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Features for micro-Doppler based activity classification
Blekinge Institute of Technology, Faculty of Engineering, Department of Mathematics and Natural Sciences. Swedish Def Res Agcy FOI, SE-58111 Linkoping, Sweden.;Blekinge Inst Technol, SE-37179 Karlskrona, Sweden..
Swedish Def Res Agcy FOI, SE-58111 Linkoping, Sweden..
Swedish Def Res Agcy FOI, SE-58111 Linkoping, Sweden.;Linkoping Univ, SE-58183 Linkoping, Sweden..
2015 (English)In: IET radar, sonar & navigation, ISSN 1751-8784, E-ISSN 1751-8792, Vol. 9, no 9, 1181-1187 p.Article in journal (Refereed) PublishedText
Abstract [en]

Safety and security applications benefit from better situational awareness. Radar micro-Doppler signatures from an observed target carry information about the target's activity, and have potential to improve situational awareness. This article describes, compares, and discusses two methods to classify human activity based on radar micro-Doppler data. The first method extracts physically interpretable features from the time-velocity domain such as the main cycle time and properties of the envelope of the micro-Doppler spectra and use these in the classification. The second method derives its features based on the components with the most energy in the cadence-velocity domain (obtained as the Fourier transform of the time-velocity domain). Measurements from a field trial show that the two methods have similar activity classification performance. It is suggested that target base velocity and main limb cadence frequency are indirect features of both methods, and that they do often alone suffice to discriminate between the studied activities. This is corroborated by experiments with a reduced feature set. This opens up for designing new more compact feature sets. Moreover, weaknesses of the methods and the impact of non-radial motion are discussed.

Place, publisher, year, edition, pages
2015. Vol. 9, no 9, 1181-1187 p.
Keyword [en]
Doppler radar, Fourier transforms, feature extraction, micro-Doppler based activity classification, radar micro-Doppler signatures, physically interpretable feature extraction, time-velocity domain, cadence-velocity domain, Fourier transform
National Category
Communication Systems
URN: urn:nbn:se:bth-11346DOI: 10.1049/iet-rsn.2015.0084ISI: 000365855500007OAI: diva2:890739
Available from: 2016-01-04 Created: 2016-01-04 Last updated: 2017-01-16Bibliographically approved
In thesis
1. Signal Processing for Radar with Array Antennas and for Radar with Micro-Doppler Measurements
Open this publication in new window or tab >>Signal Processing for Radar with Array Antennas and for Radar with Micro-Doppler Measurements
2017 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Radar (RAdio Detection And Ranging) uses radio waves to detect the presence of a target and measure its position and other properties. This sensor has found many civilian and military applications due to advantages such as possible large surveillance areas and operation day and night and in all weather. The contributions of this thesis are within applied signal processing for radar in two somewhat separate research areas: 1) radar with array antennas and 2) radar with micro-Doppler measurements.

Radar with array antennas: An array antenna consists of several small antennas in the same space as a single large antenna. Compared to a traditional single-antenna radar, an array antenna radar gives higher flexibility, higher capacity, several radar functions simultaneously and increased reliability, and makes new types of signal processing possible which give new functions and higher performance.

The contributions on array antenna radar in this thesis are in three different problem areas. The first is High Resolution DOA (Direction Of Arrival) Estimation (HRDE) as applied to radar and using real measurement data. HRDE is useful in several applications, including radar applications, to give new functions and improve the performance. The second problem area is suppression of interference (clutter, direct path jamming and scattered jamming) which often is necessary in order to detect and localize the target. The thesis presents various results on interference signal properties, antenna geometry and subarray design, and on interference suppression methods. The third problem area is measurement techniques for which the thesis suggests two measurement designs, one for radar-like measurements and one for scattered signal measurements.

Radar with micro-Doppler measurements: There is an increasing interest and need for safety, security and military surveillance at short distances. Tasks include detecting targets, such as humans, animals, cars, boats, small aircraft and consumer drones; classifying the target type and target activity; distinguishing between target individuals; and also predicting target intention. An approach is to employ micro-Doppler radar to perform these tasks. Micro-Doppler is created by the movement of internal parts of the target, like arms and legs of humans and animals, wheels of cars and rotors of drones.

Using micro-Doppler, this thesis presents results on feature extraction for classification; on classification of targets types (humans, animals and man-made objects) and human gaits; and on information in micro-Doppler signatures for re-identification of the same human individual. It also demonstrates the ability to use different kinds of radars for micro-Doppler measurements. The main conclusion about micro-Doppler radar is that it should be possible to use for safety, security and military surveillance applications.

Place, publisher, year, edition, pages
Karlskrona: Blekinge Tekniska Högskola, 2017. 180 p.
Blekinge Institute of Technology Doctoral Dissertation Series, ISSN 1653-2090 ; 2
radar, signal processing, array antenna, subarray, clutter, jamming, interference, direction of arrival estimation, security, micro-Doppler, feature extraction, classification
National Category
Signal Processing
urn:nbn:se:bth-13639 (URN)978-91-7295-335-2 (ISBN)
Public defence
2017-03-31, Karlskrona, 00:00 (English)
Available from: 2017-01-16 Created: 2016-12-18 Last updated: 2017-01-16Bibliographically approved

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