcome (Conference website)

Conference

Conference	2017 Sensor Signal Processing for Defence Conference (SSPD)
Abbreviated title	SSPD
Country/Territory	United Kingdom
City	London
Period	6/12/17 → 7/12/17
Internet address	https://www.sspd.eng.ed.ac.uk/conference-archive/2017/welcome (Conference website)

Keywords

Wavelet
sUAV
Drone
Millimeter-wave
Radar
FMCW
CW

Access to Document

10.1109/SSPD.2017.8233269

Effective and affordable detection: Effective and Affordable Detection and Small UAVs using millimetre wave coherent Doppler Radar
Robertson, D. (PI)
Science & Technology Facilities Council
1/06/16 → 31/01/19
Project: Standard

Cite this

@inproceedings{11bdae6a94d342a9a2bc90563c7efbd7,

title = "Time-frequency analysis of millimeter-wave radar micro-Doppler data from small UAVs",

abstract = "Micro-Doppler feature analysis of small UAVs (sUAVs) is of great importance for identifying such targets. This paper discusses methods that can be used for analyzing various Doppler features present in the radar signal return from sUAVs. A 94 GHz radar is used in both CW and FMCW modes for data collection, and produces high fidelity micro-Doppler returns. Wavelet decomposition method is then used to extract the high frequency components of the signal that correspond to the characteristic fast moving parts of the sUAVs. Finally, time-frequency analysis is performed to visualize and interpret the features.",

keywords = "Wavelet, sUAV, Drone, Millimeter-wave, Radar, FMCW, CW",

author = "Samiur Rahman and Duncan Robertson",

note = "Funding: UK Science and Technology Facilities Council (STFC) under grant ST/N006569/1.; 2017 Sensor Signal Processing for Defence Conference (SSPD), SSPD ; Conference date: 06-12-2017 Through 07-12-2017",

year = "2017",

month = dec,

day = "21",

doi = "10.1109/SSPD.2017.8233269",

language = "English",

isbn = "9781538616635",

booktitle = "2017 Sensor Signal Processing for Defence Conference (SSPD)",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

address = "United States",

url = "https://www.sspd.eng.ed.ac.uk/conference-archive/2017/welcome",

}

Rahman, S & Robertson, D 2017, Time-frequency analysis of millimeter-wave radar micro-Doppler data from small UAVs. in 2017 Sensor Signal Processing for Defence Conference (SSPD)., 8233269, Institute of Electrical and Electronics Engineers Inc., 2017 Sensor Signal Processing for Defence Conference (SSPD), London, United Kingdom, 6/12/17. https://doi.org/10.1109/SSPD.2017.8233269

TY - GEN

T1 - Time-frequency analysis of millimeter-wave radar micro-Doppler data from small UAVs

AU - Rahman, Samiur

AU - Robertson, Duncan

N1 - Funding: UK Science and Technology Facilities Council (STFC) under grant ST/N006569/1.

PY - 2017/12/21

Y1 - 2017/12/21

N2 - Micro-Doppler feature analysis of small UAVs (sUAVs) is of great importance for identifying such targets. This paper discusses methods that can be used for analyzing various Doppler features present in the radar signal return from sUAVs. A 94 GHz radar is used in both CW and FMCW modes for data collection, and produces high fidelity micro-Doppler returns. Wavelet decomposition method is then used to extract the high frequency components of the signal that correspond to the characteristic fast moving parts of the sUAVs. Finally, time-frequency analysis is performed to visualize and interpret the features.

AB - Micro-Doppler feature analysis of small UAVs (sUAVs) is of great importance for identifying such targets. This paper discusses methods that can be used for analyzing various Doppler features present in the radar signal return from sUAVs. A 94 GHz radar is used in both CW and FMCW modes for data collection, and produces high fidelity micro-Doppler returns. Wavelet decomposition method is then used to extract the high frequency components of the signal that correspond to the characteristic fast moving parts of the sUAVs. Finally, time-frequency analysis is performed to visualize and interpret the features.

KW - Wavelet

KW - sUAV

KW - Drone

KW - Millimeter-wave

KW - Radar

KW - FMCW

KW - CW

U2 - 10.1109/SSPD.2017.8233269

DO - 10.1109/SSPD.2017.8233269

M3 - Conference contribution

SN - 9781538616635

BT - 2017 Sensor Signal Processing for Defence Conference (SSPD)

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2017 Sensor Signal Processing for Defence Conference (SSPD)

Y2 - 6 December 2017 through 7 December 2017

ER -

Time-frequency analysis of millimeter-wave radar micro-Doppler data from small UAVs

Abstract

Conference

Keywords

Access to Document

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Projects

Effective and affordable detection: Effective and Affordable Detection and Small UAVs using millimetre wave coherent Doppler Radar

Cite this